作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2010, Vol. 36 ›› Issue (21): 43-45. doi: 10.3969/j.issn.1000-3428.2010.21.015

• 软件技术与数据库 • 上一篇    下一篇

基于潜在语义分析的个性化查询扩展模型

王卫国,徐炜民   

  1. (上海大学计算机工程与科学学院,上海 200072)
  • 出版日期:2010-11-05 发布日期:2010-11-03
  • 作者简介:王卫国(1986-),男,硕士研究生,主研方向:信息检索,数据挖掘;徐炜民,教授
  • 基金资助:
    上海市科委基金资助重大项目“上海市科普资源开发与共享信息化(二期)工程建设”(07dz23401)

Personalized Query Expansion Model Based on Latent Semantic Analysis

WANG Wei-guo, XU Wei-min   

  1. (College of Computer Engineering and Science, Shanghai University, Shanghai 200072, China)
  • Online:2010-11-05 Published:2010-11-03

摘要: 为在信息检索系统中获得更好的查询效果,提出一种混合的个性化查询扩展模型。通过潜在语义分析建立潜在语义空间,并在潜在语义空间中计算得到查询的概念相关扩展词和兴趣相关扩展词,不但有效解决了词典问题,而且满足了不同用户需求多样性和用户多兴趣点的需求。实验表明,该算法能够较好地提高搜索引擎系统的查全率、查准率,以及信息检索效率。

关键词: 潜在语义分析, 用户兴趣, 查询扩展, 个性化推荐, 信息检索

Abstract: In order to improve the quality of information retrieval systems, this paper proposes a complex and personalized model of query expansion. The proposed approach constructs a latent semantic space to get semantic concept related and interest related words. In this way, the model solves the famous vocabulary problem and meets various users’ needs. Experiments show this algorithm can significantly improve precision, recall and efficiency in information retrieval, meeting different users’ requirements in search engine systems.

Key words: latent semantic analysis, user interest, query expansion, personal recommendation, information retrieval

中图分类号: