Content aggregation on knowledge bases using graph clustering
| dc.date.accessioned | 2009-04-20T09:35:48Z | |
| dc.date.available | 2009-04-20T09:35:48Z | |
| dc.date.issued | 2006 | |
| dc.identifier.uri | urn:nbn:de:hebis:34-2009042027014 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/2009042027014 | |
| dc.format.extent | 252842 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | eng | |
| dc.rights | Urheberrechtlich geschützt | |
| dc.rights.uri | https://rightsstatements.org/page/InC/1.0/ | |
| dc.subject.ddc | 004 | |
| dc.title | Content aggregation on knowledge bases using graph clustering | eng |
| dc.type | Preprint | |
| dcterms.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. | eng |
| dcterms.accessRights | open access | |
| dcterms.creator | Schmitz, Christoph | |
| dcterms.creator | Hotho, Andreas | |
| dcterms.creator | Jäschke, Robert | |
| dcterms.creator | Stumme, Gerd | |
| 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) | ger |
| dc.subject.swd | Wissensextraktion | ger |
| dc.subject.swd | Wissensmanagement | ger |
| dc.subject.swd | Ontologie <Wissensverarbeitung> | ger |
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