Personalized Web Retrieval based on Rough-Fuzzy Method
نویسندگان
چکیده
In this paper, a novel approach of rough-fuzzy hybridization is proposed for efficient personalized Web retrieval. Variable precision rough set model is used to discover user preference. Fuzzy sets are incorporated to take care of the real-valued weights in each document vector. Discerning keywords are identified to refine a query for more focused representation. To further filter out irrelevant documents for the user, retrieved results are re-ranked according to rough similarity measures. Experiments compared with traditional search engine are presented and experimental results indicate the performance of document retrieval is greatly improved.
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