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.
%0 Conference Paper
%1 SchmitzHotho:ESWC06
%A Schmitz, Christoph
%A Hotho, Andreas
%A Jäschke, Robert
%A Stumme, Gerd
%B European Semantic Web Conference, Budva, Montenegro, 11-14.06.06
%D 2006
%K 2006 nepomuk
%T Content Aggregation on Knowledge Bases using Graph Clustering
%U http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf
%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.
@inproceedings{SchmitzHotho:ESWC06,
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 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.
},
added-at = {2006-10-04T09:44:49.000+0200},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/215be3c9ac8941fc235acf59fcb31bc4d/markusjunker},
booktitle = {European Semantic Web Conference, Budva, Montenegro, 11-14.06.06},
interhash = {d2ddbb8f90cd271dc18670e4c940ccfb},
intrahash = {15be3c9ac8941fc235acf59fcb31bc4d},
keywords = {2006 nepomuk},
timestamp = {2006-10-04T09:44:49.000+0200},
title = {Content Aggregation on Knowledge Bases using Graph Clustering},
url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf},
year = 2006
}