QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English

Massimo Nicosia, Simone Filice, Alberto Barrón-Cedeño, Iman Saleh, Hamdy Mubarak, Wei Gao, Preslav Nakov, Giovanni Da San Martino, Alessandro Moschitti, Kareem Darwish, Lluís Màrquez, Shafiq R. Joty, Walid Magdy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes QCRI’s participation in SemEval-2015 Task 3 “Answer Selection in Community Question Answering”, which targeted real-life Web forums, and was offered in both Arabic and English. We apply a supervised machine learning approach considering a manifold of features including among others
word n-grams, text similarity, sentiment analysis, the presence of specific words, and the context of a comment. Our approach was the best performing one in the Arabic subtask and the third best in the two English subtasks.
Original languageEnglish
Title of host publicationProceedings of the 9th International Workshop on Semantic Evaluation, SemEval@NAACL-HLT 2015, Denver, Colorado, USA, June 4-5, 2015
PublisherAssociation for Computational Linguistics (ACL)
Pages203-209
Number of pages7
ISBN (Print)978-1-941643-40-2
Publication statusPublished - Jun 2015

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