BACKGROUND

Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. One area of interest involves mapping functions that are based on determined locations of points of interest ("POI") rather than conventional mapping techniques.

SOME EXAMPLE EMBODIMENTS

Therefore, there is a need for an approach for generating map data based on point of interest location information.

According to one embodiment, a method comprises processing and/or facilitating a processing of metadata associated with one or more points of interest to cause, at least in part, a designation of the one or more points of interests as one or more location nodes. The method also comprises causing, at least in part, a construction of a location graph based, at least in part, on one or more connections among the one or more locations nodes. The method further comprises determining at least an approximation of one or more features based, at least in part, on the location graph.

According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code for one or more computer programs, the at least one memory and the computer program code configured to, with the at least one processor, cause, at least in part, the apparatus to process and/or facilitate a processing of metadata associated with one or more points of interest to cause, at least in part, a designation of the one or more points of interests as one or more location nodes. The apparatus is also caused to cause, at least in part, a construction of a location graph based, at least in part, on one or more connections among the one or more locations nodes. The apparatus is further caused to determine at least an approximation of one or more features based, at least in part, on the location graph.

According to another embodiment, a computer-readable storage medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause, at least in part, an apparatus to process and/or facilitate a processing of metadata associated with one or more points of interest to cause, at least in part, a designation of the one or more points of interests as one or more location nodes. The apparatus is also caused to cause, at least in part, a construction of a location graph based, at least in part, on one or more connections among the one or more locations nodes. The apparatus is further caused to determine at least an approximation of one or more features based, at least in part, on the location graph. According to another embodiment, an apparatus comprises means for processing and/or facilitating a processing of metadata associated with one or more points of interest to cause, at least in part, a designation of the one or more points of interests as one or more location nodes. The apparatus also comprises means for causing, at least in part, a construction of a location graph based, at least in part, on one or more connections among the one or more locations nodes. The apparatus further comprises means for determining at least an approximation of one or more features based, at least in part, on the location graph.

In addition, for various example embodiments of the invention, the following is applicable: a method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on (or derived at least in part from) any one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

For various example embodiments of the invention, the following is also applicable: a method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform any one or any combination of network or service provider methods (or processes) disclosed in this application.

For various example embodiments of the invention, the following is also applicable: a method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on data and/or information resulting from one or any combination of methods or processes disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. For various example embodiments of the invention, the following is also applicable: a method comprising creating and/or modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based at least in part on data and/or information resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention. In various example embodiments, the methods (or processes) can be accomplished on the service provider side or on the mobile device side or in any shared way between service provider and mobile device with actions being performed on both sides. For various example embodiments, the following is applicable: An apparatus comprising means for performing the method of any of originally filed claims 1 -17, 35-51 , and 57-59.

Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings:

FIG. 1 is a diagram of a system capable of generating map data based on point of interest location information, according to one embodiment;

FIG. 2 is a diagram of the components of a navigation platform, according to one embodiment; FIG. 3 is a flowchart of a process for generating map data based on point of interest location information, according to one embodiment;

FIG. 4 is an illustration of a map having multiple points of interest, according to one embodiment;

FIG. 5 is an illustration of a map having multiple designated clusters of POFs, according to one embodiment;

FIG. 6 is a diagram of a user interface for accessing generated map data based on point of interest information, according to one embodiment;

FIG. 7 is a diagram of hardware that can be used to implement an embodiment of the invention; FIG. 8 is a diagram of a chip set that can be used to implement an embodiment of the invention; and

FIG. 9 is a diagram of a mobile terminal (e.g., handset) that can be used to implement an embodiment of the invention.

DESCRIPTION OF SOME EMBODIMENTS

Examples of a method, apparatus, and computer program for generating map data based on point of interest location information are disclosed. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.

FIG. 1 is a diagram of a system capable of generating map data based on point of interest location information, according to one embodiment. It can be extremely challenging to obtain a detailed road network for a majority of cities (especially tier 2 and tier 3 cities) in emerging countries for many reasons. For example, these cities usually do not have a planned structure, and there might be various narrow lane roads, and streets as opposed to major highways. Official entry of these roads may be difficult to obtain. Further, companies that have specialized GPS enabled cars employ people to drive around the city to obtain road network information. While this approach ensures a detailed road network, emerging cities may not actually have passable roadways in many areas, and services and companies that want to deploy location based services and/or navigation services, need to purchase this data, which could be expensive.

To address this problem, a system 100 of FIG. 1 introduces the capability to generate map data based on point of interest location information. Obtaining geo-coded POI data by using crowd sourcing or other ways can be a less expensive option for these companies. Leveraging a POI database that is geocoded for different cities. The POI database can be obtained either by using crowd sourcing techniques or can be procured from conventional mapping companies. If the POIs are not geocoded, different geo-coding techniques can be used to geocode the POIs. In one embodiment, the geocoded POI database may be an input to the system 100.

In one or more embodiments, each POI data has meta-data associated with it such as building name, street name, landmark reference, area name, city, geo -coordinates etc. This metadata may be used to cluster the POI data. For example, all the POIs belonging to a city "x" that have the same street name "y" and are within a distance "z" may be grouped in a single cluster. A node may be associated with each cluster. For a given street name, there could be multiple nodes, and the nodes may be connected with one another. Nodes that have different street names but are at a close proximity of each other may also be connected. Edge weights may be determined that represent a distance between any two nodes. A graph may then be constructed in this fashion to represent an approximate road network.

According to various embodiments, navigation may be carried out based on the graph constructed above by running, for example, a standard shortest path algorithm such as Dijkstra's. Since the nodes encompass POIs, the routes may be presented to that has references to the applied POIs. For example, a route description could be - "Continue on M.G. Road for about 5 KM until you reach Barista Coffee, make a right near Barista Coffee to get onto S.V. road, stay on S.V. road, you will see St. Francis school to your right in 2 KM, continue on S.V. road next you will see Mount Mary Church in 4 KM, make a left near Mount Mary Church to get onto Simpoli Road, continue 4 KM and your destination will be next to Ganesh stores." As shown in FIG. 1, the system 100 comprises a user equipment (UE) 101 having connectivity to a navigation platform 103, a social networking service 107, a navigation service 109 and POI database 1 11 via a communication network 105.

According to various embodiments, POI data may be processed by the navigation platform 103 based on information available in the POI database 1 11. As discussed above, the system 100 may rely on an abundance of good quality, rich POI data and landmark data for road network construction. POIs or landmarks in emerging countries not only refer to places like malls, historical monuments, cinema theatres, hospitals, schools, etc. but also refer to local stores, shops and vendors. In India, for example, there are several popular local "mom and pop" kinds of stores like tea shops, grocery stores, gas stations, restaurants, etc. Therefore there is an abundance of POI data in these countries. This data can be collected in an efficient and speedy manner by using crowd sourcing techniques.

