Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

A Review on Bibliometric Analysis of Data Mining

Author : Ashutosh Upadhyay 1

Date of Publication :12th April 2018

Abstract: Alongside more and quicker amassing of electronic business information, Data Mining and the more up to date Big Data issues are pulling in more consideration. This paper reports the writing investigation dependent on the production diaries and articles in the examination databases. The positioning examinations of top 10 article includes in 2014 on Data Mining and Big Data show that there are 9 in like manner in the main 10 writer nations however just 2 in like manner in the best 10 writer associations. There are 6 in like manner in the main 10 research territories yet just 2 in like manner in the best 10 diary names. Notwithstanding, close to 1/3 creators adding to the Big Data writing originate from the pool of writers who have productions in the Data Mining subject. Ideally, their Big Data look into in the worth measurement may connect better to the Data Mining information and strategies.Right now, about data mining recorded by CSSCI (1998 ~ 2007) are gathered and broke down with measurable examination and bibliometric investigation, for example, year dissemination, diary appropriation, subject conveyance, the center creator and the topographical conveyance of the creator. So we can distinguish the center creator, center diaries, inquire about foundations and the law of research on information mining in the Chinese sociology circle, also, uncover the survey of information mining study and the fundamental subject in the Chinese sociology circle. In agreement, this paper demonstrates a few issues and patterns about examination on information mining.

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