purpose: this paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles. design/methodology/approach: a variety of methods such as the model construction, system analysis and experiments are used. the author has improved morris' crossmapping technique and developed a technique for directly describing, visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles. findings: the visualization tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. it can reveal more and in-depth information than analyzing co-occurrence relations between two entities. therefore, this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way. research limitations: the technique could only be used to analyze co-occurrence relations of less than three entities at present. practical implications: this research has expanded the study scope of co-occurrence analysis. the research result has provided a theoretical support for co-occurrence analysis. originality/value: there has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. this research defines multiple co-occurrence and the research scope, develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.
英文摘要
purpose: this paper explores a method of knowledge discovery by visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles. design/methodology/approach: a variety of methods such as the model construction, system analysis and experiments are used. the author has improved morris' crossmapping technique and developed a technique for directly describing, visualizing and analyzing co-occurrence relations among three or more entities in collections of journal articles. findings: the visualization tools and the knowledge discovery method can efficiently reveal the multiple co-occurrence relations among three entities in collections of journal papers. it can reveal more and in-depth information than analyzing co-occurrence relations between two entities. therefore, this method can be used for mapping knowledge domain that is manifested in association with the entities from multi-dimensional perspectives and in an all-round way. research limitations: the technique could only be used to analyze co-occurrence relations of less than three entities at present. practical implications: this research has expanded the study scope of co-occurrence analysis. the research result has provided a theoretical support for co-occurrence analysis. originality/value: there has not been a systematic study on co-occurrence relations among multiple entities in collections of journal articles. this research defines multiple co-occurrence and the research scope, develops the visualization analysis tool and designs the analysis model of the knowledge discovery method.
PANG Hongshen. Knowledge discovery method based on analysis of multiple co-occurrences in collections of journal papers[J]. chinese journal of library and information science,2012,5(4):9-20.
APA
PANG Hongshen.(2012).Knowledge discovery method based on analysis of multiple co-occurrences in collections of journal papers.chinese journal of library and information science,5(4),9-20.
MLA
PANG Hongshen."Knowledge discovery method based on analysis of multiple co-occurrences in collections of journal papers".chinese journal of library and information science 5.4(2012):9-20.
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