A Novel Architecture of Perception Oriented Web Search Engine Based on Decision Theory

The number of active web pages increases exponentially. According to the survey, the web has 14.3 trillion active web pages. The problem faced by present search engines is difficulty in returning relevant information. The current search engines do not perform semantic search and are not capable to return results based on user's perception. In this paper a perception based search engine is proposed that returns results as per the user point of view. To achieve semantic searching, a knowledge base is constructed which stores knowledge in the form of predicates. To extract knowledge from knowledge base, decision theory is used that does not restrict to any specific domain.