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Searching bibliographic data using graphs: A visual graph query interface

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  • Zhu, Yongjun
  • Yan, Erjia

Abstract

With the ever-increasing scientific literature, improving the efficiency of searching bibliographic data has become an important issue. With a lack of support of current bibliographic information retrieval systems in expressing complicated information needs, getting relevant bibliographic data is a demanding task. In this paper, we propose a visual graph query interface for bibliographic information retrieval. Through this interface, users can formulate bibliographic queries by interacting with a graph. Visual graph queries use a set of nodes with constraints and links among nodes to represent explicit and precise bibliographic information needs. The proposed visual graph query interface allows users to formulate several complex bibliographic queries (e.g., bibliographic coupling) that are not attainable in current major bibliographic information retrieval systems. In addition, the proposed interface requires less number of queries in completing everyday bibliographic search tasks.

Suggested Citation

  • Zhu, Yongjun & Yan, Erjia, 2016. "Searching bibliographic data using graphs: A visual graph query interface," Journal of Informetrics, Elsevier, vol. 10(4), pages 1092-1107.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:4:p:1092-1107
    DOI: 10.1016/j.joi.2016.09.005
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    1. Erjia Yan & Ying Ding, 2009. "Applying centrality measures to impact analysis: A coauthorship network analysis," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2107-2118, October.
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