【摘 要】
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Enabling a computer to understand a document so that itcan answer comprehension questions is a central,yet unsolved goal of Natural Language Processing,so reading comprehension of text is an important
【机 构】
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School of Computer Science and Technology,Dalian University of Technology
【出 处】
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第十六届全国计算语言学学术会议暨第五届基于自然标注大数据的自然语言处理国际学术研讨会
论文部分内容阅读
Enabling a computer to understand a document so that itcan answer comprehension questions is a central,yet unsolved goal of Natural Language Processing,so reading comprehension of text is an important problem in NLP research.In this paper,we propose a nov-el dual interaction model(called DIM Reader)1,which constructs dual iterative alternating attention mechanism over multiple hops.The pro-posed DIM Reader continually refines its view of the query and document while aggregating the information required to answer a query,aiming to compute the attentions not only for the document but also the query side,which will benefit from the mutual information.DIM Reader makes use of multiple turns to effectively exploit and perform deeper inference among queries,documents.We conduct extensive experiments on CN-N/DailyMail News datasets,and our model achieves the best results on both machine comprehension datasets among almost published results.
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