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style="color:#555555;">Susanne <a href="http://www.bibsonomy.org/author/Prediger">Prediger</a> and Rudolf <a href="http://www.bibsonomy.org/author/Wille">Wille</a> </span><em>ICCS, </em><em>volume1640ofLecture Notes in Computer Science, </em><em>page401-414. </em><em>Springer, </em>(<em>1999</em>)Wed Sep 05 15:58:00 CEST 2007ICCSconf/iccs/1999401-414Lecture Notes in Computer ScienceThe Lattice of Concept Graphs of a Relationally Scaled Context16401999graph concept fca formal cg analysis graphs http://www.bibsonomy.org/bibtex/2069db3a0aad592c82f35e1bbf701824f/stummestumme2006-09-20T20:08:31+02:00formal concept drawing 1995 fca graph analysis myown lattices <span style="color:#555555;">Gerd <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> and Rudolf <a href="http://www.bibsonomy.org/author/Wille">Wille</a> </span><em>Graph Drawing, </em><em>volume894ofLNCS, </em><em>page452-459. </em><em>Heidelberg, </em><em>Springer, </em>(<em>1995</em>)Wed Sep 20 20:08:31 CEST 2006HeidelbergGraph Drawing452-459LNCSA Geometrical Heuristic for Drawing Concept Lattices8941995formal concept drawing 1995 fca graph analysis myown lattices http://www.bibsonomy.org/bibtex/2eb6e678cba7f48ae8604d59542cd79c6/stummestumme2006-09-20T19:08:41+02:00myown toscana graphs cg conceptual iccs graph fca 2000 analysis concept formal cgs <span style="color:#555555;">P. <a href="http://www.bibsonomy.org/author/Eklund">Eklund</a> and B. <a href="http://www.bibsonomy.org/author/Groh">Groh</a> and G. <a href="http://www.bibsonomy.org/author/Stumme">Stumme</a> and R. <a href="http://www.bibsonomy.org/author/Wille">Wille</a> </span><em>Conceptual Structures: Logical, Linguistic, and Computational, </em><em>volume1867ofLNAI, </em><em>page453-467. </em><em>Heidelberg, </em><em>Springer, </em>(<em>2000</em>)Wed Sep 20 19:08:41 CEST 2006HeidelbergConceptual Structures: Logical, Linguistic, and Computational453-467LNAIContextual-Logic Extension of TOSCANA.18672000myown toscana graphs cg 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ontology 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 provides a graph clustering technique 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.