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ITNLP-AiKF at SemEval-2016 task 3: A Question Answering system using community QA repository

  • Harbin Institute of Technology
  • Ltd.

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

Abstract

Community Question Answering (CAQ) systems play an important role in people's lives due to the huge knowledge accumulated in them. In order to take full advantage of the huge knowledge, the target of SemEval2016 task3 is to find the best answers to a new question in CQA. This work proposes to use rich semantic text similarity (STS) features to complete the task. We address the task as a ranking problem and Support Vector Regression (SVR) model is chosen to combine rich semantic similarity features and context features. Finally, we used genetic algorithm to do feature selection. Our method achieves an MAP (mean average precision) of 71.52%, 71.43% and 48.49% in subtask A, B and C respectively. It ranked 8th in subtask A and subtask B, and 7th in subtask C.

Original languageEnglish
Title of host publicationSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages904-909
Number of pages6
ISBN (Electronic)9781941643952
DOIs
StatePublished - 2016
Event10th International Workshop on Semantic Evaluation, SemEval 2016 co-located with the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016 - San Diego, United States
Duration: 16 Jun 201617 Jun 2016

Publication series

NameSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

Conference

Conference10th International Workshop on Semantic Evaluation, SemEval 2016 co-located with the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016
Country/TerritoryUnited States
CitySan Diego
Period16/06/1617/06/16

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