On Semantically-Augmented XML-Based P2P Information Systems

  • Alfredo Cuzzocrea
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4027)


Knowledge representation and extraction techniques can be efficiently used to improve data modeling and IR functionalities of P2P Information Systems, which have recently attracted a lot of attention from industrial and academic researchers. These functionalities can be achieved by pushing semantics in both data and queries, and exploiting the derived expressiveness to improve file sharing primitives and lookup mechanisms made available from first-generation P2P systems. XML-based P2P Information Systems are a more specific and interesting instance of this class of systems, where the overall data domain is composed by very large, Internet-like distributed XML repositories from which users extract useful knowledge manly by means of IR methodologies implemented on the top of XML join queries. This paper focuses on several aspects of XML-based P2P Information Systems, raging from foundations and definitions to knowledge representation and extraction models and algorithms, along with their experimental evaluation. However, the results presented in this paper can also be adapted to deal with any kind of data format (e.g., HTML).


Knowledge Representation Resource Description Framework Knowledge Extraction Breadth First Search Neighboring Peer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alfredo Cuzzocrea
    • 1
  1. 1.Department of Electronics, Computer Science, and SystemsUniversity of CalabriaItaly

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