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.
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Schmitz, C., Hotho, A., Jäschke, R., Stumme, G. (2006). Content Aggregation on Knowledge Bases Using Graph Clustering. In: Sure, Y., Domingue, J. (eds) The Semantic Web: Research and Applications. ESWC 2006. Lecture Notes in Computer Science, vol 4011. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11762256_39
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