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基于术语关联图的查询重组
引用本文:罗永强,周华奇,肖金升.基于术语关联图的查询重组[J].计算机应用与软件,2004,21(3):3-4,31.
作者姓名:罗永强  周华奇  肖金升
作者单位:复旦大学计算机与信息技术系,上海,200433
基金项目:国家自然科学基金资助项目(699330 1 0 ),上海市自然科学基金资助项目 (0 0ZD1 4 0 0 6)
摘    要:当用户向搜索引擎提交查询时,查询术语之间一般会存在内在关联。发现这种术语关联,对更好地描述用户的意图具有积极的研究意义。本文在术语关联网络TAN的基础上,首先设计查询术语关联图构造算法(QTAG)勾勒出用户查询中的术语关联;其次,利用术语权重调整算法(TWA)修改术语权重,从而形成新的更侧重干目的的查询。本文提出的方法在一定程度上优化了用户查询。

关 键 词:WWW  分布式信息检索  布尔模型  向量模型  概率模型  术语关联图  查询重组  搜索引擎

QUERY REORGANIZATION BASED ON TERM ASSOCIATION GRAPH
Luo Yongqiang,Zhou Huaqi,Xiao Jinsheng.QUERY REORGANIZATION BASED ON TERM ASSOCIATION GRAPH[J].Computer Applications and Software,2004,21(3):3-4,31.
Authors:Luo Yongqiang  Zhou Huaqi  Xiao Jinsheng
Abstract:When a query is presented to a search engine,there may exist some associations among the terms expressed.If the hidden associations are found out,it will be of great benefit to describe user's purpose.We try to achieve the goal by the term association network.Firstly,we run QTAG (Query Term Association Graph)algorithm on the TAN to construct the term association graph(TAG).Secondly,we apply TWA(Term Weight Adjustment) algorithm on the TAG to modify the term weights,which,in turn,forms a new query.Our method optimizes a query in some degree.
Keywords:Term association network  Term association graph  Term selection  Weight adjustment  
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