Content Aggregation on Knowledge Bases using Graph Clustering
C. Schmitz, A. Hotho, R. Jäschke, and G. Stumme. The Semantic Web: Research and Applications, volume 4011 of LNAI, page 530-544. Heidelberg, Springer, (2006)
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.
%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 Heidelberg
%D 2006
%E Sure, York
%E Domingue, John
%I Springer
%K 2006 aggregation clustering content graph itegpub l3s myown nepomuk ontologies ontology seminar2006 theory
%P 530-544
%T Content Aggregation on Knowledge Bases using Graph Clustering
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006content.pdf
%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.
@inproceedings{schmitz2006content,
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 = {2006-09-20T18:23:30.000+0200},
address = {Heidelberg},
author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
biburl = {https://www.bibsonomy.org/bibtex/21788c88e04112a4491f19dfffb8dc39e/stumme},
booktitle = {The Semantic Web: Research and Applications},
editor = {Sure, York and Domingue, John},
interhash = {d2ddbb8f90cd271dc18670e4c940ccfb},
intrahash = {1788c88e04112a4491f19dfffb8dc39e},
keywords = {2006 aggregation clustering content graph itegpub l3s myown nepomuk ontologies ontology seminar2006 theory},
pages = {530-544},
publisher = {Springer},
series = {LNAI},
timestamp = {2009-03-18T10:03:02.000+0100},
title = {Content Aggregation on Knowledge Bases using Graph Clustering},
url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006content.pdf},
volume = 4011,
year = 2006
}