Effective and Innovative Approaches for Comparing Different Multilevel Association Rule Mining for Feature Extraction: A Review

Today multilevel association rule mining is an emerging field in data mining. Its main goal is to find hidden information in or between levels of abstraction. It is mainly used for decision making for large data. It focuses on the customer relationship management. Apriori algorithm is mainly used for the multilevel association rule mining. Producing large number of candidate item sets and multiple scanning databases is main shortage of the Apriori algorithm. Because of the multilevel association execution time is reduced and throughput increase in new methods.MRA algorithm using Bayesian probability, concept hierarchy ,COFI-tree method, dynamic concept hierarchy are used for increase performance of multilevel association rule mining.

[1]  Parag Kulkarni,et al.  Multilevel Relationship Algorithm for Association Rule Mining used for Cooperative Learning , 2014 .

[2]  Sonia Setia.  Multi-Level Association Rule Mining: A Review , 2013 .

[3]  M. Dunham,et al.  A SURVEY OF ASSOCIATION RULES , 2000 .

[4]  Younghee Kim,et al.  Mining Multilevel Association Rules on RFID Data , 2009, 2009 First Asian Conference on Intelligent Information and Database Systems.

[5]  Huang Qinglan,et al.  Multi-level Association Rule Mining Based on Clustering Partition , 2013, 2013 Third International Conference on Intelligent System Design and Engineering Applications.

[6]  Deepak Vidhate,et al.  To improve association rule mining using new technique: Multilevel relationship algorithm towards cooperative learning , 2014, 2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA).

[8]  K. R. Pardasani,et al.  Discovery of Multi-level Association Rules from Primitive Level Frequent Patterns Tree , 2022 .

[9]  Pratima Gautam,et al.  Algorithm for Efficient Multilevel Association Rule Mining , 2010 .

[10]  Yong Liang,et al.  Mining multilevel association rules with dynamic concept hierarchy , 2008, 2008 International Conference on Machine Learning and Cybernetics.

[11]  Udai Pratap Rao,et al.  Hiding sensitive association rules to maintain privacy and data quality in database , 2013, 2013 3rd IEEE International Advance Computing Conference (IACC).