Research On Intelligent Information Retrieval Based On Rough Set Theory

The information retrieve is a kind of information service form of "the person seeks theinformation". They request the user to hand over keywords to check information for match.The network information search and obtainment also become more and more difficultbecause the network scale is more and more large and the information is more andmore .rich How quick and efficiently retrieval and visit information resource of all kindsfields in order to promote exchanges and share of information turn into a researchemphases on the respect of information retrieval. On the one hand, we study how to use thetechnique of artificial intelligence to process text information, on the other hand, we studyhow to express user's interesting and optimize user interesting query and hand overinteraction intelligently between user and retrieval system etc. This dissertation studies the method of intelligent information retrieval based onrough theory. Therefore, our main discussion is the technique of text information retrievaland the method of optimization of user query vector. This paper gives an optimizing method of the text index based on Rough Set. It usesUpper, Lower Approximation and rough including of the Rough Set to optimize query anddocuments. This paper introduces an algorithm by optimizing user query vector. Firstly, itoptimizes user's query, and then uses the query to index and match. Finally, returns thequery results in the descending of similarity of between documents and queries. The text,which uses Chinese text as research object, carries on experiment research by optimizedmethod in the text retrieval. The result expresses that the method is valid for the textinformation retrieval.