Fuzzy induction in dynamic user profiling for information filtering
Rafal A. Angryk, Costin Barbu · 2004
In this paper we investigate the role of the user profile in information filtering and we introduce a novel algorithm for learning the user profile based on user’s initial profile and on a queries ’ interpretation using fuzzy generalization (Angryk and Petry 2003). Thousands of documents are usually retrieved by search engines for a given query during an information search on WWW. One way to prune irrelevant documents is to take advantage of the user’s implicit interests to filter the documents returned by the search engine, or to reformulate the query based on these interests. One of the common representations of the documents (and queries) in information retrieval is based on the vector hyperspace model (Salton and McGill 1993). We are using the expanded version of Salton’s vector space model