计算机与现代化Issue(11)：89-94,6.DOI:10.3969/j.issn.1006-2475.2017.11.017
基于词重要性的Markov网络查询扩展模型
Markov Network Query Expansion Model Based on Term Importance
王千千 1罗文兵1
作者信息
- 1. 江西师范大学计算机信息工程学院,江西南昌330022
- 折叠
摘要
Abstract
The weight of term has been widely used in models of information retrieved.In order to solve the problem of independence assumption of word bags mode for traditional model,the weight of term based on the importance of term will be used in the Markov network query expansion model.In order to calculate the weight of the term,firstly we must establish the graph-of-word of documents.Then according to the graph-of-word,we get the matrix that terms occur together and the probability transfer matrix between terms.Lastly,we use the chain of Markov to get the weight of term.By putting the weight of term into the Markov network query expansion model,the experiment results on 5 standard datasets show that the search results of using Markov network query expansion model based on term importance are better than those based on traditional model of word bags.关键词
词项图/Markov网络/查询扩展Key words
graph-of-word/Markov network/query expansion分类
信息技术与安全科学引用本文复制引用
王千千,罗文兵..基于词重要性的Markov网络查询扩展模型[J].计算机与现代化,2017,(11):89-94,6.
