Abstract: As a branch of frequent pattern mining, the task-oriented pattern mining has received increasing attention due to its broad application scenarios. The lexicographic subset tree based ...

Coimisiún na Meán is on a roll. On Tuesday, three years into its tenure as Ireland’s – and by extension Europe’s – de facto tech regulator, it announced its fourth and fifth investigations into large ...

Abstract: Partial periodic-frequent pattern mining is a critical technique in the data mining field. This technique finds all frequent patterns demonstrating partial periodicity within temporal ...

The FP-Growth (Frequent Pattern Growth) algorithm is a breakthrough in association rule mining, offering a faster and more memory-efficient alternative to the Apriori algorithm. By eliminating the ...

Agrawal, Rakesh, and Ramakrishnan Srikant. “Fast Algorithms for Mining Association Rules in Large Databases.” In Proceedings of the 20th International Conference on Very Large Data Bases, 487–99. VLDB ...

Metal coins may be just about the oldest medium of exchange still in use today, but ensuring their worth requires some of the most state-of-the-art technology available. Counterfeit coins remain a ...

With the rapid development of AI and big data mining technologies, computerized medical decision-making has become increasingly prominent. The aim of high-utility pattern mining (HUPM) is to discover ...

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover ...

Network analysis can be applied to understand organizations based on patterns of communication, knowledge flows, trust, and the proximity of employees. A multidimensional organizational network was ...

ABSTRACT: The process of extracting patterns that are frequent from supermarket datasets is a well known problem of data mining. Nowadays, we have many approaches to resolve the problem. Association ...