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Exploiting citation overlaps for Information Retrieval: Generating a boomerang effect from the network of scientific papers

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  • Birger Larsen

    (Royal School of Library and Information Science)

Abstract

A new citation search strategy is proposed for Information Retrieval (IR) based on the principle of polyrepresentation (Ingwersen, 1992, 1996). The strategy exploits logical overlaps between a range of cognitively different interpretations of the same documents in a structured manner, i.e. so-called cognitive overlaps of representations. The strategy is essentially a "cycling strategy" starting with documents retrieved by a subject search, wherefrom new documents are identified automatically by following the network of citations in scientific papers backwards and forwards in time. In contrast to earlier citation search strategies the proposed strategy does not require known relevant documents (seed documents) as a starting point, but may be based on a subject search. A pilot study is reported where the ability of the strategy to retrieve additional relevant documents is analysed. Results show that a very large amount of documents can be retrieved by the strategy, and that these may be segmented in a number of distinct "overlap levels". It is demonstrated that the combined core of the higher-level overlaps contains higher relevance density than found in the original retrieval results. Based on these results it is suggested that the documents be displayed in order of their presence in higher-level overlaps, so as to maximise the chances that as many relevant documents as possible will be presented first to a user.

Suggested Citation

  • Birger Larsen, 2002. "Exploiting citation overlaps for Information Retrieval: Generating a boomerang effect from the network of scientific papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 155-178, June.
    • Handle: RePEc:spr:scient:v:54:y:2002:i:2:d:10.1023_a:1016011326300
    DOI: 10.1023/A:1016011326300
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    References listed on IDEAS

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    Cited by:

    1. Yuandi Wang & Xiongfeng Pan & Yantai Chen & Xin Gu, 2013. "Do references in transferred patent documents signal learning opportunities for the receiving firms?," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 731-752, May.
    2. Muhammad Kamran Abbasi & Ingo Frommholz, 2015. "Cluster-based polyrepresentation as science modelling approach for information retrieval," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2301-2322, March.
    3. Christopher W. Belter, 2017. "A relevance ranking method for citation-based search results," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 731-746, August.
    4. van Eck, Nees Jan & Waltman, Ludo, 2014. "CitNetExplorer: A new software tool for analyzing and visualizing citation networks," Journal of Informetrics, Elsevier, vol. 8(4), pages 802-823.
    5. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    6. Mikkel Christoffersen, 2004. "Identifying core documents with a multiple evidence relevance filter," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(3), pages 385-394, November.
    7. Michel Zitt, 2015. "Meso-level retrieval: IR-bibliometrics interplay and hybrid citation-words methods in scientific fields delineation," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2223-2245, March.

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