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J4 ›› 2011, Vol. 46 ›› Issue (5): 54-57.

• SEWM 2011 会议 • 上一篇    下一篇

基于Markov网络团的信息检索扩展模型

石松1,王明文1,涂伟2,何世柱1   

  1. 1.江西师范大学计算机信息工程学院, 江西 南昌330022;
    2.江西科技师范学院文科综合实验中心, 江西 南昌330038
  • 收稿日期:2010-12-06 发布日期:2011-05-25
  • 作者简介:石松(1985- ),男,硕士研究生,研究方向为信息检索与数据挖掘.Email:shisongjxnu@163.com
  • 基金资助:

    国家自然科学基金资助项目(60963014);江西省自然科学基金资助项目(2008GZS0052)

Extended information retrieval model based on the Markov network cliques

SHI Song1, WANG Ming-wen1, TU Wei2, HE Shi-zhu1   

  1. 1. College of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, Jiangxi, China;
    2. The Center of Arts Complex Laboratory,  Jiangxi Science & Technology  Normal  University,
    Nanchang 330038, Jiangxi, China
  • Received:2010-12-06 Published:2011-05-25

摘要:

全局分析方法是一种常用而能有效改善信息检索效果的查询扩展方法。通过计算词间相似度构造Markov网络模型;然后由此模型加强候选词集中的词相关性描述,并提取了在Markov网络中词间的团结构;通过在查询中加入查询词所在团中的其他候选词进行查询扩展。实验表明基于Markov网络团的信息检索模型的检索效果优于基于一般的相似性矩阵查询扩展的检索效果;基于团提取方法的查询扩展的检索效果优于普通的基于提取方法的查询扩展检索效果。

关键词: 查询扩展;全局分析;Markov网络;团结构

Abstract:

Query expansion based on global analysis model is a common and effective approach to improve information retrieval performance. First, the Markov network model was built by calculating the similarity between terms. Second, the description of relationship between candidate terms was strengthened, and the clique structure was extracted from the Markov network. Finally, candidate terms and query terms in the clique structure were merged for query expansion. Experimental results showed that query expansion based on the Markov random walk matrix performs better than  query expansion based on the similarity matrix, and query expansion based on the clique extraction method performs better than query expansion based on the general extraction method.

Key words:  query expansion; global analysis; Markov network; clique

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