Authors:
Vasile Paul Breşfelean
1
;
Mihaela Breşfelean
1
;
Nicolae Ghişoiu
1
and
Călin-Adrian Comes
2
Affiliations:
1
Babeş-Bolyai University, Faculty of Economics and Business Administration, Romania
;
2
Petru Maior University, Romania
Keyword(s):
Cluster, data clustering, K-means algorithm, students, analysis, percentage relation.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
In the present paper the authors exemplify the connections among the undergraduate studies, continuing education and professional enhancement on the foundations required by Romania’s integration in EU’s structures. The study was directed to the senior undergraduate students and master degree students from the Faculty of Economics and Business Administration, Babeş-Bolyai University of Cluj-Napoca, using questionnaires in a collaborative approach, and processing the collected data by data mining clustering techniques, graphical and percentage representations, through Weka’s implemented algorithms.