HySpirit — A probabilistic inference engine for hypermedia retrieval in large databases

  • Norbert Fuhr
  • Thomas Rölleke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1377)


HySpirit is a retrieval engine for hypermedia retrieval integrating concepts from information retrieval (IR) and deductive databases. The logical view on IR models retrieval as uncertain inference, for which we use probabilistic reasoning. Since the expressiveness of classical IR models is not sufficient for hypermedia retrieval, HySpirit is based on a probabilistic version of Datalog. In hypermedia retrieval, different nodes may contain contradictory information; thus, we introduce probabilistic four-valued Datalog. In order to support fact queries as well as content-based retrieval, HySpirit is based on an open world assumption, but allows for predicate-specific closed world assumptions. For performing efficient retrieval on large databases, our system provides access to external data. We demonstrate the application of HySpirit by giving examples for retrieval on images, structured documents and large databases.


Query Language Query Term Probabilistic Inference Deductive Database Minimum Bound Rectangle 
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 1998

Authors and Affiliations

  • Norbert Fuhr
    • 1
  • Thomas Rölleke
    • 1
  1. 1.Informatik 6University of DortmundDortmundGermany

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