Cluster-based polyrepresentation as science modelling approach for information retrieval

Muhammad Kamran Abbasi () and Ingo Frommholz ()
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Muhammad Kamran Abbasi: University of Bedfordshire
Ingo Frommholz: University of Bedfordshire

Scientometrics, 2015, vol. 102, issue 3, No 31, 2322 pages

Abstract: 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.

Keywords: Information retrieval; Polyrepresentation; Document clustering; Bibliometrics; Simulated user (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11192-014-1478-1

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