2016 · 39 citations · 9 references
EducationComputer ScienceHigher EducationData AnalyticsData MiningEducational Data MiningAdmissions AnalyticsAdmissions ManagementAssessment AnalyticsStudent Success AnalyticsAcademic Performance BenchmarkingAdmission RankingCluster AnalysisCluster Analysis For GroupingClusteringClustering AnalysisStudent Performance AnalysisStudent Performance Data Analysis
University and technical organizations are facing high competition and their challenge is in analyzing their performance. The major challenges are in admission, student placement and in the curriculum. The two most important process during which data's are collected and analyzed are admission and placement. The ranking of the university depends on academic performance and placement of the student. Apart from academic performance there are various other factors which help in understanding the overall performance of the student. In this research work, the data mining technique is used to understand the performance of student and group the students under various categories as a student need to consistently improve to compete in today's world.
9
Fast and Accurate k-means For Large Datasets
Michael Shindler, Alex Wong, Adam Meyerson · 2011 · 136 citations