According to various embodiments, any POI crowd sourcing technique for collecting, verifying and grouping large amount of high-quality POI data may be used to populate the POI database 1 11. The POIs collected by any of users of UE 101 and shared with the social networking service 107 and/or the navigation service 109 have rich-meta data (including geo-coordinates) associated with them. U.S. Patent Application Publication No. 2011/0151898 entitled "Method and Apparatus for grouping Points of interest according to area names" is one example of an efficient way to collect and determine POI data by using a crowd sourcing technique. Table 1-1 below illustrates example POI data that may be collected by the navigation service 109 or a user by way of the social networking service 107 and stored in the POI database 1 11 for processing by the navigation platform 103.

> POI Name: Khana Khazana

> Building Number/Name: 147/11 , Museum Inn

> Street Name: Museum Road

> Landmark(s): Above Ruby Tuesday

> Area name: Church Street

> City: Bengalaru

> State: Karnataka

> Pin Code - 560 001

> Phone number - 9821032295

> GPS coordinates: (lat: 12.9777002335, long:

77.6293029785)

> Cellld: 4801

> CBS (area name): Church Street

> Date: 02/16/2011

Table 1-1 Sample POI data

Other sources of POI data can be used such as the Yellow Pages, or other possible sources of POI data. However, if the POI data from these other sources is not geo-coded, then it may be required to geo-code these POIs that are produced by other sources to be stored in the POI database 111 and usable by the navigation platform 103.

In one or more embodiments, the system 100, by way of the navigation platform 103, may construct an approximate road network based on the POI data available in the POI database 11 1. From a high level, constructing the approximate road network involves clustering available POI data and connecting the POI data via the clusters to form a graph. The graph that is constructed represents the approximate road network.

According to one example embodiment, clustering may be described as follows. The POI data available in a given city can have an uneven distribution. There could be certain pockets in the city where the POI distribution is high and these would represent crowded residential areas or business areas or downtown regions. There could be a sparse distribution in certain remote parts of the city. In the clustering step, any unevenly distributed POI data points may be grouped. Fig. 4, discussed below, shows the distribution of POI data points in a given city across different streets. The POI data (such as that illustrated above in Table 1-1) has meta-data such as building name, area name, landmark, city, GPS co-ordinates associated with it. The navigation platform 103 uses all or some of this information for clustering or grouping various POI data points. For each POI, the navigation platform 103 searches for other POIs that are within a distance of k KM and have the same street name. This step can be simply implemented by using range queries in a spatial database. A query such as "Find POIs with street name = X within distance K" can be given to the spatial database. This can reduce the complexity of comparing each POI with every other POI. The clusters can be stored in a spatial database such as POI database 1 1 1 and spatial indexes can be used for optimizing query performance.

In one or more embodiments, when clustering the available POI data points, the navigation platform 103 considers all the POI data points belonging to a particular city, for example city Y. Then, the navigation platform 103 considers all the POI data points that have the same street name, for example street "X" and puts them in a set S xy. If any particular POI does not have street name information, then the navigation platform 103 may look to the POI's landmark field available in the Table 1-1 , for example. Then, the navigation platform 103 tries to determine the street name of the landmark.

Formally, S_xy = {p_l , p_2, ...,p_n} contains n POIs that have street name = X and city = Y. The navigation platform 103 considers each POI (p i) in S xy, for i= (1 to n). For each p i, navigation platform 103 considers all other POIs p_j where i and j are different, and compute the distance d(p_i, p_j). If d(p_i, pj) < k, (where k is a parameter of the system) then p i and p_j belong to the same cluster C_i. The navigation platform 103 marks POI p_j to be clustered and removes it from S_xy and does not consider it again for clustering. After considering all the POIs in set S_xy, the navigation platform 103 generates a set C_xy = {C_l , C_2, ..,C_m} of clusters for a street X and city Y. The property of these clusters is that each cluster encompasses POIs that belong to the same street and are physically close to each other.

According to one example embodiment, graph construction may be described as follows. After the clusters are created, the navigation platform 103 associates a node N_i with each cluster C_i. The centroid of each cluster C_i represents the geo-coordinates of the node N_i. Fig. 5, discussed below, illustrates the cluster formation and node association step. Each cluster, and in return each node, groups POIs that are physically close to each other along a given street. For example, nodes 1 ,2,3,4,5,6,7 may be associated with a street named "Swami Vivekanand Road" and nodes 8, 9, 10 may be associated with "Mahatma Gandhi Road". The navigation platform 103 connects the nodes as follows. Let V_xy = { N_l, N_l, .., N_n} denote a set of nodes that belong to street X and city Y. Let V = {V_xy, V_zy, .., V_ky} denote a set of all the nodes that belong to different streets in city Y.

The navigation platform 103 considers set V_xy without loss of generality. For each node N_i, in V_xy, the navigation platform 103 considered all other nodes and pick a node (N_j) that is closet to node N_i (i.e. distance between N_i and N_j is minimum as compared to the distance between N_i and rest of the nodes in set V_xy). If an edge (e_ij or eji) already exists between node N_i and N_j then the navigation platform 103 ignores node N_j and picks the second closest node N_k. The navigation platform repeats this until it finds a node N_p that is closer to node N_i and no edge exists between them. The navigation platform 103 then connects these two nodes with and an undirected edge e_ip. Note that edge e_ip is undirected so e_ip and e_pi would refer to the same edge. The navigation platform 103 then adds edge e_ip to set E_xy. A weight of this edge e_ip is equal to the distance between node N_i and N_p. After the end of this step, a set of undirected, weighted edges E_xy is produced that represents the edges for street X and city Y. This step ensures that all the nodes belonging to street X are connected with each other (i.e. there exists a path between any two nodes in set V_xy} . The navigation platform 103 repeats this same procedure for other streets and gets a set E = {E_xy, E_zy, ... , E_ky} .

Accordingly, for example, nodes 1 and 2 are connected via edge e_12. These nodes are close to each other and belong to the same street. Other nodes are connected in a similar fashion. By connecting the nodes belonging to the same street, the navigation platform 103 can start mapping the street. The navigation platform 103 can also obtain the following information about each street:

• Start and End points of the street: For all the nodes belonging to set V_xy, the navigation platform 103 determines a shortest path between any two nodes N_i and N_j in V_xy. The navigation platform 103 temporarily sets all the edge weights to 1 and finds the shorted path based on the length of the path. Standard all pair shortest path algorithms such as Floyd- Warshall algorithm can be deployed here. For example, based on the example node set 1, 2, 3, 4, 5, 6, 7, discussed above, the path length between node 1 and node 7 is 6 and path length between node 2 and 4 is 2. Out of all the paths, the navigation platform 103 picks a path that has the maximum length. The navigation platform 103 then assigns the start and end nodes of this path to be the start and end points of the street.

