Christos Tryfonopoulos

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This paper presents DIAS, a distributed alert service for digital libraries, currently under development in project DIET. We first discuss the models and languages for expressing user profiles and notifications. Then we present the data structures, algorithms and protocols that underly the peer-to-peer agent architecture of DIAS.
Information filtering, also referred to as publish/subscribe, complements one-time searching since users are able to subscribe to information sources and be notified whenever new documents of interest are published. In approximate information filtering only selected information sources, that are likely to publish documents relevant to the user interests in(More)
In the selective dissemination of information (or publish/subscribe) paradigm, clients subscribe to a server with continuous queries (or profiles) that express their information needs. Clients can also publish documents to servers. Whenever a document is published, the continuous queries satisfying this document are found and notifications are sent to(More)
We study the problem of selective dissemination of information in P2P networks. We present our work on data models and laiguages for textual information dissemination and discuss a relemnt P2P architecture that motivates our efforts. We also survey our results on the computational complexity of three related algorithmic problems (query satisfiability,(More)
We present MinervaDL, a digital library architecture that supports approximate information retrieval and filtering functionality under a single unifying framework. The architecture of MinervaDL is based on the peer-to-peer search engine Minerva, and is able to handle huge amounts of data provided by digital libraries in a distributed and self-organizing(More)
Most approaches to information filtering taken so far have the underlying hypothesis of potentially delivering notifications from every information producer to subscribers. This exact publish/subscribe model creates an efficiency and scalability bottleneck, and might not even be desirable in certain applications. The work presented here puts forward MAPS, a(More)
Today's content providers are naturally distributed and produce large amounts of new information every day. Peer-to-peer information filtering is a promising approach that offers scalability, adaptivity to high dynamics, and failure resilience. The authors developed two approaches that utilize the Chord distributed hash table as the routing substrate, but(More)