Four-valued knowledge augmentation for structured document retrieval

  • Authors:
  • M. Lalmas;T. Rolleke

  • Affiliations:
  • Department of Computer Science, Queen Mary University of London, United Kingdom;Department of Computer Science, Queen Mary University of London, United Kingdom

  • Venue:
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
  • Year:
  • 2003
  • XML fuzzy ranking

    FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems

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Abstract

Structured documents are composed of objects with a content and a logical structure. The effective retrieval of structured documents requires models that provide for a content-based retrieval of objects that takes into account their logical structure, so that the relevance of an object is not solely based on its content, but also on the logical structure among objects. This paper proposes a formal model for representing structured documents where the content of an object is viewed as the knowledge contained in that object, and the logical structure among objects is capture by a process of knowledge augmentation: the knowledge contained in an object is augmented with that of its structurally related objects. The knowledge augmentation process takes into account the fact that knowledge can be incomplete and become inconsistent.