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基于概率粗糙集模型的信息检索
引用本文:黄治国,朱承学,薛凡,王加阳. 基于概率粗糙集模型的信息检索[J]. 计算机工程, 2008, 34(23): 193-195
作者姓名:黄治国  朱承学  薛凡  王加阳
作者单位:1. 黄淮学院国际学院,驻马店,463000
2. 湖南第一师范学院信息技术系,长沙,410002
3. 中南大学信息科学与工程学院,长沙,410083
基金项目:河南省教育科学"十一五"规划课题基金资助项目,湖南省自然科学基金资助项目,湖南省教育厅科研基金资助项目
摘    要:针对经典粗糙集模型难以分类标引空间以及体现类间关联的缺陷,将条件概率关系结合粗糙集理论引入信息检索,提出一种基于概率粗糙集的信息检索模型。定义标引词空间的条件概率关系,自动挖掘概念相似类形成概念空间。定义文档与查询、文档与文档间语义贴近度的计算方法。根据贴近度实现检索匹配结果的排序输出。仿真实例表明了该方法的可行性和有效性。

关 键 词:粗糙集  信息检索  条件概率关系  语义贴近度
修稿时间: 

Information Retrieval Based on Probability Rough Set Model
HUANG Zhi-guo,ZHU Cheng-xue,XUE Fan,WANG Jia-yang. Information Retrieval Based on Probability Rough Set Model[J]. Computer Engineering, 2008, 34(23): 193-195
Authors:HUANG Zhi-guo  ZHU Cheng-xue  XUE Fan  WANG Jia-yang
Affiliation:(1. International College, Huanghuai University, Zhumadian 463000; 2. Department of Information and Technology, Hunan First Normal College, Changsha 410002; 3.School of Information Science and Engineering, Central South University, Changsha 410083)
Abstract:Aiming at the disadvantage of classical rough set theory on identifying the conceptually similar terms and the relationships between classes, this paper proposes a novel information retrieval model based on conditional probability relation and rough set. Conception space is formed by defining conditional probability relation in index words space to mine conception similar class automatically. A method is designed to calculate semantic distance between a document and a query, as well as documents. And the ordered outputs of retrieval result are acquired. The simulation instance shows that this algorithm is feasible and effective in practice.
Keywords:rough set  information retrieval  conditional probability relation  semantic distance
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