A Survey and comparative study of the various algorithms for Frequent Itemset Mining - Uma, N; Prashanth, CSR (International Journal of Computer Sciences and Engineering, 2025)
In Data mining field, frequent item set mining is one of the most intensively investigated problems in terms of computational complexity. The concept is widely used in market basket analysis, finance, and health care systems. Finding frequent patterns plays an essential role in mining associations, correlations and much other interesting relationship among data. The interest in the problem still persists despite of elaborate research conducted in the last two decades, due to its computational complexity and the fact that the results sets can be exponentially large. This combinatorial explosion of frequent item set methods become even more problematic when they are applied to Big Data. In this survey paper, an effort is made to present various popular algorithms and its analysis.