QCRI: Answer selection for community question answering - Experiment for Arabic and English

• Main Authors: NICOSIA, Massimo, FILICE, Simone, BARRON-CEDENO, Alberto, SALEH, Iman, MUBARAK, Hamdy, GAO, Wei, NAKOV, Preslav, MARTINO, Giovanni Da San, MOSCHITTI, Alessandro, DARWISH, Kareem, MARQUZ, Lluis Marquz, JOTY, Shafiq, MAGDY, Walid Magdy
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/4579; https://ink.library.smu.edu.sg/context/sis_research/article/5582/viewcontent/S15_2036.pdf
• Institution: Singapore Management University

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