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.
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Notes
Scientific Literature Digital Library, http://citeseer.ist.psu.edu.
Google search engine, for peer-reviewed scholarly literature, http://scholar.google.com.
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Acknowledgments
This research is supported by National Natural Science Foundation of China (grant number 61272370), the specialized research fund for doctoral tutor (20110041110034), and the Fundamental Research Funds for the Central Universities. Part of the research was conducted during Shengbo Liu’s visiting doctoral studentship at the iSchool at Drexel University.
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Liu, S., Chen, C., Ding, K. et al. Literature retrieval based on citation context. Scientometrics 101, 1293–1307 (2014). https://doi.org/10.1007/s11192-014-1233-7
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DOI: https://doi.org/10.1007/s11192-014-1233-7