• Length of the street: Once the navigation platform 103 finds the start and end points of the street, the navigation platform 103 may run a standard shortest path algorithm such as Dijkstra's algorithm to get the length of this path. The navigation platform 103 may use the original edge weights, (which refer to the actual distance between any two given nodes). The length of the street obtained may be an approximate estimation, and the accuracy of the approximation can be improved if the POIs have a good coverage across a given street.

• Direction of the street: By observing the geo-coordinates of the start and end points of the street, the navigation platform 103 can determine if the street is North-South bound or East-West bound. Typically, the latitude and longitudes have direction incorporated in them. For example, latitudes increment as one goes from south to north and longitudes increment as one goes from east to west. Further, the navigation platform 103 may consider that negative latitude indicates south and negative longitude indicates west.

Now that the street information has been determined, the navigation platform 103 determines intersection points between cross streets. Recall that set V = {V_xy, V_zy, .., Vky} denotes the set of nodes for all the streets in a city Y. For any two given streets, street X and street Z, the navigation platform 103 considers nodes from set V_xy and V_zy. For each node in set V_xy, the navigation platform 103 determines if there are any nodes in set V_zy that are close to each other, i.e. are at a distance of L from each other, where L is a system parameter. If any such nodes are within a distance L, this indicates that there is a strong probability that the two streets intersect with each other. Assuming that the distance between parallel streets is more than for intersecting streets, by carefully choosing L, the navigation platform 103 weeds out the possibility of connecting parallel streets.

The navigation platform 103 then associates an edge between the two nodes. Considering the example discussed above and illustrated in Fig. 5, nodes 6 and 8 and nodes 7 and 8 are considered close to each other. Therefore the navigation platform 103 adds edges e_68 and e_78, respectively. These edges are then added to the edge set E. These edges connect the two cross streets and a path is created from one street to another. Even if a street name changes from street A to Street A', this approach captures the point where the street name has changed and connects the two streets and provides a contiguous path. The navigation platform 103 has now produced a graph G=(V,E) that captures the street information and connects two streets if they intersect. This graph therefore represents the approximate road network. Since this graph has POI information embedded in it, it may be used for performing landmark-based navigation.

It should be noted that the accuracy of the street information contained in this graph G depends on the density, distribution, quality and quantity of POI data. Good quality POI data is heavily distributed across the given city can yield more accurate road network by using our approach. Although the road network constructed by our method may not be extremely accurate, this level of approximation may be adequate for providing landmark-based navigation. As discussed above, a node may be determined to be associated with each cluster. Each node belongs to a certain street may be compared with every other node belonging to the same street. From this comparison, distances may be computed. The complexity of this step can be reduced by using efficient queries to a spatial database such as POI database 1 1 1. After processing the POFs to determine nodes, the navigation platform may store any processed data in the POI database 11 1 for recall such as a query such as "Find Nodes with street name = X within a distance of D and no previous edge exist, order by distance." If no nodes are found within a distance of D, then the distance can be increased. This implementation therefore minimizes some computational complexity. A similar query can be used to find nodes that lie along a cross-street junction. The final graph can be efficiently stored in a spatial database and/or the POI database 1 11 , and spatial indexes can be used for optimizing query performance.

According to various embodiments, the clustering and graph construction processes discussed above may be implemented run over the POI database as a backend process. That is, as a preprocessing step to various location based services. Once the graph is constructed, the navigation platform 103 may be set up to run various location based services such as landmark based navigation.

According to various embodiments, the system 100 may be used for landmark-based navigation as follows. Once the graph is determined that represents the road network, the navigation platform 103 runs a shortest path algorithm such as Dijkstra's on it to determine a path between a source and destination. Consider a scenario in which user enters a start and destination address. The navigation platform can use any address geocoding technique to determine the geo- coordinates associated with that address. The navigation platform 103 may query the POI database 11 1 to find out which POIs are close to the source and destination. For example, if these POI's are denoted as p_s and p_d respectively, the navigation platform 103 then determines any clusters and nodes to which these POIs belong. In this example, let these nodes be denoted as N_s and N_d. These nodes become the source and destination nodes for the shortest path algorithm on Graph G = (V,E).

Considering the example discussed above for nodes 1 , 2, 3, 4, 5, 6, 7, 8, 9, and as illustrated in Fig. 5, a shortest path from node 2 to node 9 can be obtained as {2-3-4-5-6-8-9} . Since POIs are associated with each node along the path, references may be given to these POIs along with the route. For example, the navigation platform 103 may provide directions to a user of UE 101 by way of navigation API 1 13 such as "You are next to EFG shop (POI associated with node 2), head south on Swami Viviekanand road and keep going straight, after 5 KM you will see XYZ shop on your right (POI associated with node 3), continue for 4 KM, you will see PQR mall (POI associated with node 4), continue for 3 KM, you will see ABC school (POI associated with node 5), continue for 2 KM, you will see LM store (POI associated with node 6), continue 1 KM and make a left near DEF theatre store (POI associated with node 8) and get on to Mahatma Gandhi Road, continue 3 KM and your destination shall be next to HIJ store (POI associated with node 9)".

It should be noted that the distances suggested in the route are an approximate estimation. The accuracy can be improved if the POIs have a good coverage across a given street. The main advantage of this form of navigation is that a user can be given references to multiple POIs. So even if he is not able to find a particular POI, or a POI name changes or is relocated, there are other POIs to still guide the user seeking navigation information by way of UE 101. By way of example, the UE 101 , navigation platform 103, social networking service 107, navigation service 109 and POI database 1 11 communicate with each other and other components of the communication network 105 using well known, new or still developing protocols. In this context, a protocol includes a set of rules defining how the network nodes within the communication network 105 interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model.

By way of example, the communication network 105 of system 100 includes one or more networks such as a data network, a wireless network, a telephony network, or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short range wireless network, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiberoptic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN), Bluetooth®, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), and the like, or any combination thereof.

The UE 101 is any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the UE 101 can support any type of interface to the user (such as "wearable" circuitry, etc.).

