SPDM: New Approach for Personalized Web Search
Organizations and educational institutions wish to use personalized applications which manage huge amount of information accessible at online through user profiling that helps to mold information presented to individual user. Existing methods uses personalized filtering and rating system for generating user profiles. This process becomes tedious due to huge amount of information updated on web every day. This paper proposes a new user profile generation named Semantic Preference Distribution Mechanism (SPDM) focuses on efficiency by providing browsing assistance and adaptive links. The authors' proposed mechanism makes use of topic ontology association. It takes two ontologies and produces a set of semantic correspondence between the group of elements and others.