Answer stance detection based on recurrent interactive attention network

LUO Wangda; LIU Yuhan; LIANG Bin; XU Ruifeng

doi:10.16511/j.cnki.qhdxxb.2021.21.006

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Journal of Tsinghua University(Science and Technology) ›› 2021, Vol. 61 ›› Issue (9) : 913-919. DOI: 10.16511/j.cnki.qhdxxb.2021.21.006

COMPUTATIONAL LINGUISTICS

Answer stance detection based on recurrent interactive attention network

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Abstract

Most existing answer stance detection methods ignore the interactive dependence between question and answer. This paper describes an answer stance detection method based on a recurrent interactive attention (RIA) network. This method simulates the human interactions in question-answer reading comprehension using an interactive attention mechanism and iterations to simulate the interactive dependence between question and answer for detecting the answer stance. In addition, since the question text cannot explicitly express its stance, the question text is transformed into declarative sentences. Tests on a Chinese social media question-answer dataset show that this method outperforms existing answer stance detection methods due to the effective representation of the interactive dependence between the question and the answer.

Key words

answer stance detection / recurrent interactive attention / question representation

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LUO Wangda, LIU Yuhan, LIANG Bin, XU Ruifeng. Answer stance detection based on recurrent interactive attention network[J]. Journal of Tsinghua University(Science and Technology). 2021, 61(9): 913-919 https://doi.org/10.16511/j.cnki.qhdxxb.2021.21.006

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