Annotation-based Document Retrieval with Probabilistic Logics

  • Citation-Key:
    Frommholz:07
  • Title:
    Annotation-based Document Retrieval with Probabilistic Logics
  • Author(s):
    Ingo Frommholz
  • In:
    • Citation-Key:
      ECDL:07
    • Title:
      Research and Advanced Technology for Digital Libraries. Proc. of the 11th European Conference on Digital Libraries (ECDL 2007)
    • Editor(s):
      Norbert Fuhr
      Laszlo Kovacs
      Carlo Meghini
    • Publisher:
      Springer
    • In:
      Research and Advanced Technology for Digital Libraries. Proc. of the 11th European Conference on Digital Libraries (ECDL 2007)
    • Year:
      2007
  • Page(s):
    321--332

Abstract:


Annotations are an important part in today's digital libraries and Web information systems as an instrument for interactive knowledge creation. Annotation-based document retrieval aims at exploiting annotations as a rich source of evidence for document search. The POLAR framework supports annotation-based document search by translating POLAR programs into four-valued probabilistic datalog and applying a retrieval strategy called knowledge augmentation, where the content of a document is augmented with the content of its attached annotations. In order to evaluate this approach and POLAR's performance in document search, we set up a test collection based on a snapshot of ZDNet News, containing IT-related articles and attached discussion threads. Our evaluation shows that knowledge augmentation has the potential to increase retrieval effectiveness when applied in a moderate way.

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