Sequential Mining: Patterns and Algorithms Analysis

TL;DR

This paper provides a comprehensive analysis and classification of existing sequential pattern mining algorithms, comparing their features and strategies to enhance understanding of this field.

Contribution

It offers a systematic classification and comparative analysis of various sequential pattern mining algorithms, highlighting their key features and differences.

Findings

Classified algorithms into five main categories

Compared algorithms based on key features

Enhanced understanding of sequential pattern mining approaches

Abstract

This paper presents and analysis the common existing sequential pattern mining algorithms. It presents a classifying study of sequential pattern-mining algorithms into five extensive classes. First, on the basis of Apriori-based algorithm, second on Breadth First Search-based strategy, third on Depth First Search strategy, fourth on sequential closed-pattern algorithm and five on the basis of incremental pattern mining algorithms. At the end, a comparative analysis is done on the basis of important key features supported by various algorithms. This study gives an enhancement in the understanding of the approaches of sequential pattern mining.