关键词: 综述, 序列模式挖掘, 树结构, 列表结构, 分布式框架

Abstract: Sequential pattern mining aims to discover interesting patterns or rules from databases to support and guide user decision-making. In recent years, research on algorithms related to sequential pattern mining has been increasingly in-depth. With the emergence of large-scale data, many sequential algorithms suitable for parallel environments have been proposed. A review of existing sequential and parallel sequential mining algorithms is presented. In sequential pattern serial mining algorithms, algorithms are categorized based on the data structures they use, such as tree structures, list structures, and linked structures, comprehensively summarizing the advantages and disadvantages of different structures and detailing the strengths and weaknesses of each algorithm. In sequential pattern parallel mining algorithms, for the first time, the existing distributed frameworks are classified according to different characteristics of storage structures, analyzing the advantages and disadvantages of different distributed frameworks and introducing and analyzing parallel algorithms based on these frameworks. Finally, future research directions are proposed to address the shortcomings of existing sequential pattern mining methods.

Key words: survey, sequential pattern mining, tree structure, list structure, distributed framework