Question Classification Based on Word Association for Question and Answer Archives

Xu Jin, K. Lee
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引用次数: 1

Abstract

Word mismatch is the most significant problem that causes low performance in question classification, whose questions consist of only two or three words that expressed in many different ways. So, it is necessary to apply word association in question classification. In this paper, we propose question classification method using translation-based language model, which use word translation probabilities for question-question pair that is learned in the same category. In the experiment, we prove that translation probabilities of question-question pairs in the same category is more effective than question-answer pairs in total collection.
基于词关联的问答档案问题分类
单词不匹配是导致问题分类性能低下的最重要的问题,因为问题仅由两三个单词组成,这些单词以许多不同的方式表达。因此,在问题分类中应用词关联是很有必要的。本文提出了一种基于翻译语言模型的问题分类方法,该方法利用同一类别中学习到的问题对的单词翻译概率进行问题分类。在实验中,我们证明了在总集合中,同一类别的问答对的翻译概率比问答对的翻译概率更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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