Pattern Discovery Using Association rule |
Author(s): |
| Pratik Ahuja , Thakur College of Engineering and Technology; Chinmay Birla, Thakur College Of Engineering and Technology; Sonu Varma, Thakur College of Engineering and Technology |
Keywords: |
| Retail, Market, Data, Assciation Rule, Account, Database, Algorithm, Admin KDD, Improved System, SDLC, Apriori, Mining, warehousing, SCM |
Abstract |
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Database mining is motivated by decision support problems faced by most business organizations and is described as an important area of research. One of the most challenges in database mining is developing fast and efficient algorithms that can handle large volume of data because most mining algorithms performs computation over the entire database and often the database are very large.The methodologies of data mining that are used by existing market basket analysis are apriori algorithm to find frequent item sets for a large database but it has many shortcoming which can be resolved by many other algorithms one of which is Partitioning the large database and using apriori algorithm . Existing Market basket analysis display the frequent item set when searched for a particular item but the proposed system will show the results of prediction when searched for a particular item so as to improve the business throughput. |
Other Details |
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Paper ID: IJSRDV2I2382 Published in: Volume : 2, Issue : 2 Publication Date: 01/05/2014 Page(s): 681-683 |
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