Using swarm intelligence to perceive the semantic web

Abstract

Semantic web comes with heterogeneous sources of knowledge including texts, graphics, blogs, animations, audios, and videos. However, there have been limited researches conducted to present semantic web information in the form suitable to individuals. This paper reports on the design and implementation of 'Divon', a swarm of agents that emulate a user profile driven approach to the present semantic web information in the forms suitable to individuals. Divon has been structured with four agents, namely, Message Agent, Query Handler Agent, Presentation Agent, and User Profiler Agent. The Message Agent plays a key role in guiding the search process and displaying the information in a suitable form for the user whereas User Profiler Agent Creates individual user profiles according to individual preferences. Divon has been developed on JADE environment and can run on any computer in connection with an arbitrary search engine. Divon has been evaluated against three metrics, namely, average search time, average response time and the precision withi top 10 results. Evaluation results have shown that divon enhance the performance relative to the Google in average search time and precision within top ten results. However divon gets slightly slower in response time due to the fact that it operates on top of the Google © 2008 IEEE.