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Title: Knowledge discovery method based on analysis of multiple co-occurrences in collections of journal papers
Author: PANG Hongshen
Source: Chinese Journal of Library and Information Science
Issued Date: 2012-12-25
Volume: 5, Issue:4, Pages:9-20
Keyword: Multiple co-occurrences ; Visualization analysis ; Knowledge discovery ; Research fi eld analysis ; Embryonic stem cell
Subject: 编辑出版
Abstract:

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.

English Abstract:

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.

Related URLs: 查看原文
Content Type: 期刊论文
URI: http://ir.las.ac.cn/handle/12502/5658
Appears in Collections:Chinese Journal of Library and Information Science-2012_期刊论文

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Recommended Citation:
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.
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