Communications between the network nodes are typically effected by exchanging discrete packets of data. Each packet typically comprises (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol typically indicates a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, typically include a physical (layer 1) header, a data-link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application (layer 5, layer 6 and layer 7) headers as defined by the OSI Reference Model. FIG. 2 is a diagram of the components of navigation platform 103, according to one embodiment. By way of example, the navigation platform includes one or more components for providing generating map data based on point of interest location information. It is contemplated that the functions of these components may be combined in one or more components or performed by other components of equivalent functionality. In this embodiment, the navigation platform 103 includes a control logic 201 , a communication module 203, a POI data extraction module 205, a clustering module 207, a graphing/mapping module 209 and a display/navigation module 21 1.

According to various embodiments, the control logic 201 controls the processing of POI data and navigation requests that are received by way of the communication module 203. For example, the navigation platform 103 may receive a request from the UE 101 by way of the navigation API 1 13. The request may be to generate a map of an area and/or generate navigation instructions between at least two locations. Upon receipt of such a request, the control logic 201 instructs the POI data extraction module 205 to communicate with the POI database 1 11 to determine POI data points that may be near the at least two locations and anywhere in between. The POI data that is extracted base on a query of the POI database 1 11 is then clustered in the manner discussed above by the clustering module 207 and a graph is produced by the graphing/mapping module 209. From this graph, a map may be produced accordingly by the graphing/mapping module 209. The display/navigation module 21 1 uses the graph and mapping information to determine any navigation instructions and/or display a requested map to produce a presentation of an approximated map of a region. The map and/or navigation instructions are then delivered to the navigation API 1 13 by way of the communication module 203 for viewing on the UE 101. The navigation API 1 13 may display any map and/or navigation information by way of a user interface that is coordinated with the navigation platform 103 and/or navigation service 109 and/or social networking service 107. Post processing, the navigation platform may store any determined clustering, nodal and/or mapping information in the POI database 1 11 for future processing/updating. Any stored map data may be accessed by the UE 101 by way of the navigation API 1 13, the navigation service 109 and the social networking service 107 for viewing, rating, verification and/or updating of any determined POI data or map approximations. For example, users of the social network may verify the accuracy of an approximated map and update the map accordingly so that others, as well as themselves, may continue to develop the accuracy of the map data stored in the POI database 111.

FIG. 3 is a flowchart of a process for generating map data based on point of interest location information, according to one embodiment. In one embodiment, the navigation platform 103 performs the process 300 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 8. In step 301, the navigation platform 103 processes and/or facilitates a processing of metadata to determine one or more street names associated with one or more points of interest. The process continues to step 303 in which the navigation platform 103 processes and/or facilitates a processing of the metadata to determine density information for a distribution of the one or more points of interest. The metadata may include, for example, any of geolocation information, geocode information, one or more building names, proximity information to one or more other points-of-interest, etc., or a combination thereof. Then, in step 305, the navigation processing platform determines a shape, a size, or a combination thereof of one or more clusters based, at least in part, on the density information. Next, in step 307, the navigation platform 103 processes and/or facilitates a processing the metadata to determine one or more clusters of the one or more points-of-interest. It should be noted that the one or more clusters may be based, at least in part, on the one or more street names. The process continues to step 309 in which the navigation platform 103 processes and/or facilitates a processing of the metadata associated with one or more points of interest to cause, at least in part, a designation of the one or more points of interests as one or more location nodes. In designating the nodes, the navigation platform 103 may cause, at least in part, a designation of the one or more clusters as the one or more location nodes. Then, in step 31 1, the navigation platform 103 determines the one or more connections based, at least in part, on one or more respective centroids of the one or more clusters. Next, in step 313, the navigation platform 103 determines one or more connections based, at least in part, on a shortest distance between the one or more nodes. The process continues to step 315 in which the navigation platform 103 connects the nodes.

Then, in step 317, the navigation platform 103 causes, at least in part, a construction of a location graph based, at least in part, on the one or more connections among the one or more locations nodes. It should be noted that the one or more connections may be based, at least in part, on the one or more street names. Next, in step 319 in which the navigation platform 103 determines at least an approximation of one or more features based, at least in part, on the location graph. The one or more features, for example, may include, at least in part, one or more roadways. The process continues to step 321 in which the navigation platform 103 processes and/or facilitates a processing of the density information to determine one or more characteristics of the one or more features, the one or more clusters, the one or more points of interest, or a combination thereof. Such characteristic information may be, for example, a type of feature, type of POI, type of cluster, etc. In the case of a cluster, the navigation platform 103 may designate the characteristic to be a business district or a mall based on the types of POI's in the area, for example, or a religious region because of a number of churches in the area. In step 323, the navigation platform 103 processes and/or facilitates a processing of the location graph, the one or more connections, the metadata, or a combination thereof to determine one or more intersections of the one or more features.

Then, in step 325, the navigation platform 103 determines one or more types of the one or more roadways based, at least in part, on the location graph, the metadata, user feedback information, or a combination thereof. For example, a roadway may be a single-lane road or a four-lane highway. Such a determination may be helpful in developing navigation instructions and/or when rendering any determined features. Next, in step 327, the navigation platform 103 causes, at least in part, a rendering of a user interface for presenting the one or more clusters, the one or more points of interest within the one or more clusters, or a combination thereof. The rendering may be, for example, a user interface that allows for an interactive map illustrated by way of the navigation API 1 13, or any other rendering means for viewing on the UE 101, or from any other terminal associated with the social networking service 107 and/or the navigation service 109.

The process continues to step 329 in which the navigation platform 103 determines to provide at least one user interface element in the user interface for controlling, at least in part, a zoom level of the one or more clusters, a number of the points of interest to present, or a combination thereof. Such an element may be helpful in customizing a display of the rendered features and/or POI's and their respective clusters. The navigation platform 103, in conjunction with the navigation API 1 13 may provide for other user interface elements such as a means for selecting a point of interest to get more details about that POI or other POI's around it such as address information, organizational information, menu information in the case of a restaurant, etc. User interface elements may also enable a user to move the rendering from one view to another so as to view other areas without having to conduct an additional search for map data for rendering on the UI.

Then, in step 331 , the navigation platform 103 determines mapping information, navigation information, or a combination thereof based, at least in part, on the one or more features, the one or more points of interest, the location graph, or a combination thereof. Such mapping information may be, for example, an interactive map rendering of any determined roadways, features, having the points of interest, etc. Navigation information may be, for example, a set of directions between at least two locations based, at least in part, on the determined POI's, roadways, etc. In other words, the mapping information, the navigation information, or a combination thereof may be landmark based. The Navigation information may be presented by way of text and/or illustration on the interactive map. So, in step 333, the navigation platform 103 causes, at least in part, a rendering of a user interface for presenting the one or more features, the mapping information, the navigation information, or a combination thereof.

