QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums

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Abstract

In this paper, we describe our QU-BIGIR system for the Arabic subtask D of the SemEval 2017 Task 3. Our approach builds on our participation in the past version of the same subtask. This year, our system uses different similarity features that encodes lexical and semantic pairwise similarity of text pairs. In addition to well-known similarity measures such as cosine similarity, we use other measures based on the summary statistics of word embedding representation for a given text. To rank a list of candidate question-answer pairs for a given question, we train a linear SVM classifier over our similarity features. Our best resulting run came second in subtask D with a very competitive performance to the first-ranking system.

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APA

Torki, M., Hasanain, M., & Elsayed, T. (2017). QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 360–364). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s17-2059

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