20 Best Data Mining For Association Rules And Sequential Patterns [2024]

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FAQ:

Q: What are the best algorithms for sequential pattern mining?

A: There exists several sequential pattern mining algorithms. Some of the classic algorithms for this problem are PrefixSpan, Spade, SPAM, and GSP. However, in the recent decade, several novel and more efficient algorithms have been proposed such as CM-SPADE and CM-SPAM (2014), FCloSM and FGenSM (2017), to name a few.

Q: What is pattern mining?

A: Pattern mining consists of discovering interesting, useful, and unexpected patterns in databases Various types of patterns can be discovered in databases such as frequent itemsets, associations, subgraphs , sequential rules, and periodic patterns.

Q: What is the difference between association rule mining and sequential pattern mining?

A: Association rule mining, however, does not consider the sequence in which the items are purchased. Sequential pattern mining takes care of that. An example of a sequential pattern is “5% of customers buy bed first, then mattress and then pillows” The items are not purchased at the same time, but one after another.

Q: What is sequence database pattern mining?

A: There has been a lot of work in the field of data mining about pattern mining . The goal of pattern mining is to discover useful, novel and/or unexpected patterns in databases. In this blog post, we will be interested by a specific type of database called sequences databases. A sequence database contains some sequences.