计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 485-488.doi: 10.11896/j.issn.1002-137X.2016.6A.114

• 软件工程与数据库技术 • 上一篇    下一篇

基于Copulas框架的混合式查询扩展方法

张书波,张引,张斌,孙达明   

  1. 东北大学信息科学与工程学院 沈阳110819,东北大学信息科学与工程学院 沈阳110819,东北大学信息科学与工程学院 沈阳110819,东北大学信息科学与工程学院 沈阳110819
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受宁夏回族自治区自然科学基金资助

Combined Query Expansion Method Based on Copulas Framework

ZHANG Shu-bo, ZHANG Yin, ZHANG Bin and SUN Da-ming   

  • Online:2018-11-14 Published:2018-11-14

摘要: 基于语义资料和局部分析的混合式查询扩展可以同时提供具有语义相关性和时效性的扩展结果,但如何有效地混合不同相似度度量指标是尚未解决的问题。提出了一种基于Copulas框架的混合式查询扩展方法,在统一框架内实现了不同类型相似度度量指标的合并。该方法基于语义分析及词语共现分析方法,分别计算扩展词与用户查询词的语义及统计相似概率,进而在Copulas框架下融合扩展词集,选取最高质量的扩展词形成查询扩展。实验结果表明,该方法充分利用了语义及词语共现分析查询扩展方法的优点,有效地弥补了两者的不足,提高了搜索结果的查准率,具有更优的搜索性能。

关键词: 信息检索,查询扩展,语义分析,词语共现分析,搜索性能

Abstract: Hybrid query expansion methods based on semantic and local analysis can provide time-sensitive extension results with semantic correlation.However,how to effectively combine two different kinds of similarity metrics has not been solved.This paper proposd a hybrid query expansion method based on the Copulas framework to implement the combination of different types of similarity metrics.Based on the query expansion methods of semantic and word co-occurrence analysis,the proposed method respectively calculates the semantical and the statistical similar probabilities between expansion-words and the query words submitted by the user.It then selects high quality extension words to obtain the final extension word set.The experimental results show that the method makes full use of the advantages of the two kinds of query expansion methods to improve the precision ratio factor.The method has better search performance.

Key words: Information retrieval,Query expansion,Semantic analysis,Word co-occurrence analysis,Search performance

[1] Carpineto C,Romano G.A Survey of Automatic Query Expansion in Information Retrieval[J].ACM Computing Surveys,2012,4(1):1-50
[2] Selvaretnam B,Belkhatir M.Natural Language Technology and Query Expansion:Issues,state-of-the-art and Perspectives[J].Journal of Intelligent Information Systems,2012,8(3):709-740
[3] 李兴春.信息检索技术中基于语义的扩展查询研究[J].重庆师范大学学报(自然科学版),2013,30(4):115-118
[4] Runkler T A,Bezdek J C.Automatic keyword extraction with relational clustering and Levenshtein distances[J].Institute of Electrical and Electronics Engineers,2002,9(2):636-640
[5] X Jin-xi,Croft B.Improving the effectiveness of information retrieval with local context analysis[J].ACM Transactions on Information Systems,2000,8(1):79-112
[6] 朱鲲鹏,魏芳.基于用户日志挖掘的查询扩展方法[J].计算机应用与软件,2012,9(6):113-115
[7] Pal D,Mitra M,Datta K.Improving Query Expansion UsingWordNet[C]∥CoRR.2013:1-18
[8] 王旭阳,萧波.基于本体和局部上下文分析的查询扩展方法[J].计算机工程,2012,8(7):57-59,9
[9] 吴秦,白玉昭,梁久祯.一种基于语义词典的局部查询扩展方法[J].南京大学学报(自然科学),2014,50(4):526-533
[10] 欧阳柳波,谭睿哲.一种基于本体和用户日志的查询扩展方法[J].计算机工程与应用,2015,51(1):151-155
[11] Sklar A.Fonctions de repartition an dimensions et leurs marges[J].Publ.Inst.Statist.Univ.Paris,1959,8(1):229-231
[12] Eickhoff C,de Vries A P,Collins-Thompson K.Copulas for Information Retrieval[C]∥SIGIR’13.Dublin,Ireland,2013:663-672

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!