Theoretically and Comparatively Analysis of Different Frequent Pattern Mining Algorithms

Provided by: Seek Digital Library
Topic: Data Management
Format: PDF
In this paper, the authors are trying to comparing the different sequential data mining algorithms for finding the frequent data patterns. There are many algorithms have designed for finding the frequent data patterns from the transactional database. Transactional database have specified number of transactions itemsets T, which are used for knowledge discovery. For studying and comparatively analysis purpose, they take three methods, one is traditional method Apriori and other two methods are 1. LCM (Linear Closed itemset Miner) algorithm and 2. Top-K closed frequent pattern mining.

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