Designing agents as if people mattered
Software agents
Multi-agent learning approach to WWW information retrieval using neural network
IUI '99 Proceedings of the 4th international conference on Intelligent user interfaces
Building efficient and effective metasearch engines
ACM Computing Surveys (CSUR)
Resource description framework: metadata and its applications
ACM SIGKDD Explorations Newsletter
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
A New Approach of the Collaborative User Interface Agents
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
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The Internet represents the biggest communication media and its dimension increases every day. This continuous growth of information makes the Internet more and more interesting, but also the task of finding selected information becomes more complex and hard. Finding exactly what a user needs is not always an easy task: for example common search engines provide thousands of links for every search. Obviously not all these links are related to what the user really needs. In this paper, we present a Collaborative Autonomous Interface Agent (CAIA) that collaborates with the Internet search engines and supports the user in finding exactly the information consistent with his/her interest. A system has been designed, fully implemented and tested. The testing results shows a big improvement in the relevancy of the retrieved links and of the user's satisfaction by using CAIA+Google compared to using only Google.