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Tag-Based Paper Retrieval: Minimizing User Effort with Diversity Awareness

  • Quoc Viet Hung NguyenEmail author
  • Son Thanh Do
  • Thanh Tam Nguyen
  • Karl Aberer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9049)

Abstract

As the number of scientific papers getting published is likely to soar, most of modern paper management systems (e.g. ScienceWise, Mendeley, CiteULike) support tag-based retrieval. In that, each paper is associated with a set of tags, allowing user to search for relevant papers by formulating tag-based queries against the system. One of the most critical issues in tag-based retrieval is that user often has difficulties in precisely formulating his information need. Addressing this issue, our paper tackles the problem of automatically suggesting new tags for user when he formulates a query. The set of tags are selected in such a way that resolves query ambiguity in two aspects: informativeness and diversity. While the former reduces user effort in finding the desired papers, the latter enhances the variety of information shown to user. Through studying theoretical properties of this problem, we propose a heuristic-based algorithm with several salient performance guarantees. We also demonstrate the efficiency of our approach through extensive experimentation using real-world datasets.

Keywords

Ranking Score User Query Query Suggestion Query Size Domain Coverage 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Quoc Viet Hung Nguyen
    • 1
    Email author
  • Son Thanh Do
    • 1
  • Thanh Tam Nguyen
    • 1
  • Karl Aberer
    • 1
  1. 1.École Polytechnique Fédérale de LausanneLausanneSwitzerland

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