The process continues to step 335 in which the navigation platform 103 determines accuracy information of the one or more features, the location graph, the one or more connections, or a combination thereof based, at least in part, on user feedback information, previously collected mapping information, or a combination thereof. Then, in step 337, the navigation platform 103 causes, at least in part, an update of the location graph, the one or more features, or a combination thereof based, at least in part, on the accuracy information. Upon updating the accuracy of the location graph and/or the features, the navigation platform 103 may repeat for example steps 333-337 to re-render the UI of features, mapping and/or navigation information until there are no longer any accuracy updates determined.

Fig. 4 is an illustration of a distribution of POIs in a mapped region 401. POI's 403, 405, 407, 409, 411 , 413 and 421 represent POI's along "Swami Vivekanand Road", and POI's 415, 417 and 419 represent POI's along "Mahatma Gandhi Road." The POI's 403-421 may be used by the navigation platform 103 to determine the layout of "Swami Vivekanand Road" and "Mahatma Gandhi Road," for example. Other POI's that are not illustrated may be used to generate the other roadways on the map. The POI's and user feedback information may be used to enhance already created maps in conjunction with conventional mapping techniques to enhance their accuracy. The POI's in this illustration are not yet clustered or associated with a node.

Fig. 5 is an illustration of the distribution of POI's illustrated in FIG. 4 after they have been clustered by the navigation platform 103. The clusters of POI's are based on their proximity to one another. The navigation platform 103 associates a node with each cluster such that the nodes belonging to the same street may be connected. The nodal location information is available based on available metadata that is stored in the POI database 1 11. The Connect nodes present near the intersection point of two streets. The clusters are illustrated was being circular or oval, but could be of any shape. For example, based on the density information, the clusters could be shaped like any polygon or other curved shape that better suits the distribution of POI's. Based on the density information and the overall distribution of POI's that are within a particular threshold, a centroid of the cluster may be determined. In one or more embodiments, the centroids of neighboring nodes may be connected to approximate terrain features and/or roadways. Alternatively, the bounds of the determined clusters may be connected based on a shortest distance between the bounds of the cluster to approximate the terrain features and/or roadways.

For example, according to one embodiment, when determining features based on connecting various nodes determined based on the designation of clusters, consider the discussion above with respect to nodes 1-10. In this illustration, nodes 1 ,2,3,4,5,6,7 may be associated with a street named "Swami Vivekanand Road" and nodes 8, 9, 10 may be associated with "Mahatma Gandhi Road". The navigation platform 103 connects the nodes as discussed above. For example, let V_xy = {N_l , N_l, .., N_n} denote a set of nodes that belong to street X and city Y. Let V = {V_xy, V_zy, .., V_ky} denote a set of all the nodes that belong to different streets in city Y.

The navigation platform 103 considers set V_xy without loss of generality. For each node N_i, in V_xy, the navigation platform 103 considered all other nodes and pick a node (N_j) that is closet to node N_i (i.e. distance between N_i and N_j is minimum as compared to the distance between N_i and rest of the nodes in set V_xy). If an edge (e_ij or e_ji) already exists between node N_i and N_j then the navigation platform 103 ignores node N_j and picks the second closest node N_k. The navigation platform repeats this until it finds a node N_p that is closer to node N_i and no edge exists between them. The navigation platform 103 then connects these two nodes with and an undirected edge e_ip. Note that edge e_ip is undirected so e_ip and e_pi would refer to the same edge. The navigation platform 103 then adds edge e_ip to set E_xy. A weight of this edge e_ip is equal to the distance between node N_i and N_p. After the end of this step, a set of undirected, weighted edges E_xy is produced that represents the edges for street X and city Y. This step ensures that all the nodes belonging to street X are connected with each other (i.e. there exists a path between any two nodes in set V_xy} . The navigation platform 103 repeats this same procedure for other streets and gets a set E = {E_xy, E_zy, ... , E_ky} .

Accordingly, for example, nodes 1 and 2 are connected via edge e_12. These nodes are close to each other and belong to the same street. Other nodes are connected in a similar fashion. By connecting the nodes belonging to the same street, the navigation platform 103 can start mapping the street. The navigation platform 103 can also obtain the following information about each street:

• Start and End points of the street: For all the nodes belonging to set V_xy, the navigation platform 103 determines a shortest path between any two nodes N_i and N_j in V_xy. The navigation platform 103 temporarily sets all the edge weights to 1 and finds the shorted path based on the length of the path. Standard all pair shortest path algorithms such as Floyd- Warshall algorithm can be deployed here. For example, based on the example node set 1 , 2, 3, 4, 5, 6, 7, discussed above, the path length between node 1 and node 7 is 6 and path length between node 2 and 4 is 2. Out of all the paths, the navigation platform 103 picks a path that has the maximum length. The navigation platform 103 then assigns the start and end nodes of this path to be the start and end points of the street.

• Length of the street: Once the navigation platform 103 finds the start and end points of the street, the navigation platform 103 may run a standard shortest path algorithm such as Dijkstra's algorithm to get the length of this path. The navigation platform 103 may use the original edge weights, (which refer to the actual distance between any two given nodes). The length of the street obtained may be an approximate estimation, and the accuracy of the approximation can be improved if the POIs have a good coverage across a given street.

• Direction of the street: By observing the geo-coordinates of the start and end points of the street, the navigation platform 103 can determine if the street is North-South bound or East-West bound. Typically, the latitude and longitudes have direction incorporated in them. For example, latitudes increment as one goes from south to north and longitudes increment as one goes from east to west. Further, the navigation platform 103 may consider that negative latitude indicates south and negative longitude indicates west.

Now that the street information has been determined, the navigation platform 103 determines intersection points between cross streets. Recall that set V = {V_xy, V_zy, .., Vky} denotes the set of nodes for all the streets in a city Y. For any two given streets, street X and street Z, the navigation platform 103 considers nodes from set V_xy and V_zy. For each node in set V_xy, the navigation platform 103 determines if there are any nodes in set V_zy that are close to each other, i.e. are at a distance of L from each other, where L is a system parameter. If any such nodes are within a distance L, this indicates that there is a strong probability that the two streets intersect with each other. Assuming that the distance between parallel streets is more than for intersecting streets, by carefully choosing L, the navigation platform 103 weeds out the possibility of connecting parallel streets.

