基于模糊粗糙集理论的信息检索方法的研究

信息检索中的词汇挖掘就是利用给定域范围的词汇来提高用户查询效率，大多数情况下信息检索系统上的查询不是优化的。词汇挖掘可以使我们在查询上进行泛化、特化或者其他基于词汇转换的操作来提高查询性能。本文将粗糙集和模糊集理论结合起来研究了一种新的词汇挖掘框架，该框架即使当文本和查询使用加权表示即模糊表示时，也可以用基于粗糙集的近似集合。

Research of methods for information retrieval based on fuzzy rough set theory

Vocabulary mining ininformationretrieval refersto theutilization of the domain vocabulary towardsimproving the user's query. Most often queries posed to information retrieval systems are not optimal for retrieval purposes. Vocabulary mining allows one to generalize, specialize or perform other kinds of vocabulary-based transformations on the query in order to improve retrieval performance. In this paper a new framework for vocabulary mining is investigated which derives from the combination of rough sets and fuzzy sets. The framework allows one to use rough set-based approximations even when the documents and queries are described using weighted, i.e., fuzzy representations.