Abstract
Frequent Itemsets (FI) Mining is one of the most researched areas of data mining. When some new transactions are appended, deleted or modified in a dataset, updating FI is a nontrivial task since such updates may invalidate existing FI or introduce new ones. In this paper a novel algorithm suitable for FI mining in dynamic datasets named Incremental Compressed Arrays is presented. In the experiments, our algorithm was compared against some algorithms as Eclat, PatriciaMine and FP-growth when new transactions are added or deleted. © 2008 Springer-Verlag Berlin Heidelberg.
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Hernández-León, R., Hernández-Palancar, J., Carrasco-Ochoa, J. A., & Martínez-Trinidad, J. F. (2008). A novel incremental algorithm for frequent itemsets mining in dynamic datasets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5197 LNCS, pp. 145–152). https://doi.org/10.1007/978-3-540-85920-8_18
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