• Birla Sunderlal

The purpose of the Apriori Algorithm is to find frequent itemsets between different transaction sets of data.Apriori is a classical algorithm for frequent patterns extraction. An approach implemented in Transposed database then result is very fast. Apriori is work to operate on databases containing transactions. The main aim of this research is to improve the performance of the conventional Apriori algorithm that extracts frequent patterns for binary transaction dataset. Recently, different works proposed a new way to mine frequent patterns in transposed databases where a database with thousands of attributes but only tens of objects. In this case, mining the transposed database runs through a smaller search space. This work systematically explores the search space of frequent patterns mining and represent database in transposed form. This paper proposed an algorithm for mining frequent patterns which are based on Apriori algorithm and used space reduced longest common sequence (LCS) which makes apriori algorithm space efficient. Space complexity for Proposed algorithm is O(n) while the Dynamic Approach like Longest Common Subsequence space complexity is O(n2) memory for given items in dataset.

Transposition of database, Apriori algorithm, LCS, Frequent itemset, Data mining, Space complexity.

" Method for extracting Frequent Pattern Using Transposition of Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.23-27, March-2019, Available :http://www.jetir.org/papers/JETIR1903D07.pdf

" Method for extracting Frequent Pattern Using Transposition of Database", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp23-27, March-2019, Available at : http://www.jetir.org/papers/JETIR1903D07.pdf