Personalized Web Search System Based on Rough Sets
Lei Shi · 2007
In this paper,a novel rough set based approach is proposed to create a personalized Web search system. Firstly,user profiles which consist of categories of user's interests by grouping related keywords are designed.Rough set theory is used to deal with inherent ambiguities of natural language and refine query according to user profiles.Then refined query is submitted to search component.To further filter out irrelevant documents for the user,retrieved re- sults are re-ranked according to rough similarity measures between refined query and documents by ranking component. Experiments compared with traditional search engine are presented and experimental results indicate the precision of Web retrieval is greatly improved and system are suitable for individual usage.