Title:
READING COMPREHENSION ASSISTANCE SYSTEM AND READING COMPREHENSION ASSISTANCE METHOD
Document Type and Number:
WIPO Patent Application WO/2021/005433
Kind Code:
A1
Abstract:
Provided are a reading comprehension assistance system and a reading comprehension assistance method for enabling input of natural language as a query sentence and presenting, to a reader, a location highly relevant to the input sentence. The reading comprehension assistance system includes: a document reading unit that reads a subject document; a document dividing unit that divides the subject document into a plurality of blocks; a first distributed representation acquisition unit that acquires distributed representations of words for each of the plurality of blocks; a query sentence reading unit that reads a query sentence; a second distributed representation acquisition unit that extracts words included in the query sentence and acquires distributed representations of the words; and a similarity degree acquisition unit that compares the distributed representations of the words between the query sentence and each of the plurality of blocks, and derives a similarity degree. The similarity degree acquisition unit: searches the words included in the blocks for a word that matches a word included in the query sentence; and for a matching word, derives a similarity degree between the distributed representations of the word in the blocks and the distributed representations of the word in the query sentence.
Inventors:
DOZEN YOSHITAKA (JP)
HIGASHI KAZUKI (JP)
YAMAMOTO KUNITAKA (JP)
HIGASHI KAZUKI (JP)
YAMAMOTO KUNITAKA (JP)
Application Number:
PCT/IB2020/055845
Publication Date:
January 14, 2021
Filing Date:
June 22, 2020
Export Citation:
Assignee:
SEMICONDUCTOR ENERGY LAB (JP)
International Classes:
G06F40/44; G06F16/332
Foreign References:
| JP2019082931A | 2019-05-30 |
Other References:
HOMMA, YUKINORI, SADAMITSU, KUGATSU,NISHIDA, KYOSUKE, ASANO, HISAKO, MATSUO: "Technical Reports of Spoken Language Processing (SLR)", PARTIAL DOCUMENT RETRIEVAL BASED ON DOCUMENT STRUCTURE, vol. 2017, no. 26, 8 May 2017 (2017-05-08), pages 1 - 6, ISSN: 2188-8663
MATT J. KUSNER ET AL.: "From Word Embeddings To Document Distances", PROCEEDINGS OF THE 32ND INTERNATIONAL CONFERENCE ON MACHINE LEARNINGS, vol. 37, 11 July 2015 (2015-07-11), pages 957 - 966, XP055723654, Retrieved from the Internet
MATT J. KUSNER ET AL.: "From Word Embeddings To Document Distances", PROCEEDINGS OF THE 32ND INTERNATIONAL CONFERENCE ON MACHINE LEARNINGS, vol. 37, 11 July 2015 (2015-07-11), pages 957 - 966, XP055723654, Retrieved from the Internet
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