Intelligent retrieval of hypermedia documents

Authors:
Mounia Lalmas;Thomas Rölleke;Norbert Fuhr
Affiliations:
Department of Computer Science, Queen Mary, University of London, London E1 4NS, England;Department of Computer Science, Queen Mary, University of London, London E1 4NS, England and HySpirit GmbH, Postfach 30 02 58, 44232 Dortmund, Germany;Informatik VI, University of Dortmund, 44221 Dortmund, Germany
Venue:
Intelligent exploration of the web
Year:
2003

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Abstract

Intelligent retrieval of hypermedia documents requires sophisticated document representations and querying facilities that allow for content-based and fact-based querying as well as considering the structure of documents. This paper describes POOL, a Probabilistic Object-Oriented four-valued Logic, which allows a uniform view on hypermedia documents for the purpose of their retrieval: documents, images, authors, dates, etc. are treated as objects and POOL models the content of objects, the facts about objects, and the structure of objects to provide for a relevance-based ranking of hypermedia documents.