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|Title:||Statistical Implicative Analysis Approximation to KDD and Data Mining: A Systematic and Mapping Review in Knowledge Discovery Database Framework|
|Authors:||Pazmiño-Maji, R. A.|
García-Peñalvo, F. J.
Conde-González, M. Á.
|Keywords:||Statistical Implicative Analysis|
Knowledge Discovery Database
|Publisher:||IARIA XPS Press|
|Citation:||Pazmiño-Maji, R., García-Peñalvo, F. J., & Conde-González, M. Á. (2017). Statistical Implicative Analysis Approximation to KDD and Data Mining: A Systematic and Mapping Review in Knowledge Discovery Database Framework. In A. Schmidt, F. Laux, D. Hristovski, & S. Ohnishi (Eds.), Proceedings of the Ninth International Conference on Advances in Databases, Knowledge, and Data Applications, DBKDA 2017, (May 21 - 25, 2017 - Barcelona, Spain) (pp. 70-77). Wilmington, DE, USA: IARIA XPS Press.|
|Abstract:||According to Scopus, only in the year 2016, there were 15747 scientific papers about data mining and KDD. These have been and remain useful technologies. In this paper, we determine the approximation level of SIA to KDD and Data Mining. To this end, we have created an approximation framework based on definition and step process proposed by Fayyad. We use mapping review and ystematic review from literature published in the last 5 years in bibliographic databases ACM, EBSCO, Google Scholar, IEEE, ProQuest, Scopus and WOS. We started with 200 papers and finally, 35 had all quality criteria. This paper also describes the SIA papers and identifies a series of future research in SIA, KDD and Data Mining.|
|Appears in Collections:||Publications|
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