ConvKN at SemEval-2016 task 3: Answer and question selection for question answering on Arabic and English fora

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24 Citations (Scopus)

Abstract

We describe our system, ConvKN, participating to the SemEval-2016 Task 3 "Community Question Answering". The task targeted the reranking of questions and comments in real-life web fora both in English and Arabic. ConvKN combines convolutional tree kernels with convolutional neural networks and additional manually designed features including text similarity and thread specific features. For the first time, we applied tree kernels to syntactic trees of Arabic sentences for a reranking task. Our approaches obtained the second best results in three out of four tasks. The only task we performed averagely is the one where we did not use tree kernels in our classifier.

Original languageEnglish
Title of host publicationSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages896-903
Number of pages8
ISBN (Electronic)9781941643952
Publication statusPublished - 1 Jan 2016
Event10th International Workshop on Semantic Evaluation, SemEval 2016 - San Diego, United States
Duration: 16 Jun 201617 Jun 2016

Other

Other10th International Workshop on Semantic Evaluation, SemEval 2016
CountryUnited States
CitySan Diego
Period16/6/1617/6/16

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Science Applications

Cite this

Barron, A., Bonadiman, D., Martino, G., Rayhan Joty, S., Moschitti, A., Khalid Al Obaidli, F., Romeo, S., Tymoshenko, K., & Uva, A. (2016). ConvKN at SemEval-2016 task 3: Answer and question selection for question answering on Arabic and English fora. In SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings (pp. 896-903). Association for Computational Linguistics (ACL).