Other resources
Tutorials
Blog posts written by the founder of SPMF
- Getting started with SPMF
- Interview with the SPMF founder: Philippe Fournier-viger
- Discovering hidden patterns in texts using SPMF
- Introduction to time series mining with SPMF
- Discovering and visualizing sequential patterns in web log data using SPMF and GraphViz
- Introduction to the Apriori algorithm (with Java code)
- Introduction to clustering: the K-Means algorithm (with Java code)
- An Introduction to Data Mining
- An Overview of Pattern Mining Techniques (by data types)
- An introduction to Frequent Pattern Mining
- An Introduction to Sequential Pattern Mining
- An Introduction to Sequential Rule Mining
- An introduction to Periodic Pattern Mining
- Key papers about Periodic Pattern Mining
- An Introduction to Sequence Prediction
- An
Introduction to High Utility Itemset Mining
- Key papers about High Utility Itemset Mining
- An Introduction to High Utility Quantitative Itemset Mining
- An Introduction to High Utility Itemset Mining with a Taxonomy
- An Introduction to Frequent Subgraph Mining
- An Introduction to Episode Mining
- Key papers about Episode Mining
- How to call SPMF from R?
- How to call SPMF from Python?
- How to call SPMF from C#?
- How to call SPMF from a C++ Program (Windows)?
- How to run SPMF from VB (Visual Basic) .NET?
- SPMF’s architecture (1) The Algorithm Manager
Research papers
Papers presenting the SPMF software:
- Fournier-Viger, P., Lin, C.W., Gomariz, A., Soltani, A., Deng, Z., Lam, H. T. (2016). The SPMF Open-Source Data Mining Library Version 2. Proc. 19th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD 2016). Springer, pp. 36-40.
- Fournier-Viger, P., Gomariz, A., Gueniche, T., Soltani, A., Wu., C., Tseng, V. S. (2014). SPMF: a Java Open-Source Pattern Mining Library. Journal of Machine Learning Research (JMLR), 15: 3389-3393.
Survey papers:
- Fournier-Viger., P., Lin, J. C.-W., Truong, T., Nkambou, R. (2019). A survey of high utility itemset mining. In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer (to appear), p. 1-46.
- Fournier-Viger, P., Lin, J. C.-W., Vo, B, Chi, T.T., Zhang, J., Le, H. B. (2017). A Survey of Itemset Mining. WIREs Data Mining and Knowledge Discovery, e1207 doi: 10.1002/widm.1207, 18 pages.
- Fournier-Viger, P., Lin, J. C.-W., Kiran, R. U., Koh, Y. S., Thomas, R. (2017). A Survey of Sequential Pattern Mining. Data Science and Pattern Recognition (DSPR), vol. 1(1), pp. 54-77.
- Ouarem, O., Nouioua, F., Fournier-Viger, P. (2023). A Survey of Episode Mining. WIREs Data Mining and Knowledge Discovery, Wiley,14(2):e1524.
Papers describing each algorithm offered in SPMF: Algorithms
Papers citing SPMF: Citations
Textbook about Pattern Mining and SPMF
- "Pattern
Mining :Theory and Practice" (PDF) (2020, in Thai
language) by Teacher Panida Songram from Mahasarakham
University. This textbook gives a good introduction to pattern mining
and cover various topic as well as describes how to use the SPMF
software.

Related projects
Several wrappers have been proposed to use SPMF or some algorithms from SPMF in other software or languages such as Weka, R, Python and Spark.
