Refinement of the ACP2P by sharing user-feedbacks and learning query-responder-agent-relationships
Tsunenori Mine, Akihiro Kogo, Satoshi Amamiya, Makoto Amamiya · 2009
This paper proposes two methods for improving the retrieval accuracy of the Agent-Community-based Peer-to-Peer information retrieval (ACP2P) method. One uses user feedbacks exchanged in a community. The other uses query-learning methods that make a middle agent to learn query-responder agent relationships. The latter methods are useful not only for improving the retrieval accuracy, but also for reducing communication loads. We conduct several experiments with test collections so that the evaluation can be done in an objective manner. The experimental results illustrate the validity of our proposed methods.