Abstract. Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments we show how expertise based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages. 1

The Bibster system is an application of the use of semantics in Peer-to-Peer systems, which is aimed at researchers that share bibliographic metadata. In this paper we describe the design and implementation of recommender functionality in the Bibster system which allows personalized access to the bibliographic metadata available in the Peer-to-Peer network. These functions are based on a semantic user profile which is created from content and usage information as well as a similarity function. Furthermore, these functions make use of the semantic topology of the Peer-to-Peer system.

Requirements for widely distributed information systems supporting virtual organizations have given rise to a new category of peer-to-peer (p2p) systems called schema-based. In such systems each peer is a database management system in itself, exposing its own schema. In such a setting, a main objective is the efficient search across peer databases by processing each incoming query without overly consuming bandwidth. In this report, we adopt a super-peer-based architecture and suggest a query routing mechanism, upon which we propose a query processing technique for top-k queries. Top-k queries in the context of p2p systems give the opportunity to filter the results and to eliminate network traffic by choosing the k highest ranked results. We introduce HT-p2p and HT-p2p+, two extended versions of the Hybrid Threshold Algorithm adapted to our p2p scenario. For the evaluation of these algorithms we implemented a prototype system upon the JXTA platform. Extensive experiments with different data sets and parameters have shown promising results about the performance of the query processing strategy. ± Acknowledgement: Special thanks to Evi Dagalaki for her contribution to the evaluation process. 1

This paper reviews the popular methodologies in integrating metadata records in distributed digital libraries environment. Each of these solutions does meet some of the requirements of distributed library services somehow, but still some issues need further study, such as limitation on the capacity of collections, retrieval of content-related records built in different metadata formats. In order to alleviate the problem, a novel super-peer based infrastructure for integrating metadata records in distributed and heterogeneous environment is introduced with respect to three situations, namely, sharing a common schema; in different schemata but in same community; in different schema and community. This paper sequentially describes feasible solutions according to these scenarios before coming to the conclusion. 1