A modified ontology based personalized search engine using bond energy algorithm

Abstract

Search engines play an important function in increasing the speed of access to web information. As the volume of the content on the web is dynamically increasing, the general purpose web search engines are becoming inadequate. Since users with different backgrounds give queries in different contexts expecting different responses. The large number of irrelevant results returned by a search engine usually disappoints the user. The personalization of search engine overcomes this problem by ranking the results of web documents based on the inherent relations and closeness between the query concept and web document. In this paper we personalize the search engine using the Fuzzy Concept Network (FCN) and the Bond Energy Algorithm (BEA). The BEA calculates the closeness called affinity. Our main idea is to employ the concept network built based on the user's profile and ranks based on the Bond Energy Algorithm for searching and quickly retrieving of web pages. The advantage is that the most relevant search results can be retrieved. We examined our approach with data sets and prove our claims. © 2011 Springer-Verlag.