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
- An Introduction to Sequence Prediction
- An Introduction to 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
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.
- 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.
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. (download count:
Those are external projects (may not be up-to-date):
- A wrapper for using SPMF algorithms in Weka: :https://github.com/chrispy645/spmf-wrapper
- A wrapper for using SPMF algorithms in R : https://github.com/pommedeterresautee/spmf
- A wrapper for using some SPMF algorithm (VMSP) in Python: https://github.com/fandu/maximal-sequential-patterns-mining
- Wrappers for using some SPMF algorithms in Spark: https://github.com/skrusche63/spark-fsm and https://github.com/skrusche63/spark-arules