Fusing Data and Optimizing Queries for Intelligent Search

A progressive application of evolutionary computing to optimize Boolean search queries in crisp and fuzzy information retrieval systems was investigated, evaluated in laboratory environment and presented. Additionally, WebFusion - novel meta- search engine contributing to the effectiveness of web search has been presented. The system learns the expertness of every particular underlying standalone search engine in a certain category based on the users ' preferences estimated according to an analysis of the click-through behavior. An intelligent re-ranking based on ordered weighted averaging is used for fusing the results' scores obtained from the underlying search engines. In this paper, the two promising web search improvement techniques are merged on the way towards intelligent search application.