基于用户回答顺序的社区问答答案质量预测研究  

Answer Quality Prediction Based on the Answering Order in Community Question Answering

作　　者：徐安滢[1] 吉宗诚 王斌[3] 

机构地区：[1]中国科学院计算技术研究所,北京100190 [2]华为诺亚方舟实验室,北京100085 [3]中国科学院信息工程研究所,北京100093

出　　处：《中文信息学报》2017年第2期132-138,共7页Journal of Chinese Information Processing

摘　　要：近年来,随着互联网的普及和知识爆炸性的增长,社区问答网站积累了大量的用户和内容,同时也产生了大量的低质量文本,极大地影响了用户检索满意答案的效率,因此如何提升答案质量预测的性能十分重要。目前,社区问答答案质量预测方面的研究大都是使用点方式(pointwise)来实现分类模型,但由于问题的难度不同,对答案的要求也有所差异,使用点方式会忽略掉部分答案的特点,所以该文使用点对方式(pairwise)来预测答案质量。另外,已有的研究工作表明,社区问答中同一问题下的答案数量特征对答案质量预测没有效果,甚至有冗余作用。对于时间差也有相同的结论,即不能提升预测性能。该文提出了一种将上述两者结合在一起的新特征,实验结果表明,该特征能显著提高社区问答答案质量预测的性能。In recent years, with the popularity of the internet and the explosive growth of the knowledge, community question answering websites had accumulated a large number of users and content, and generated a large amount of low quality text. It had greatly adverse effect for users to retrieve correct answers. Most present work about answer quality prediction in community question answering used the pointwise method to train a classification model. However, different questions have different difficulties and thus have different requirements of their answers. In addition, some of the answers＇ teatures can not be easily characterised by the pointwise method. Therefore, this paper used the pairwise method to predict answer quality. Moreover, previous work has shown that the number of answers in one question is useless, even reduncdant for predicting the answer quality in community question answer lug. The conclusion is same for the time difference factor. This paper combines these two features into one new feature. Experimental results show that the new feature can significantly improve the prediction performance.

关 键 词：答案质量预测 排序学习 社区问答 回答顺序 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]