The navigation platform 103 then associates an edge between the two nodes. Considering the example discussed above and illustrated in Fig. 5, nodes 6 and 8 and nodes 7 and 8 are considered close to each other. Therefore the navigation platform 103 adds edges e_68 and e_78, respectively. These edges are then added to the edge set E. These edges connect the two cross streets and a path is created from one street to another. Even if a street name changes from street A to Street A', this approach captures the point where the street name has changed and connects the two streets and provides a contiguous path. The navigation platform 103 has now produced a graph G=(V,E) that captures the street information and connects two streets if they intersect. This graph therefore represents the approximate road network. Since this graph has POI information embedded in it, it may be used for performing landmark-based navigation.

It should be noted that the accuracy of the street information contained in this graph G depends on the density, distribution, quality and quantity of POI data. Good quality POI data is heavily distributed across the given city can yield more accurate road network by using our approach. Although the road network constructed by our method may not be extremely accurate, this level of approximation may be adequate for providing landmark-based navigation. As discussed above, a node may be determined to be associated with each cluster. Each node belongs to a certain street may be compared with every other node belonging to the same street. From this comparison, distances may be computed. The complexity of this step can be reduced by using efficient queries to a spatial database such as POI database 1 1 1. After processing the POFs to determine nodes, the navigation platform may store any processed data in the POI database 11 1 for recall such as a query such as "Find Nodes with street name = X within a distance of D and no previous edge exist, order by distance." If no nodes are found within a distance of D, then the distance can be increased. This implementation therefore minimizes some computational complexity. A similar query can be used to find nodes that lie along a cross-street junction. The final graph can be efficiently stored in a spatial database and/or the POI database 11 1, and spatial indexes can be used for optimizing query performance.

According to various embodiments, the clustering and graph construction processes discussed above may be implemented run over the POI database as a backend process. That is, as a pre- processing step to various location based services. Once the graph is constructed, the navigation platform 103 may be set up to run various location based services such as landmark based navigation.

According to various embodiments, the system 100 may be used for landmark-based navigation as follows. Once the graph is determined that represents the road network, the navigation platform 103 runs a shortest path algorithm such as Dijkstra's on it to determine a path between a source and destination. Consider a scenario in which user enters a start and destination address. The navigation platform can use any address geocoding technique to determine the geo- coordinates associated with that address. The navigation platform 103 may query the POI database 11 1 to find out which POIs are close to the source and destination. For example, if these POI's are denoted as p_s and p_d respectively, the navigation platform 103 then determines any clusters and nodes to which these POIs belong. In this example, let these nodes be denoted as N_s and N_d. These nodes become the source and destination nodes for the shortest path algorithm on Graph G = (V,E).

Considering the example discussed above for nodes 1 , 2, 3, 4, 5, 6, 7, 8, 9, and as illustrated in Fig. 5, a shortest path from node 2 to node 9 can be obtained as {2-3-4-5-6-8-9} . Since POIs are associated with each node along the path, references may be given to these POIs along with the route. For example, the navigation platform 103 may provide directions to a user of UE 101 by way of navigation API 1 13 such as "You are next to EFG shop (POI associated with node 2), head south on Swami Viviekanand road and keep going straight, after 5 KM you will see XYZ shop on your right (POI associated with node 3), continue for 4 KM, you will see PQR mall (POI associated with node 4), continue for 3 KM, you will see ABC school (POI associated with node 5), continue for 2 KM, you will see LMN store (POI associated with node 6), continue 1 KM and make a left near DEF theatre store (POI associated with node 8) and get on to Mahatma Gandhi Road, continue 3 KM and your destination shall be next to HIJ store (POI associated with node 9)".

FIG. 6 is a diagrams of a user interface 600 utilized in the processes of FIG. 3, according to various embodiments. In this example, a user of the UE 101 and the navigation API 1 13 by way of the user interface 600 begins navigation from a starting location 601. The navigation platform 103 determines any terrain information and/or roadway information based on the POFs discussed above and illustrated in FIG. 6 generically as 603. The mapping of the various roadways illustrated in the UI 600 may be based solely on POI location information or in combination with conventionally mapped data. The navigated path may be illustrated on the user interface 600 by way of a line 605, for example. The position of the UE 101 may also be tracked on the user interface in addition to or in lieu of the plotted route to track the progress of a traveler as he progresses from the start location 601 to an end location 607. To enable the traveler to progress from the start location 601 to the end location 607, the user may scroll through navigation directions 609 provided by way of the user interface 600. The directions may also be provided in an audio format that may be selected in addition to, or as alternative to the direction field 609. For example, if the user chooses to use a solely audio format for delivering the directions, a larger rendering of the map (or a larger area of the map) may be presented because more display space would be available.

According to this example, direction may be provided to a user of the UE 101 as follows: "You are next to EFG shop (POI associated with node 1), head south on Swami Viviekanand road and keep going straight, after 5 KM you will see XYZ shop on your right (POI associated with node 3), continue for 4 KM, you will see PQR mall (POI associated with node 4), continue for 3 KM, you will see ABC school (POI associated with node 5), continue for 2 KM, you will see LM store (POI associated with node 6), continue 1 KM and make a left near DEF theatre store (POI associated with node 8) and get on to Mahatma Gandhi Road, continue 3 KM and your destination shall be next to HIJ store (POI associated with node 10)." Upon reaching the end location, or if the end location 607 is merely a via point to go to another destination, the user interface 600 may indicate that the traveler has reached the end point 607 or destination. The user interface 600 may also zoom in as a traveler nears the end location, or a POI to provide more detail to aid the traveler in reaching the end location 607. For example, as a traveler reaches a turn or series of turns that, based on user feedback, is a confusing area, the user interface may provide a more detailed view of that area to help the traveler get through the confusing region without any problems. The user interface 600 may zoom in, additional POFs may be illustrated, more detailed descriptions of the PO s in the area may be presented, an alternative view may be provides such as a heads up display or integration with an augmented reality that directs a traveler through the region based on what the traveler might see from his vantage point, etc. The processes described herein for generating map data based on point of interest location information may be advantageously implemented via software, hardware, firmware or a combination of software and/or firmware and/or hardware. For example, the processes described herein, may be advantageously implemented via processor(s), Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc. Such exemplary hardware for performing the described functions is detailed below. FIG. 7 illustrates a computer system 700 upon which an embodiment of the invention may be implemented. Although computer system 700 is depicted with respect to a particular device or equipment, it is contemplated that other devices or equipment (e.g., network elements, servers, etc.) within FIG. 7 can deploy the illustrated hardware and components of system 700. Computer system 700 is programmed (e.g., via computer program code or instructions) to generate map data based on point of interest location information as described herein and includes a communication mechanism such as a bus 710 for passing information between other internal and external components of the computer system 700. Information (also called data) is represented as a physical expression of a measurable phenomenon, typically electric voltages, but including, in other embodiments, such phenomena as magnetic, electromagnetic, pressure, chemical, biological, molecular, atomic, sub-atomic and quantum interactions. For example, north and south magnetic fields, or a zero and non-zero electric voltage, represent two states (0, 1) of a binary digit (bit). Other phenomena can represent digits of a higher base. A superposition of multiple simultaneous quantum states before measurement represents a quantum bit (qubit). A sequence of one or more digits constitutes digital data that is used to represent a number or code for a character. In some embodiments, information called analog data is represented by a near continuum of measurable values within a particular range. Computer system 700, or a portion thereof, constitutes a means for performing one or more steps of generating map data based on point of interest location information. A bus 710 includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus 710. One or more processors 702 for processing information are coupled with the bus 710.

