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Cluster-based polyrepresentation as science modelling approach for information retrieval

  • Muhammad Kamran Abbasi
    ,
  • Ingo Frommholz
Research Output: Contribution to journal Article Peer-review

Abstract

The increasing number of publications make searching and accessing the produced literature a challenging task. A recent development in bibliographic databases is to use advanced information retrieval techniques in combination with bibliographic means like citations. In this work we will present an approach that combines a cognitive information retrieval framework based on the principle of polyrepresentation with document clustering to enable the user to explore a collection more interactively than by just examining a ranked result list. Our approach uses information need representations as well as different document representations including citations. To evaluate our ideas we employ a simulated user strategy utilising a cluster ranking approach. We report on the possible effectiveness of our approach and on several strategies how users can achieve a higher search effectiveness through cluster browsing. Our results confirm that our proposed polyrepresentative cluster browsing strategy can in principle significantly improve the search effectiveness. However, further evaluations including a more refined user simulation are needed.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 2301-2322

Journal (Volume, Issue Number)

Scientometrics (Volume 102, Issue 3)

Publication milestones

  • Published - 01/01/2015

Publication status

Published - 01/01/2015

ISSN

0138-9130

External Publication IDs

  • handle.net: 10547/333147
  • Scopus: 84925514086

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