%0 Conference Paper
%1 schmitz2006content
%A Schmitz, Christoph
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%B The Semantic Web: Research and Applications
%C Berlin/Heidelberg
%D 2006
%E Sure, York
%E Domingue, John
%I Springer
%K 2006 aggregation clustering graph iccs_example knowledge l3s myown trias_example
%P 530--544
%T Content Aggregation on Knowledge Bases using Graph Clustering
%U http://www.springerlink.com/content/u121v1827v286398/
%V 4011
%X 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.