FBK-HLT: An Application of Semantic Textual Similarity for Answer Selection in Community Question Answering

Abstract

This paper reports the description and performance of our system, FBK-HLT, participating in the SemEval 2015, Task #3 "Answer Selection in Community Question Answering" for English, for both subtasks. We submit two runs with different classifiers in combining typical features (lexical similarity, string similarity, word n-grams, etc.) with machine translation evaluation metrics and with some ad hoc features (e.g user overlapping, spam filtering). We outperform the baseline system and achieve interesting results on both subtasks.