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SCIR-QA at SemEval-2017 Task 3: CNN Model Based on Similar and Dissimilar Information between Keywords for Question Similarity

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We describe a method of calculating the similarity between questions in community QA. Questions in cQA are usually very long and there are a lot of useless information about calculating the similarity between questions. Therefore, we implement a CNN model based on similar and dissimilar information on questions keywords. We extract the keywords of questions, and then model the similar and dissimilar information between the keywords, and use the CNN model to calculate the similarity.

Original languageEnglish
Title of host publicationACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages305-309
Number of pages5
ISBN (Electronic)9781945626555
DOIs
StatePublished - 2017
Event11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada
Duration: 3 Aug 20174 Aug 2017

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

Conference11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
Country/TerritoryCanada
CityVancouver
Period3/08/174/08/17

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