A STUDY OF SUBJECT OVERLAP BETWEEN THE MAIN CATEGORIES OF KNOWLEDGE MANAGEMENT WITHIN THE WEB OF SCIENCE

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HAZERI AFSANEH; TAVAKOLIZADEH RAVARI MOHAMMAD; EBRAHIMI VAJIHE

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Journal: Iranian Journal of Information Processing & Management Year:2015 | Volume:30 | Issue:4 Page(s): 997-1023

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Title

A STUDY OF SUBJECT OVERLAP BETWEEN THE MAIN CATEGORIES OF KNOWLEDGE MANAGEMENT WITHIN THE WEB OF SCIENCE

Author(s)

HAZERI AFSANEH | TAVAKOLIZADEH RAVARI MOHAMMAD | EBRAHIMI VAJIHE | Issue Writer Certificate

Keywords

KNOWLEDGE MANAGEMENTQ2

CLUSTERINGQ1

KEYWORDS COQ2

OCCURRENCEQ2

SUBJECT OVERLAPQ2

INCLUSION INDEXQ2

Abstract

Although a relatively new discipline, KNOWLEDGE MANAGEMENT (KM) is an area with a wide range of theoretical concepts and practical implications. The applicability of KM in different environments, and the vast value and benefits of its application, have led to great developments within the discipline over the last few years. The interdisciplinary nature of KM has also provided the opportunity for contributions by people from different disciplines, which in turn has lead to the rapid advancement of KM boundaries. This paper aims to examine the subject structure of the KM discipline through keyword analysis of documents in the Web of Science, using a hierarchical CLUSTERING approach and an INCLUSION INDEX. Within the Web of Science categories, according to the findings, the three categories of “Management”, “Computer Science Information Systems” and “Information Science Library Science” claim the highest number of documents in this area. Of 5570 author keywords, 96 keywords are identified as “highly used” keywords. Three hierarchical clusters (dendrograms) are formed from co-occurrence analysis of highly used keywords in the three categories. A comparison of these denrograms indicates that six clusters, including a total of 16 keywords, are common in the three categories. Looking at clusters of the three categories revealed that two categories - Management and Information Science Library Science - have 14 common/shared clusters, and therefore the highest degree of similarities. However, the category of Computer Science Information Systems, with 28 unique clusters, differs most markedly from the other two categories. To investigate the rate of common keywords from one category to another, the INCLUSION INDEX is calculated. Results of this exercise indicate that the category of Information Science Library Science has the highest number of common keywords.

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APA: Copy

TAVAKOLIZADEH RAVARI, MOHAMMAD, & EBRAHIMI, VAJIHE. (2015). A STUDY OF SUBJECT OVERLAP BETWEEN THE MAIN CATEGORIES OF KNOWLEDGE MANAGEMENT WITHIN THE WEB OF SCIENCE. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), 30(4), 997-1023. SID. https://sid.ir/paper/131017/en

Vancouver: Copy

TAVAKOLIZADEH RAVARI MOHAMMAD, EBRAHIMI VAJIHE. A STUDY OF SUBJECT OVERLAP BETWEEN THE MAIN CATEGORIES OF KNOWLEDGE MANAGEMENT WITHIN THE WEB OF SCIENCE. IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY)[Internet]. 2015;30(4):997-1023. Available from: https://sid.ir/paper/131017/en

IEEE: Copy

MOHAMMAD TAVAKOLIZADEH RAVARI, and VAJIHE EBRAHIMI, “A STUDY OF SUBJECT OVERLAP BETWEEN THE MAIN CATEGORIES OF KNOWLEDGE MANAGEMENT WITHIN THE WEB OF SCIENCE,” IRANIAN JOURNAL OF INFORMATION PROCESSING & MANAGEMENT (INFORMATION SCIENCES AND TECHNOLOGY), vol. 30, no. 4, pp. 997–1023, 2015, [Online]. Available: https://sid.ir/paper/131017/en

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