Association Rule Mining using Apriori Algorithm: A Survey

Association rule mining is the most important technique in the field of data mining. Association rule mining finding frequent patterns, associations, correlations, or causal structures among sets of items or objects in transaction databases, relational databases, and other information repositories. In this paper we present a survey of recent research work carried by different researchers. Of course, a single article cannot be a complete review of all the research work, yet we hope that it will provide a guideline for the researcher in interesting research directions that have yet to be explored.

[1]  Zhuang Chen,et al.  An improved Apriori algorithm based on pruning optimization and transaction reduction , 2011, 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC).

[2]  R. Sumithra,et al.  Using distributed apriori association rule and classical apriori mining algorithms for grid based knowledge discovery , 2010, 2010 Second International conference on Computing, Communication and Networking Technologies.

[3]  Yongge Shi,et al.  An Improved Apriori Algorithm , 2010, 2010 IEEE International Conference on Granular Computing.

[4]  Huiying Wang,et al.  The research of improved association rules mining Apriori algorithm , 2011, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[5]  Rupali Haldulakar.  Optimization of Association Rule Mining through Genetic Algorithm , 2011 .

[6]  Zhigang Lu,et al.  An Improved Apriori-based Algorithm for Association Rules Mining , 2009, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery.

[7]  Yong-qing Wei,et al.  An improved Apriori algorithm for association rules of mining , 2009, 2009 IEEE International Symposium on IT in Medicine & Education.