A Review Paper: A Comparative Analysis on Association Rule Mining Algorithms
Gurpreet Singh1, Sonia Jassi2
1Dr. Gurpreet Singh, Professor & Head, Department of Computer Science & Engineering, St. Soldier Institute of Engineering Technology, Jalandhar (Punjab), India.
2Dr. Sonia Jassi, M.Tech Scholar, Department of Computer Science & Engineering, St. Soldier Institute of Engineering Technology, Jalandhar (Punjab), India.
Manuscript received on 22 May 2017 | Revised Manuscript received on 30 May 2017 | Manuscript published on 30 May 2017 | PP: 1-3 | Volume-6 Issue-2, May 2017 | Retrieval Number: B1665056217©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data mining is a process which finds useful patterns from large amount of data. The development of Information Technology has generated large amount of databases and huge data in various areas. The research in databases and information technology has given rise to an approach to store and manipulate this precious data for further decision making. Data mining is a process of extraction of useful information and patterns from huge data. It is also called as knowledge discovery process, knowledge mining from data, knowledge extraction or data /pattern analysis. [1] Various algorithms and techniques like Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees, Genetic Algorithm, Nearest Neighbor method etc., are used for knowledge discovery from databases. But here we are going to discuss Association rules mining.
Keywords: Data, Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees, Genetic Algorithm.
Scope of the Article: Classification