%0 
%0 Conference Proceedings
%A Schmitz, Christoph; Hotho, Andreas; Jäschke, Robert & Stumme, Gerd
%D 2006
%T Content Aggregation on Knowledge Bases using Graph Clustering
%E Sure, York & Domingue, John
%B The Semantic Web: Research and Applications
%C Berlin/Heidelberg
%I Springer
%V 4011
%6
%N 
%P 530--544
%& 
%Y 
%S Lecture Notes in Computer Science
%7
%8 June
%9
%? 
%! 
%Z 
%@ 978-3-540-34544-2
%(
%)
%*
%L
%M
%1 
%2 
%3 inproceedings
%4 
%# 
%$ 
%F schmitz2006content
%K 2006, aggregation, clustering, graph, iccs_example, knowledge, l3s, myown, trias_example
%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.
%Z 
%U http://www.springerlink.com/content/u121v1827v286398/
%+
%^