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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Schmitz, C., Hotho, A., Jäschke, R., & Stumme, G. (2006). Content aggregation on knowledge bases using graph clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4011 LNCS, pp. 530–544). Springer Verlag. https://doi.org/10.1007/11762256_39
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