Title:
SYSTEMS AND METHODS TO SEARCH FOR DIGITAL TWINS
Document Type and Number:
WIPO Patent Application WO/2023/102831
Kind Code:
A1
Abstract:
To search for digital twins (avatars) on a computerized platform, a semantic embedding is made of the search query and this is compared with respective semantic embeddings generated for digital twins on the computerized platform, to determine a first set digital twins whose semantic embeddings are similar to that of the search query. A trained graph neural network generates respective graph embeddings of feature data of the first set of digital twins, and these graph embeddings are compared with graph embeddings that the trained graph neural network generates for other digital twins on the platform, to determine a second set of digital twins whose graph embeddings are similar to graph embeddings of the first set of digital twins. The search results returned in response to the search query may include at least one digital twin in the second set of digital twins.
Inventors:
WU SI (CN)
WANG XI (CN)
YIN CHUANTAO (CN)
WANG XI (CN)
YIN CHUANTAO (CN)
Application Number:
PCT/CN2021/136819
Publication Date:
June 15, 2023
Filing Date:
December 09, 2021
Export Citation:
Assignee:
ORANGE (FR)
WU SI (CN)
WANG XI (CN)
YIN CHUANTAO (CN)
WU SI (CN)
WANG XI (CN)
YIN CHUANTAO (CN)
International Classes:
G06N3/04; G06F16/33; G06F40/30; G06N3/08
Foreign References:
| US20210271707A1 | 2021-09-02 | |||
| US9037464B1 | 2015-05-19 |
Other References:
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WILLIAM L HAMILTON ET AL: "Inductive Representation Learning on Large Graphs", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 7 June 2017 (2017-06-07), XP081281604
NILS REIMERS ET AL: "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 27 August 2019 (2019-08-27), XP081470451
KIROS ET AL.: "Advances in Neural Information Processing Systems", vol. 28, 2015, INFERSENT, article "Skip-Thought Vectors", pages: 3294 - 3302
CONNEAU ET AL.: "Supervised Learning of Universal Sentence Representations from Natural Language Inference Data", PROCEEDINGS OF THE 2017 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, 2017, pages 670 - 680, XP055483765, DOI: 10.18653/v1/D17-1070
CER ET AL.: "Universal Sentence Encoder", ARXIV, vol. 1803, pages 11175
JACOB DEVLIN ET AL.: "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", ARXIV PREPRINT ARXIV, vol. 1810, pages 04805
WL HAMILTON: "Inductive representation learning on large graphs", PROCEEDINGS OF THE 31ST INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING SYSTEMS, 2017, pages 1025 - 1035
DERRIEN SYLVIE ET AL: "Thing in, a research platform for the Web of Things", 2019 IEEE 27TH INTERNATIONAL SYMPOSIUM ON MODELING, ANALYSIS, AND SIMULATION OF COMPUTER AND TELECOMMUNICATION SYSTEMS (MASCOTS), IEEE, 21 October 2019 (2019-10-21), pages 431 - 432, XP033785558, ISSN: 2375-0227, ISBN: 978-1-7281-4950-9, [retrieved on 20200623], DOI: 10.1109/MASCOTS.2019.00056
WILLIAM L HAMILTON ET AL: "Inductive Representation Learning on Large Graphs", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 7 June 2017 (2017-06-07), XP081281604
NILS REIMERS ET AL: "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 27 August 2019 (2019-08-27), XP081470451
KIROS ET AL.: "Advances in Neural Information Processing Systems", vol. 28, 2015, INFERSENT, article "Skip-Thought Vectors", pages: 3294 - 3302
CONNEAU ET AL.: "Supervised Learning of Universal Sentence Representations from Natural Language Inference Data", PROCEEDINGS OF THE 2017 CONFERENCE ON EMPIRICAL METHODS IN NATURAL LANGUAGE PROCESSING, 2017, pages 670 - 680, XP055483765, DOI: 10.18653/v1/D17-1070
CER ET AL.: "Universal Sentence Encoder", ARXIV, vol. 1803, pages 11175
JACOB DEVLIN ET AL.: "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", ARXIV PREPRINT ARXIV, vol. 1810, pages 04805
WL HAMILTON: "Inductive representation learning on large graphs", PROCEEDINGS OF THE 31ST INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING SYSTEMS, 2017, pages 1025 - 1035
Attorney, Agent or Firm:
LIU, SHEN & ASSOCIATES (CN)
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