Association Rule Mining for Identifying Optimal Customers using MAA Algorithm |
Author(s): |
| V Vasudha Rani , GMRIT |
Keywords: |
| Apriori, Improved Apriori, Frequent item set, Support, Candidate item set, Time consuming |
Abstract |
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identifying customers which are more likely potential for a product and service offering is an important issue. In customers identification data mining has been used extensively to predict potential customers for a product and service. Most of the research effort in the scope of association rules has been oriented to simplify the rule set and to improve performance of the algorithm. With the recent advancement of Internet and Web Technology, web search has taken an important role in the ordinary life. This project suggests a new framework of algorithm MAA that overcomes the limitations associated with existing methods and enables the finding of association rules based on Apriori Algorithm among the presence and/or absence of a set of items without a preset minimum support threshold and Minimizing Candidate Generation. |
Other Details |
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Paper ID: IJSRDV5I90557 Published in: Volume : 5, Issue : 9 Publication Date: 01/12/2017 Page(s): 1005-1008 |
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