In Data mining field, though an intensive investigation is done,the problem of frequent item set mining is still an interesting and challenging problem in terms of its computational complexity. The concept of frequent item set forms the basis of association rule mining and correlation mining and is widely used in market basket analysis, finance, and health care systems. Though,the research community has contributed a lot in this field,the interest in the problem persists due to the underlying complexity involved in computation resulting in combinatorial explosion of itemsets. In this paper, an effort is made to understand the main techniques used to solve these problems and to provide a comprehensive survey of the most influential algorithms in this field
Volume 12 | 02-Special Issue
Pages: 448-454
DOI: 10.5373/JARDCS/V12SP2/SP20201091