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New Technology of Library and Information Service  2016, Vol. 32 Issue (7-8): 87-93    DOI: 10.11925/infotech.1003-3513.2016.07.11
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Finding Semantic Relations Among Subject Indexed Papers
Li Xiaoying(),Xia Guanghui,Li Danya
Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China
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[Objective] This paper tries to identify important and implicit semantic relations among the subject indexed papers. [Methods] Based on the subject indexed biomedical papers from MEDLINE, we proposed an algorithm consisting of subjects coordinating and indexing rules, as well as optimization rules for weighted indexing results and relation occurrences. The new algorithm was then examined with experimental disease data. [Results] With the help of domain experts’ verification, the precision of the new algorithm was higher than 95%. [Limitations] The proposed method was only appropriate for papers with subject indexing. [Conclusions] The proposed algorithm can be used to identify semantic relations among English and Chinese subjects indexed biomedical papers, and help us develop algorithms in other areas.

Key wordsFinding semantic relations      Indexed papers      Coordinating rules      Threshold     
Received: 09 March 2016      Published: 29 September 2016

Cite this article:

Li Xiaoying,Xia Guanghui,Li Danya. Finding Semantic Relations Among Subject Indexed Papers. New Technology of Library and Information Service, 2016, 32(7-8): 87-93.

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