Study on Positive and Negative Rule Based Mining Techniques for E-Commerce Applications

Kavita Yadav¹, Pravin G Kulurkar²

^1,2Vidharbha Institute of Technology, Nagpur

Abstract

In the recent years the scope of data mining has evolved into an active area of research because of the previously unknown and interesting knowledge from very large database collection. The data mining is applied on a variety of applications in multiple domains like in business, IT and many more sectors. In Data Mining the major problem which receives great attention by the community is the classification of the data. The classification of data should be such that it could be they can be easily verified and should be easily interpreted by the humans. In this paper we would be studying various data mining techniques so that we can find few combinations for enhancing the hybrid technique which would be having multiple techniques involved so enhance the usability of the application. We would be studying CHARM Algorithm, CM-SPAM Algorithm, Apriori Algorithm, MOPNAR Algorithm and the Top K Rules.

Keywords

• Data Mining, CHARM Algorithm, CM-SPAM Algorithm, Apriori Algorithm, MOPNAR Algorithm, Top K Rules

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Cite this Article as Follows

Kavita Yadav, Pravin G Kulurkar. "Study on Positive and Negative Rule Based Mining Techniques for E-Commerce Applications" International Conference on Computer Applications (2016): 06-09. Print.