Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G. (2006),
Content Aggregation on Knowledge Bases using Graph Clustering, in
York Sure & John Domingue, ed.,
'The Semantic Web: Research and Applications'
, Springer, Heidelberg
, pp. 530-544
.
[BibTeX]
[Endnote]
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.
Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G. (2006),
Content Aggregation on Knowledge Bases using Graph Clustering, in
'Proceedings of the 3rd European Semantic Web Conference'
, Springer, Budva, Montenegro
, pp. 530-544
.
[BibTeX]
[Endnote]
Schmitz, C.; Hotho, A.; Jäschke, R. & Stumme, G. (2006),
Content Aggregation on Knowledge Bases using Graph Clustering, in
York Sure & John Domingue, ed.,
'The Semantic Web: Research and Applications'
, Springer, Heidelberg
, pp. 530-544
.
[BibTeX]
[Endnote]
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.