Answer selection in arabic community question answering: A feature-rich approach

Yonatan Belinkov, Alberto Barrón-Cedeño, Hamdy Mubarak

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

4 Citations (Scopus)

Abstract

The task of answer selection in community question answering consists of identifying pertinent answers from a pool of user-generated comments related to a question. The recent SemEval-2015 introduced a shared task on community question answering, providing a corpus and evaluation scheme. In this paper we address the problem of answer selection in Arabic. Our proposed model includes a manifold of features including lexical and semantic similarities, vector representations, and rankings. We investigate the contribution of each set of features in a supervised setting. We show that employing a feature combination by means of a linear support vector machine achieves a better performance than that of the competition winner (F1 of 79.25 compared to 78.55).

Original languageEnglish
Title of host publication2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings
EditorsNizar Habash, Stephan Vogel, Kareem Darwish
PublisherAssociation for Computational Linguistics (ACL)
Pages183-190
Number of pages8
ISBN (Electronic)9781941643587
Publication statusPublished - 2015
Event2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - Beijing, China
Duration: 30 Jul 2015 → …

Publication series

Name2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings

Conference

Conference2nd Workshop on Arabic Natural Language Processing, ANLP 2015
Country/TerritoryChina
CityBeijing
Period30/07/15 → …

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