Text Mining of Highly Cited Publications in Data Mining


Data mining is a very popular research area among researchers from various disciplines. Identification of patterns related with data mining research are very popular. The main objective of this study is to identify the main and subdisciplines of data mining research using text mining techniques. This paper analyzes the highly cited research publications in the field of data mining using text mining methods. Web of Science was used as the source database for extracting the data required for the study. The top 50 articles under Information Science Library Science research area were selected as the study sample of this research. The data were coded separately using titles and abstracts of selected articles. The main disciplines and further sub-disciplines were identified. Based on the categories, term-document matrix was created. The analysis revealed that the prominent research areas related with data mining are GIS, information and bibliometric analysis. Further, it was concluded that these results based on the mining of information from the highly cited publications will be useful for researchers and publishers for academic and indexing purposed.



Data Mining algorithms

Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL