交互式问答是具备处理系列相关问题以及与用户进行对话式交互的问答技术,是近年来国际上问答技术研究的一个热门方向,但是目前在中文问答领域几乎没有开展相关的研究。实现交互式问答系统首先要判别用户系列问题之间的相关性。该文探讨了提取问题中不同特征对中文交互式问答问题相关检测的作用,并且根据识别出的有效特征采用基于二元分类方法分别对翻译成中文的TREC QA问题集语料和真实的交互式问答语料进行问题相关检测实验,实验结果显示该文的方法获得了较好的问题相关检测效果。
Abstract
Interactive question answering (IQA) is a kind of QA technology that is able to process a series of coherent questions and interact with users by the means of dialogue, Being a hot research topic in the area of QA, though. IQA is less touched in Chinese to our knowledge. An important problem in a typical IQA system is the relevance recognition among a series of questions. This paper analyzes the effectiveness of different features extracted from questions on relevance recognition of question in Chinese IQA. Based on the key features detected, we experiment the Binary Classification model on the TREC QA task question set that was translated to Chinese, as well as a real IQA question set. Experimental results show that the proposed method is effective.
Key wordscomputer application; Chinese information processing;interactive question answering; question; relevance recognition; binary classification
关键词
计算机应用 /
中文信息处理 /
交互式问答 /
问题 /
相关检测 /
二元分类
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Key words
computer application /
Chinese information processing /
interactive question answering /
question /
relevance recognition /
binary classification
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参考文献
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脚注
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基金
国家自然科学基金重点项目资助(60736044);国家自然科学基金面上项目资助(60675034);国家863计划探索类专题项目资助(2008AA01Z144)
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