GW_QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora

Proceedings of the 11th International Workshop on Semantic Evaluations (SemEval-2017), pages 344–348, Vancouver, Canada, August 3 - 4, 2017. c⃝2017 Association for Computational Linguistics GW QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora Nada Almarwani and Mona Diab Department of Computer Science The George Washington University {nadaoh;mtdiab}@gwu.edu Abstract This paper describes our submission to SemEval-2017 Task 3 Subtask D, ”Ques- tion Answer Ranking in Arabic Commu- nity Question Answering”. In this work, we applied a supervised machine learn- ing approach to automatically re-rank a set of QA pairs according to their relevance to a given question. We employ features based on latent semantic models, namely WTMF, as well as a set of lexical features based on string length and surface level matching. The proposed system ranked first out of 3 submissions, with a MAP score of 61.16%. 1 Introduction Nowadays Community Question Answering (CQA) websites provide a virtual place for users to share and exchange knowledge about different topics. In most cases, users freely express their concerns and hope for some reliable answers from specialists or other users. In addition, they can search for an answer from previously posted question-answers (QA) that are similar to their question. Although posting a question and looking for a direct or related answer in CQA sounds appealing, the number of unanswered questions are relatively high. According to Baltadzhieva and Chrupała (2015) the number of unanswered questions in Stack Overflow1 and Yahoo! Answers2 are approximately 10.9% and 15%, respectively. Interestingly, as noted in (Asaduzzaman et al., 2013), the high percentage of unanswered questions is due to the duplicate question problem, i.e. the existence of a similar question that had been addressed before, which 1A programming CQA forum 2A community-driven question-and-answer site makes users not re-address the question again. Hence, it is the asker’s role to review the site looking for an answer before posting a new question. This is a task that requires searching related questions from a hundred others posted on a daily basis. Thus, in a good forum there should be an automatic search functionality to retrieve the set of QA that are more likely to be related to the new question being asked. As a result, the number of duplications and unanswered questions will be limited. In order to find a solution to this and other prob- lems in CQA, the SemEval 2015, 2016, and 2017 Task 3 have been dedicated to dealing with ”An- swer Selection in Community Question Answer- ing” (Nakov et al., 2017, 2016; AlessandroMos- chitti et al., 2015). There are 5 different subtasks, one of which has been proposed for Arabic. The specific task for Arabic in the SemEval 2016-2017 Task 3, subtask D, was to re-rank the possible re- lated question-answer pairs to a given question. The Arabic task is especially difficult due to its challenging characteristics. Arabic is one of the most complex languages to process due to its mor- phological richness, with relative free word order, and its diglossic nature (where the …

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