Affiliation:
1. VIT University, Chennai, India
Abstract
Data mining techniques are widely used for various educational researches. This article depicts the survey of various data mining techniques and tools which are used to guide students, course instructors, course developers, course administrators and organizations in respective fields based on future scope. This article also highlights how recommender systems rule the educational field though it's filtering mechanisms in recommending courses for students. It also illustrates future scope of data mining in educational needs.
Subject
Computer Science Applications
Reference44 articles.
1. Carlsson, G., Mémoli, F., Ribeiro, A., & Segarra, S. (2017). Admissible Hierarchical Clustering Methods and Algorithms for Asymmetric Networks. IEEE Transactions on Signal and Information Processing overNetworks.
2. Ranking of Influencing Factors in Predicting Students’ Academic Performance
3. Fast algorithms for mining association rules.;R.Agrawal;Proc. 20th int. conf. very large data bases,1994
4. Students performance prediction using KNN and Naïve Bayesian
5. Arroyo, M. T. K., Marticorena, C., Matthei, O., & Cavieres, L. (2000). Plant invasions in Chile: present patterns and future predictions. Invasive species in a changing world (pp. 385-421).
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