@inproceedings{2abff2bc65874063a670d362fca104bc,
title = "VectorSLU: A Continuous Word Vector Approach to Answer Selection in Community Question Answering Systems",
abstract = "Continuous word and phrase vectors have proven useful in a number of NLP tasks. Here we describe our experience using them as a source of features for the SemEval-2015 task 3, consisting of two community question answering subtasks: Answer Selection for categorizing answers as potential, good, and bad with regards to their corresponding questions; and YES/NO inference for predicting a yes, no, or unsure response to a YES/NO question using all of its good answers. Our system ranked 6th and 1st in the English answer selection and YES/NO inference subtasks respectively, and 2nd in the Arabic answer selection subtask.",
author = "Yonatan Belinkov and Mitra Mohtarami and Scott Cyphers and James Glass",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics; 9th International Workshop on Semantic Evaluation, SemEval 2015 ; Conference date: 04-06-2015 Through 05-06-2015",
year = "2015",
language = "الإنجليزيّة",
series = "SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings",
pages = "282--287",
editor = "Preslav Nakov and Torsten Zesch and Daniel Cer and David Jurgens",
booktitle = "SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics",
}