A processor (or multiple processors) 702 performs a set of operations on information as specified by computer program code related to generate map data based on point of interest location information. The computer program code is a set of instructions or statements providing instructions for the operation of the processor and/or the computer system to perform specified functions. The code, for example, may be written in a computer programming language that is compiled into a native instruction set of the processor. The code may also be written directly using the native instruction set (e.g., machine language). The set of operations include bringing information in from the bus 710 and placing information on the bus 710. The set of operations also typically include comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor 702, such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination.

Computer system 700 also includes a memory 704 coupled to bus 710. The memory 704, such as a random access memory (RAM) or any other dynamic storage device, stores information including processor instructions for generating map data based on point of interest location information. Dynamic memory allows information stored therein to be changed by the computer system 700. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory 704 is also used by the processor 702 to store temporary values during execution of processor instructions. The computer system 700 also includes a read only memory (ROM) 706 or any other static storage device coupled to the bus 710 for storing static information, including instructions, that is not changed by the computer system 700. Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus 710 is a non-volatile (persistent) storage device 708, such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system 700 is turned off or otherwise loses power.

Information, including instructions for generating map data based on point of interest location information, is provided to the bus 710 for use by the processor from an external input device 712, such as a keyboard containing alphanumeric keys operated by a human user, a microphone, an Infrared (IR) remote control, a joystick, a game pad, a stylus pen, a touch screen, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system 700. Other external devices coupled to bus 710, used primarily for interacting with humans, include a display device 714, such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a plasma screen, or a printer for presenting text or images, and a pointing device 716, such as a mouse, a trackball, cursor direction keys, or a motion sensor, for controlling a position of a small cursor image presented on the display 714 and issuing commands associated with graphical elements presented on the display 714. In some embodiments, for example, in embodiments in which the computer system 700 performs all functions automatically without human input, one or more of external input device 712, display device 714 and pointing device 716 is omitted.

In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC) 720, is coupled to bus 710. The special purpose hardware is configured to perform operations not performed by processor 702 quickly enough for special purposes. Examples of ASICs include graphics accelerator cards for generating images for display 714, cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware.

Computer system 700 also includes one or more instances of a communications interface 770 coupled to bus 710. Communication interface 770 provides a one-way or two-way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link 778 that is connected to a local network 780 to which a variety of external devices with their own processors are connected. For example, communication interface 770 may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface 770 is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface 770 is a cable modem that converts signals on bus 710 into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface 770 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface 770 sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface 770 includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface 770 enables connection to the communication network 105 for generating map data based on point of interest location information to the UE 101.

The term "computer-readable medium" as used herein refers to any medium that participates in providing information to processor 702, including instructions for execution. Such a medium may take many forms, including, but not limited to computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Non-transitory media, such as non- volatile media, include, for example, optical or magnetic disks, such as storage device 708. Volatile media include, for example, dynamic memory 704. Transmission media include, for example, twisted pair cables, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. The term computer-readable storage medium is used herein to refer to any computer-readable medium except transmission media. Logic encoded in one or more tangible media includes one or both of processor instructions on a computer-readable storage media and special purpose hardware, such as ASIC 720.

Network link 778 typically provides information communication using transmission media through one or more networks to other devices that use or process the information. For example, network link 778 may provide a connection through local network 780 to a host computer 782 or to equipment 784 operated by an Internet Service Provider (ISP). ISP equipment 784 in turn provides data communication services through the public, world-wide packet-switching communication network of networks now commonly referred to as the Internet 790. A computer called a server host 792 connected to the Internet hosts a process that provides a service in response to information received over the Internet. For example, server host 792 hosts a process that provides information representing video data for presentation at display 714. It is contemplated that the components of system 700 can be deployed in various configurations within other computer systems, e.g., host 782 and server 792.

At least some embodiments of the invention are related to the use of computer system 700 for implementing some or all of the techniques described herein. According to one embodiment of the invention, those techniques are performed by computer system 700 in response to processor 702 executing one or more sequences of one or more processor instructions contained in memory 704. Such instructions, also called computer instructions, software and program code, may be read into memory 704 from another computer-readable medium such as storage device 708 or network link 778. Execution of the sequences of instructions contained in memory 704 causes processor 702 to perform one or more of the method steps described herein. In alternative embodiments, hardware, such as ASIC 720, may be used in place of or in combination with software to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware and software, unless otherwise explicitly stated herein.

The signals transmitted over network link 778 and other networks through communications interface 770, carry information to and from computer system 700. Computer system 700 can send and receive information, including program code, through the networks 780, 790 among others, through network link 778 and communications interface 770. In an example using the Internet 790, a server host 792 transmits program code for a particular application, requested by a message sent from computer 700, through Internet 790, ISP equipment 784, local network 780 and communications interface 770. The received code may be executed by processor 702 as it is received, or may be stored in memory 704 or in storage device 708 or any other non-volatile storage for later execution, or both. In this manner, computer system 700 may obtain application program code in the form of signals on a carrier wave. Various forms of computer readable media may be involved in carrying one or more sequence of instructions or data or both to processor 702 for execution. For example, instructions and data may initially be carried on a magnetic disk of a remote computer such as host 782. The remote computer loads the instructions and data into its dynamic memory and sends the instructions and data over a telephone line using a modem. A modem local to the computer system 700 receives the instructions and data on a telephone line and uses an infra-red transmitter to convert the instructions and data to a signal on an infra-red carrier wave serving as the network link 778. An infrared detector serving as communications interface 770 receives the instructions and data carried in the infrared signal and places information representing the instructions and data onto bus 710. Bus 710 carries the information to memory 704 from which processor 702 retrieves and executes the instructions using some of the data sent with the instructions. The instructions and data received in memory 704 may optionally be stored on storage device 708, either before or after execution by the processor 702.

