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.

We provide a new method for systematically structuring the top-down level of ontologies.
is based on an interactive, top--down knowledge acquisition
ocess, which assures that the knowledge engineer
nsiders all possible cases while avoiding redundant acquisition.
e method is suited especially for creating/merging the top
rt(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.

Topics in education are changing with an ever faster pace. E-Learning
sources tend to be more and more decentralised. Users need increasingly to be able to
e the resources of the web. For this, they should have tools for finding and organizing
formation in a decentral way. In this, paper, we show how an ontology-based tool
ite allows to make the most of the resources available on the web.