Comparative Study of Various Sequential Pattern Mining Algorithms

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
In sequential pattern, mining represents an important class of data mining problems with wide range of applications. It is one of the very challenging problems because it deals with the careful scanning of a combinatorial large number of possible subsequence patterns. Broadly sequential pattern mining algorithms can be classified into three types namely Apriori based approaches, pattern growth algorithms and early pruning algorithms. These algorithms have further classification and extensions. Detailed explanation of each algorithm along with its important features, pseudo code, advantages and disadvantages is given in the subsequent sections of the paper.

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