Literature retrieval based on citation context

被引:56
作者
Liu, Shengbo [1 ]
Chen, Chaomei [2 ]
Ding, Kun [1 ,3 ]
Wang, Bo [1 ]
Xu, Kan
Lin, Yuan [3 ]
机构
[1] Dalian Univ Technol, WISElab, Dalian 116024, Peoples R China
[2] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA
[3] Dalian Univ Technol, Informat Retrieval Lab, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Literature retrieval; Citation context; Tag cloud; Citation context classification; COMPUTER RECOGNITION; CITING STATEMENTS; COCITATION;
D O I
10.1007/s11192-014-1233-7
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
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.
引用
收藏
页码:1293 / 1307
页数:15
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