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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Kim Anh Nguyen
ThaiNguyen University of Information and Communication Technology
Computer Science & IT Engineering

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Supervised attention for answer selection in community question answering Thanh Thi Ha; Atsuhiro Takasu; Thanh Chinh Nguyen; Kiem Hieu Nguyen; Van Nha Nguyen; Kim Anh Nguyen; Son Giang Tran
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2269.59 KB) | DOI: 10.11591/ijai.v9.i2.pp203-211

Abstract

Answer selection is an important task in Community Question Answering (CQA). In recent years, attention-based neural networks have been extensively studied in various natural language processing problems, including question answering. This paper explores matchLSTM for answer selection in CQA. A lexical gap in CQA is more challenging as questions and answers typical contain multiple sentences, irrelevant information, and noisy expressions. In our investigation, word-by-word attention in the original model does not work well on social question-answer pairs. We propose integrating supervised attention into matchLSTM. Specifically, we leverage lexical-semantic from external to guide the learning of attention weights for question-answer pairs. The proposed model learns more meaningful attention that allows performing better than the basic model. Our performance is among the top on SemEval datasets.
Co-Authors Atsuhiro Takasu Kiem Hieu Nguyen Son Giang Tran Thanh Chinh Nguyen Thanh Thi Ha Van Nha Nguyen