Abstract
Peer databases are individual, independently developed data- bases that contain local data, but are also linked to each other through acquaintances for the purpose of sharing data. Many researchers have tackled the problem of query processing in P2P networks. Only recently have researchers started to exploit the idea of community-based querying in peer database networks. P2P communities are formed using common claimed attributes. We develop a community-based search algorithm for peer databases. The algorithm combines an existing community formation and discovery algorithm with an existing query translation mechanism for peer databases. We have implemented the algorithm and report on preliminary experiments.KeywordsQuery ProcessingMapping TableLink WeightQuery TranslationCommunity BoardThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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