Summary
A new algorithm named Compressed Binary Mine (CBMine) for mining association rules and frequent patterns is presented in this chapter. Its efficiency is based on a compressed vertical binary representation of the database. CBMine was compared with several a priori implementations, like Bodon’s a priori algorithm, and MAFIA, another vertical binary representation method. The experimental results have shown that CBMine has significantly better performance, especially for sparse databases.
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Palancar, J.H., León, R.H., Pagola, J.M., Hechavarría, A. (2008). A Compressed Vertical Binary Algorithm for Mining Frequent Patterns. In: Lin, T.Y., Xie, Y., Wasilewska, A., Liau, CJ. (eds) Data Mining: Foundations and Practice. Studies in Computational Intelligence, vol 118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78488-3_12
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DOI: https://doi.org/10.1007/978-3-540-78488-3_12
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