Content Aggregation on Knowledge Bases using Graph Clustering.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 530-544.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.
Content Aggregation on Knowledge Bases using Graph Clustering.
In:
Proceedings of the 3rd European Semantic Web Conference, volume 4011, series LNCS, pages 530-544.
Springer, Budva, Montenegro, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[doi]
[BibTeX]
Content Aggregation on Knowledge Bases using Graph Clustering.
In: Y. Sure and J. Domingue, editors,
The Semantic Web: Research and Applications, volume 4011, series LNAI, pages 530-544.
Springer, Heidelberg, 2006.
Christoph Schmitz, Andreas Hotho, Robert Jäschke and Gerd Stumme.
[doi]
[abstract]
[BibTeX]
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.