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.
REF derived features from a comment in the context of the entire thread.
QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English
SemEval@NAACL-HLT
Computer Science