@inproceedings{4c66872d4345471290e4c3a4629c79c5,
title = "Answer selection in arabic community question answering: A feature-rich approach",
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).",
author = "Yonatan Belinkov and Alberto Barr{\'o}n-Cede{\~n}o and Hamdy Mubarak",
note = "Publisher Copyright: {\textcopyright} ACL 2015. All rights reserved.; 2nd Workshop on Arabic Natural Language Processing, ANLP 2015 ; Conference date: 30-07-2015",
year = "2015",
language = "English",
series = "2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "183--190",
editor = "Nizar Habash and Stephan Vogel and Kareem Darwish",
booktitle = "2nd Workshop on Arabic Natural Language Processing, ANLP 2015 - held at 53rd Annual Meeting of the Association for Computational Linguistics, ACL 2015 - Proceedings",
address = "United States",
}