Literature retrieval based on citation context

Shengbo Liu (), Chaomei Chen (), Kun Ding (), Bo Wang (), Kan Xu () and Yuan Lin ()
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Shengbo Liu: Dalian University of Technology
Chaomei Chen: Drexel University
Kun Ding: Dalian University of Technology
Bo Wang: Dalian University of Technology
Kan Xu: Dalian University of Technology
Yuan Lin: Dalian University of Technology

Scientometrics, 2014, vol. 101, issue 2, No 23, 1293-1307

Abstract: Abstract While the citation context of a reference may provide detailed and direct information about the nature of a citation, few studies have specifically addressed the role of this information in retrieving relevant documents from the literature primarily due to the lack of full text databases. In this paper, we design a retrieval system based on full texts in the PubMed Central database. We constructed two modules in the retrieval system. One is a reference retrieval module based on citation contexts. Another is a citation context retrieval module for searching the citation contexts of a specific paper. The results of comparisons show that the reference retrieval module performed better than Google Scholar and PubMed database in terms of finding proper references based on topic words extracted from citation context. It also performed very well on searching highly cited papers and classic papers. The citation context retrieval module visualizes the topics of citation contexts as tag clouds and classifies citation contexts based on cue words in citation contexts.

Keywords: Literature retrieval; Citation context; Tag cloud; Citation context classification (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s11192-014-1233-7

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