SPMF is an open-source data mining mining platform written in Java.

Sequence data pattern mining Framework in Java (SPMF)

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I was doing some research on how to mine patterns from sequence data and I found a really good open sourced platform called SPMF.

SPMF is an open-source data mining platform written in Java. It is distributed under the GPL v3 license.

SPMF is an open-source data mining mining platform written in Java.

SPMF is an open-source data mining mining platform written in Java.

The link to the website:  http://www.philippe-fournier-viger.com/spmf/index.php

It offers implementations of 52 data mining algorithms for:

  • sequential pattern mining,
  • association rule mining,
  • frequent itemset mining,
  • sequential rule mining,
  • clustering

It can be used as a standalone program with a user interface or from the command line. Moreover, the source code of each algorithm can be integrated in other Java software.

The following picture is a map which you can visualize the relationship between the various data mining algorithms offered in SPMF.

Visual map of algorithms

Visual map of algorithms

 

Supporting Algorithms

Sequential Pattern Mining Algorithms

  • the PrefixSpan algorithm for mining frequent sequential patterns from a sequence database (Pei et al., 2004).
  • the SPAM algorithm for mining frequent sequential patterns from a sequence database (Ayres, 2002)
  • the BIDE+ algorithm for mining frequent closed sequential patterns from a sequence database (Wang et al. 2007)
  • the SeqDIM algorithm for mining frequent multidimensional sequential patterns from a multi-dimensional sequence database (Pinto et al. 2001)
  • the Songram et al. algorithm for mining frequent closed multidimensional sequential patterns from a multi-dimensional sequence database (Songram et al. 2006)
  • the Fournier-Viger et al. algorithm, a sequential pattern mining algorithm that combines several features from well-known sequential pattern mining algorithms and also proposes some original features (Fournier-Viger et al., 2008):

Sequential Rule Mining Algorithms

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