FIG. 8 illustrates a chip set or chip 800 upon which an embodiment of the invention may be implemented. Chip set 800 is programmed to generate map data based on point of interest location information as described herein and includes, for instance, the processor and memory components described with respect to FIG. 7 incorporated in one or more physical packages (e.g., chips). By way of example, a physical package includes an arrangement of one or more materials, components, and/or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and/or limitation of electrical interaction. It is contemplated that in certain embodiments the chip set 800 can be implemented in a single chip. It is further contemplated that in certain embodiments the chip set or chip 800 can be implemented as a single "system on a chip." It is further contemplated that in certain embodiments a separate ASIC would not be used, for example, and that all relevant functions as disclosed herein would be performed by a processor or processors. Chip set or chip 800, or a portion thereof, constitutes a means for performing one or more steps of providing user interface navigation information associated with the availability of functions. Chip set or chip 800, or a portion thereof, constitutes a means for performing one or more steps of generating map data based on point of interest location information.

In one embodiment, the chip set or chip 800 includes a communication mechanism such as a bus 801 for passing information among the components of the chip set 800. A processor 803 has connectivity to the bus 801 to execute instructions and process information stored in, for example, a memory 805. The processor 803 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively or in addition, the processor 803 may include one or more microprocessors configured in tandem via the bus 801 to enable independent execution of instructions, pipelining, and multithreading. The processor 803 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP) 807, or one or more application- specific integrated circuits (ASIC) 809. A DSP 807 typically is configured to process real-world signals (e.g., sound) in real time independently of the processor 803. Similarly, an ASIC 809 can be configured to performed specialized functions not easily performed by a more general purpose processor. Other specialized components to aid in performing the inventive functions described herein may include one or more field programmable gate arrays (FPGA), one or more controllers, or one or more other special-purpose computer chips.

In one embodiment, the chip set or chip 800 includes merely one or more processors and some software and/or firmware supporting and/or relating to and/or for the one or more processors.

The processor 803 and accompanying components have connectivity to the memory 805 via the bus 801. The memory 805 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to generate map data based on point of interest location information. The memory 805 also stores the data associated with or generated by the execution of the inventive steps.

FIG. 9 is a diagram of exemplary components of a mobile terminal (e.g., handset) for communications, which is capable of operating in the system of FIG. 1 , according to one embodiment. In some embodiments, mobile terminal 901, or a portion thereof, constitutes a means for performing one or more steps of generating map data based on point of interest location information. Generally, a radio receiver is often defined in terms of front-end and back- end characteristics. The front-end of the receiver encompasses all of the Radio Frequency (RF) circuitry whereas the back-end encompasses all of the base-band processing circuitry. As used in this application, the term "circuitry" refers to both: (1) hardware-only implementations (such as implementations in only analog and/or digital circuitry), and (2) to combinations of circuitry and software (and/or firmware) (such as, if applicable to the particular context, to a combination of processor(s), including digital signal processor(s), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions). This definition of "circuitry" applies to all uses of this term in this application, including in any claims. As a further example, as used in this application and if applicable to the particular context, the term "circuitry" would also cover an implementation of merely a processor (or multiple processors) and its (or their) accompanying software/or firmware. The term "circuitry" would also cover if applicable to the particular context, for example, a baseband integrated circuit or applications processor integrated circuit in a mobile phone or a similar integrated circuit in a cellular network device or other network devices.

Pertinent internal components of the telephone include a Main Control Unit (MCU) 903, a Digital Signal Processor (DSP) 905, and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit 907 provides a display to the user in support of various applications and mobile terminal functions that perform or support the steps of generating map data based on point of interest location information. The display 907 includes display circuitry configured to display at least a portion of a user interface of the mobile terminal (e.g., mobile telephone). Additionally, the display 907 and display circuitry are configured to facilitate user control of at least some functions of the mobile terminal. An audio function circuitry 909 includes a microphone 91 1 and microphone amplifier that amplifies the speech signal output from the microphone 91 1. The amplified speech signal output from the microphone 911 is fed to a coder/decoder (CODEC) 913.

A radio section 915 amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna 917. The power amplifier (PA) 919 and the transmitter/modulation circuitry are operationally responsive to the MCU 903, with an output from the PA 919 coupled to the duplexer 921 or circulator or antenna switch, as known in the art. The PA 919 also couples to a battery interface and power control unit 920.

In use, a user of mobile terminal 901 speaks into the microphone 91 1 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC) 923. The control unit 903 routes the digital signal into the DSP 905 for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), satellite, and the like, or any combination thereof.

The encoded signals are then routed to an equalizer 925 for compensation of any frequency- dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator 927 combines the signal with a RF signal generated in the RF interface 929. The modulator 927 generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up- converter 931 combines the sine wave output from the modulator 927 with another sine wave generated by a synthesizer 933 to achieve the desired frequency of transmission. The signal is then sent through a PA 919 to increase the signal to an appropriate power level. In practical systems, the PA 919 acts as a variable gain amplifier whose gain is controlled by the DSP 905 from information received from a network base station. The signal is then filtered within the duplexer 921 and optionally sent to an antenna coupler 935 to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna 917 to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, any other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks.

Voice signals transmitted to the mobile terminal 901 are received via antenna 917 and immediately amplified by a low noise amplifier (LNA) 937. A down-converter 939 lowers the carrier frequency while the demodulator 941 strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer 925 and is processed by the DSP 905. A Digital to Analog Converter (DAC) 943 converts the signal and the resulting output is transmitted to the user through the speaker 945, all under control of a Main Control Unit (MCU) 903 which can be implemented as a Central Processing Unit (CPU).

The MCU 903 receives various signals including input signals from the keyboard 947. The keyboard 947 and/or the MCU 903 in combination with other user input components (e.g., the microphone 91 1) comprise a user interface circuitry for managing user input. The MCU 903 runs a user interface software to facilitate user control of at least some functions of the mobile terminal 901 to generate map data based on point of interest location information. The MCU 903 also delivers a display command and a switch command to the display 907 and to the speech output switching controller, respectively. Further, the MCU 903 exchanges information with the DSP 905 and can access an optionally incorporated SIM card 949 and a memory 951. In addition, the MCU 903 executes various control functions required of the terminal. The DSP 905 may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP 905 determines the background noise level of the local environment from the signals detected by microphone 91 1 and sets the gain of microphone 91 1 to a level selected to compensate for the natural tendency of the user of the mobile terminal 901.

The CODEC 913 includes the ADC 923 and DAC 943. The memory 951 stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device 951 may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, magnetic disk storage, flash memory storage, or any other non-volatile storage medium capable of storing digital data.

An optionally incorporated SIM card 949 carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card 949 serves primarily to identify the mobile terminal 901 on a radio network. The card 949 also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile terminal settings. While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.