Abstract
SPMF is an open-source data mining library, specialized in pattern mining, offering implementations of more than 120 data mining algorithms. It has been used in more than 310 research papers to solve applied problems in a wide range of domains from authorship attribution to restaurant recommendation. Its implementations are also commonly used as benchmarks in research papers, and it has also been integrated in several data analysis software programs. After three years of development, this paper introduces the second major revision of the library, named SPMF 2, which provides (1) more than 60 new algorithm implementations (including novel algorithms for sequence prediction), (2) an improved user interface with pattern visualization (3) a novel plug-in system, (4) improved performance, and (5) support for text mining.
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Fournier-Viger, P., Lin, J. C. W., Gomariz, A., Gueniche, T., Soltani, A., Deng, Z., & Lam, H. T. (2016). The SPMF open-source data mining library version 2. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9853 LNCS, pp. 36–40). Springer Verlag. https://doi.org/10.1007/978-3-319-46131-1_8
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