ISKODOR integrates personal collections, peer search, and centralized search services. User modeling in ISKODOR fills three roles: discovery of sites with suitable information stores, context-based query interpretation, and automatic profile-based filtering of new information. Explanation and control are achieved through graphical depiction of sources, explicit feedback regard ingutility, and explicit control over peer association behavior and information sharing.

The Web provides a global platform for knowledge sharing. However, several shortcomings still arise from the absence of personalization and collaboration in Web searches. More effective retrieval techniques could be provided by means of transforming explicit knowledge into implicit knowledge. The approach presented in this paper is based on a peer-to-peer architecture and aims at complementing classical Web searches in terms of personalized ranking lists. These local rankings can be accumulated and evaluated in order to supplement the process of knowledge generation by building Virtual Knowledge Communities. Furthermore, the aggregation of ranking lists can be used to identify topics as well as communities of interest. Together with social aspects for community support, a framework for congenial Web search is defined.