基于Word2vec的语义查询扩展方法  

Semantic Query Expansion Method Based on Word2vec

作　　者：章露露[1] 吕晓伟[1] ZHANG Lu-lu;LV Xiao-wei(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学信息工程与自动化学院,云南昆明650500

出　　处：《软件导刊》2018年第9期48-51,共4页Software Guide

摘　　要：查询扩展是信息检索领域重要研究内容。为了解决信息检索过程中用户提交查询时描述不准确以及查询词不匹配的问题,提出一种基于Word2vec的语义查询扩展方法。使用分布式神经语言概率模型Word2vec训练低维词向量,选取扩展词候选集,利用面向扩展词的查询向量生成方法过滤候选集,使选取的扩展词能更有效地体现整个查询的语义及语法相关性。实验结果表明基于Word2vec的语义查询扩展方法使查全率及查准率均有提高,因此该方法能很好地应用于查询扩展领域。Query expansion is an important research issue in the field of information retrieval.In order to solve the problem of inaccurate description and mismatch when users submit queries,we propose a new semantic query expansion method based on Word2vec.The distributed neural language probability model word2vec is used to train the low dimensional word vectors to select the expansion term anthology,and a new query vector generation method based on extended words is proposed to filter candidate sets,so that the selected extended words can be reflected more effectively in the semantic and grammatical correlation of the whole query.The experimental results show that the semantic query expansion method based on Word2vec has improved both the recall rate and the precision ratio.Therefore,the semantic query extension method based on Word2vec can be applied to the domain of query extension well.

关 键 词：查询扩展 分布式神经语言概率模型 Word2vec 面向扩展词 语义相关性 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]