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基于Markov网络的检索模型

曹 瑛,王明文,陶红亮   

  1. 江西师范大学计算机信息工程学院, 江西 南昌330022
  • 收稿日期:2006-03-29 修回日期:1900-01-01 出版日期:2006-10-24 发布日期:2006-10-24
  • 通讯作者: 王明文

Information retrieval model based on Markov Network

CAO Ying,WANG Ming-wen,TAO Hong-liang   

  1. College of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
  • Received:2006-03-29 Revised:1900-01-01 Online:2006-10-24 Published:2006-10-24
  • Contact: WANG Ming-wen

摘要: 基于Markov网络的信息检索模型提出一种贝叶斯网络推广的检索模型,该模型利用词项在文档集中的共现信息来构造Markov网络,通过该索引项子Markov网络来加载附加查询证据源,计算文档与查询之间的相关性概率,由此概率进行文档排序. 实验结果表明,本文提出的Markov网络模型比其他传统的检索方法具有更优的检索性能.

关键词: Markov网络, 信息检索模型, 查询证据源

Abstract: A novel method is proposed and realized based on Markov Network, which can construct Markov Network according to the co-occurrence information of the terms in collection. The relevance probability between document and query is computed by adding additional evidential sources to the model from the term space Markov Network. Experiment results show that our Markov model method can get more effective performances compared with other methods.

Key words: query evidential source , information retrieval model, Markov Network

[1] 石松1,王明文1,涂伟2,何世柱1. 基于Markov网络团的信息检索扩展模型[J]. J4, 2011, 46(5): 54-57.
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