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Evaluation of Relevance and Knowledge Augmentation in Discussion Search

  • Ingo Frommholz
  • Norbert Fuhr
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4172)

Abstract

Annotation-based discussions are an important concept for today’s digital libraries and those of the future, containing additional information to and about the content managed in the digital library. To gain access to this valuable information, discussion search is concerned with retrieving relevant annotations and comments w.r.t. a given query, making it an important means to satisfy users’ information needs. Discussion search methods can make use of a variety of context information given by the structure of discussion threads. In this paper, we present and evaluate discussion search approaches which exploit quotations in different roles as highlight and context quotations, applying two different strategies, knowledge and relevance augmentation. Evaluation shows the suitability of these augmentation strategies for the task at hand; especially knowledge augmentation using both highlight and context quotations boosts retrieval effectiveness w.r.t. the given baseline.

Keywords

Digital Library Query Term Email Message Access Probability Retrieval Status 
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 2006

Authors and Affiliations

  • Ingo Frommholz
    • 1
  • Norbert Fuhr
    • 1
  1. 1.University of Duisburg-EssenDuisburgGermany

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