Mining Customer Data for Decision Making Using Effective Frequent Pattern Mining Algorithm
| Author(s) | : | Mr. Ravi Kumar, Mr. Hemant Sahu |
| Institution | : | Dept of Computer Science and Eng. Parthivi College of Engineering & Management Bhilai, Chhattisgarh, India |
| Published In | : | Vol. 4, Issue 15 — January 2017 |
| Page No. | : | - |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
This The huge amounts of datacontinuously being collected and stored in databases,many companies and firms are becoming interested inmining association rules from their databases to increasetheir profits. Frequent pattern discovery from customerdata is playing an important role for business support andimprovement. Punctually identification of new emergingtrends is very important in business process. Salespatterns from inventory data signalize market tendencyand can be used in forecasting which has great potentialfor decision making, strategic planning and marketcompetition. The objective of this paper is to know thecustomer behavior at the time of purchase, how easilyprovide them what they want? The proposed approachmakes use of the traditional Apriori algorithm to generatea set of association rules from a database and someimprovement over Apriori for fast scanning of thedatabase.
Mr. Ravi Kumar, Mr. Hemant Sahu, “Mining Customer Data for Decision Making Using Effective Frequent Pattern Mining Algorithm”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 15, pp. -, January 2017.
