Toward Peer-to-Peer Based Semantic Search Engines: An Organizational Approach
Haizheng Zhang Victor Lesser · VDM Verlag Dr. Müller eBooks · 2008
This book frames a peer-to-peer information retrievalproblem as a multi-agent framework and attacks itfrom an organizational perspective by exploringvarious adaptive, self-organizing topologicalorganizations, designing appropriatecoordination strategies, and exploiting learningtechniques to create more accurate routing policy forlarge-scale agent organizations. In addition, areinforcement-learning based approach is developed inthis thesis to take advantage of the run-timecharacteristics of P2P IR systems, includingenvironmental parameters, bandwidth usage, andhistorical information about past search sessions. Inthe learning process, agents refine their contentrouting policies by constructing relatively accuraterouting tables based on a Q-learning algorithm.Experimental results show that this learningalgorithm considerably improves the performance ofdistributed search sessions in P2P IR systems.The book is addressed to researchers andpractitioners in information retrieval and searchengine, content-based routing areas.