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Please use this identifier to cite or link to this item: http://nbn-resolving.de/urn:nbn:de:hebis:34-2009042027014

Title: Content aggregation on knowledge bases using graph clustering
Authors: Schmitz, ChristophHotho, AndreasJäschke, RobertStumme, Gerd
???metadata.dc.subject.swd???: WissensextraktionWissensmanagementOntologie <Wissensverarbeitung>
???metadata.dc.subject.ddc???: 004 - Informatik (Data processing Computer science)
Issue Date: 2006
Abstract: Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.
URI: urn:nbn:de:hebis:34-2009042027014
???metadata.dc.description.everything???: Auch erschienen in: Sure, York u.a. (Hrsg.): The semantic web. (Lecture notes in computer science ; 4011). Berlin u.a. : Springer, 2006. S. 530-544. ISBN 3-540-34544-2 = 978-3-540-34544-2 (The original publication is available at www.springerlink.com)
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