Study on Hotspots Detection Based on CSSCI Academic Resource Ontology
Cross relation and its blending degree among academic resource would be revealed through association analysis of academic resource from CSSCI. So, this paper tries to change the traditional analysis mode that using association rule mining to gain the subject relationship based on single standard, and introduces the ontology mechanism with semantic description capabilities into the knowledge organization of CSSCI academic resource for organizing all kinds of academic concepts by object-oriented approach, so that to establishes CSSCI Academic Resource Networks Model based on Ontology. On this basis, knowledge mining technique will also be adopted to detect the research hotspots of disciplines from the perspectives of high-frequency themes and themes from influential entity in disciplines, to discover the interdisciplinary hotspots so as to promote the exchange of interdisciplinary and to clear the specific direction of interdisciplinary cooperation. Upon that, all kinds of analysis conclusions and scientific laws which have academic value and could generate academic influence would be obtained to support the decision for scientific evaluation.
Zhihua Xu, Gang Shen and Sally Lin
H. Wang et al., "Study on Hotspots Detection Based on CSSCI Academic Resource Ontology", Advanced Materials Research, Vols. 171-172, pp. 19-26, 2011