Applying User Feedback and Query Learning Methods to Multiple Communities

摘要

This paper proposes a novel Peer-to-Peer Information Retrieval (P2PIR) method using user feedback and query-learning. The method actively utilizes negative feedback information so that other agents can filter it out when retrieving it. The proposed method effectively increases retrieval accuracy and decreases communication loads required for document retrieval in communities.The experiments were carried out on multiple communities constructed with multi-agent framework Kodama [1]. The experimental results illustrated the validity of our proposed method.