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Elements of a Learning Interface for Genre Qualified Search

  • Andrea Stubbe
  • Christoph Ringlstetter
  • Randy Goebel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4830)

Abstract

Even prior to content, the genre of a web document leads to a first coarse binary classification of the recall space in relevant and non-relevant documents. Thinking of a genre search engine, massive data will be available via explicit or implicit user feedback. These data can be used to improve and to customize the underlying classifiers. A taxonomy of user behaviors is applied to model different scenarios of information gain. Elements of such a learning interface, as for example the implications of the lingering time and the snippet genre recognition factor, are discussed.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrea Stubbe
    • 1
  • Christoph Ringlstetter
    • 2
  • Randy Goebel
    • 2
  1. 1.CIS, University of Munich 
  2. 2.AICML, University of Alberta 

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