A Comprehensive Survey of Pattern Mining: Challenges and Opportunities

Abstract

Pattern mining is an important field of data mining. The fundamental task of data mining is to explore the database to find out sequential, frequent patterns. In recent years, data mining has shifted its focus to design methods for discovering patterns with user expectations. In this regard various types of pattern mining methods have been proposed. Frequent pattern mining, sequential pattern mining, temporal pattern mining, and constraint based pattern mining. Pattern mining has various useful real-life applications such as market basket analysis, e-learning, social network analysis, web page, click sequences, Bioinformatics, etc., this paper presents a survey of various types of pattern mining. The main goal of this paper is to present both an introduction to all pattern mining and a survey of various algorithms, challenges and research opportunities. This paper not only discusses the problems of pattern mining and its related applications, but also the extensions and possible future improvements in this field.

Detecting the Behaviour of COVID-19 Based On Parallel Approach of Sequential Rule Mining Algorithm

“…It can boost productivity by doing multiple tasks at once. The multi-core processor has two or more cores are placed in the same physical package [32][33]. Each CPU core has its memory and shares the main memory, as seen in Figure 1.…”