Towards Content Aggregation on Knowledge Bases through Graph Clustering
17. Workshop "Grundlagen von Datenbanken", (May 2005)Abstract
Recently, several research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which have been targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary for participants to provide brief descriptions of themselves, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peer a given query should be forwarded. In this talk, I propose the use of graph clustering techniques on knowledge bases for that purpose. After a brief round-trip over an ontology-based P2P knowledge management scenario, I will demonstrate the automatic generation of self-descriptions of peers’ knowledge bases through the use of graph clustering. Viewing the knowledge base of a peer as a graph consisting of concepts and instances, one can employ clustering techniques to partition it into clusters of similar entities. From each cluster, the centroid can then be selected as a re presentative. This yields a list of entities giving an aggregated self description of the peer.
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