Agent-Community-Based Peer-to-Peer Information Retrieval and Its Evaluation

摘要

The Agent-Community-based Peer-to-Peer (ACP2P) information retrieval method uses agent communities to manage and look up information of interest to users. An agent works as a delegate of its user and searches for information that the user wants by communicating with other agents. The communication between agents is carried out in a peer-to-peer computing architecture. Retrieving information relevant to a user query is performed with content files which consist of original and retrieved documents, and two histories: a query/retrieved document history and a query/sender agent history. Making use of the histories has a collaborative filtering effect, which gradually creates virtual agent communities, where agents with the same interests stay together. Our hypothesis is that a virtual agent community reduces communication loads necessary to perform a search. As an agent receives more queries, then more links to new knowledge are acquired. From this behavior, a "give-and-take" (or positive feedback) effect for agents seems to emerge. However, we have only shown parts of the effects of reducing communication loads and making "give-and-take" through preliminary experimental results. This paper discusses more detail of experimental results and shows that the two histories help in reducing communication loads among agents, facilitating bidirectional communications between them and thus creating virtual agent communities, where agents with the same interests stay together.