Informatics Publishing Limited

D. Kerana Hanirex ¹, K. P. Kaliyamurthie ¹

Affiliations
1 Department of Computer Science Engineering, Bharath University, Chennai – 600073, Tamil Nadu, IN

Abstract

Association rule mining is the recent data mining research. We have presented an approach for mining frequent itemsets using dengue virus type-1 data set. This paper proposes an Improved Two Dimensional Transaction Reduction (ITDTR) algorithm which is a combined approach of transaction reduction and sampling in bio data mining. This system produces the same frequent item sets as produced from Apriori algorithm and FP-Growth algorithm with the higher performance. This system reveals that Glycine(G), Leucine(L), Serine(S), Lysine(K), Phenylalanine(F) are the dominating amino acids in dengue virus type-1 data set with higher accuracy and efficiency. The efficiency of this algorithm is compared with Apriori algorithm, FP-Growth algorithm, Genetic algorithm and TDTR algorithm which we have implemented in our previous research work.

Keywords

Apriori, Association Rule Mining, Bio Data Mining, Data Mining, Distributed and TDTR, FP-Growth, Genetic, ITDTR

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D. Kerana Hanirex ¹, K. P. Kaliyamurthie ¹

Affiliations
1 Department of Computer Science Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN

Abstract

Association rule mining is one of the recent data mining research.Mining frequent itemsets in relational databases using relational queries give great attention to researchers nowadays. This paper implements set oriented algorithm for mining frequent itemsets in relational databases. In this paper the sort and merge scan algorithm SETM is implemented for super market data set.This paper finds out the frequent itemset and its execution time and the results are compared with the traditional Apriori algorithm.

Keywords

5-6 words, Drawn from title, Word representing the work.

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