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论文类型： 期刊论文

发表时间： 2014-11-01

发表刊物： 14th International-Society-of-Scientometrics-and-Informetrics Conference (ISSI)

收录刊物： SCIE、CPCI-S、CPCI-SSH、SSCI、Scopus

卷号： 101

期号： 2

页面范围： 1293-1307

ISSN号： 0138-9130

关键字： Literature retrieval; Citation context; Tag cloud; Citation context classification

摘要： 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.