The Internet is a cooperative and decentralized network built out of millions of participants that share large amounts of information. Peer-to-peer (P2P) systems go hand-in-hand with this huge decentralized network, where each individual node can serve content as well as request it. In this scenario, thematic search algorithms should lead to and benefit from the emergence of semantic communities that are the result of the interaction among participants. As a consequence, intelligent algorithms for neighbor selection should give rise to a logical network topology reflecting efficient communication patterns. When routing queries within a P2P network different conflicting issues may arise in individual nodes, such as deciding whether to propagate a query or to reject its processing. Such issues emerge in the context of incomplete and potentially inconsistent information in a distributed setting. To the best of our knowledge, current algorithmic approaches to P2P query processing are mostly based on a "reactive" approach, endowing the individual nodes with little or no intelligence. This paper presents a novel approach to use argumentation as part of the decision making machinery within individual nodes in a P2P network for thematic search. Our approach will rely on assumption-based argumentation (ABA). We provide a formalization for P2P networks for thematic search, on top of which intelligent algorithms based on ABA are specified. A case study is used to illustrate the proposed approach, providing insights into the performance of the new framework.
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