Data Mining and Knowledge Engineering

Manmay Badheka ¹, Shruti Yagnik ¹, Ompriya Kale ¹, Sagar Gajera ¹

Affiliations
1 Department of Computer Engineering, L. J. Institute of Engineering & Technology, Ahmedabad, IN

Abstract

In data mining approaches, association rules mining algorithms are promising for actual applications such as marketing strategies, catalog design. However, the association rules mining is essentially based on a database comprised of Boolean attributes. In order to apply a mining algorithm to further various problems, quantitative attributes should also be appropriately dealt. Fuzzy association rules mining approaches are proposed to overcome such disadvantages based on the fuzzy set concept. The fuzzy association rule mining has a good property in terms of the quantization of numerical attributes of a database compared to generalize Boolean association rule mining. So, the mining results of fuzzy association rules are easy to understand for corresponding human operators.

Keywords

Association Rule Mining, Fuzzy Association Rule Mining, Membership Function, Certainty Factor.

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Sagar Gajera ¹, Narendrasinh Limbad ¹, Manmay Badheka ¹

Affiliations
1 Department of Computer Engineering, L. J. Institute of Engineering & Technology, Ahmedabad, IN

Abstract

In Functions of Data Mining, Frequent Pattern mining algorithms are challenging for real time applications like market basket analysis, sales analysis etc. However, frequent pattern mining is based on occurrences of any item set into the database or data repositories. A-priori and FP-Tree are the most basic algorithms for mining frequent patterns. There are other methods developed from these two methods to make the procedure efficient and to overcome the disadvantages of basic algorithms. The advantages of these methods can be visualized using some attributes like efficiency, space efficiency, lower database scan, simplicity etc. Also, Comparison of these methods with each other, the disadvantages can be extracted.

Keywords

Association Rule Mining, Frequent Pattern Mining, Frequent Itemset, A-Priori Algorithm.

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