Title :
Use of mining techniques to improve the effectiveness of marketing and sales
Author :
Malgaonkar, Saurabh ; Surve, S. ; Hirave, Tejas
Author_Institution :
Dept. of Comput. Eng., Mumbai Univ., Mumbai, India
Abstract :
The mentioned system is designed to find the most frequent combinations of items. It is based on developing an efficient algorithm that outperforms the best available frequent pattern algorithms on a number of typical data sets. This will help in marketing and sales. The technique can be used to uncover interesting cross-sells and related products. Three different algorithms from association mining have been implanted and then best combination method is utilized to find more interesting results. The analyst then can perform the data mining and extraction and finally conclude the result and make appropriate decision.
Keywords :
data mining; marketing data processing; efficient algorithm; frequent pattern algorithms; marketing and sales; mining techniques; Algorithm design and analysis; Association rules; Computers; Educational institutions; Itemsets; association rule mining; data mining; maximal frequent pattern; mining evolution;
Conference_Titel :
Advances in Technology and Engineering (ICATE), 2013 International Conference on
Conference_Location :
Mumbai
Print_ISBN :
978-1-4673-5618-3
DOI :
10.1109/ICAdTE.2013.6524726