Abstract
This paper presents an efficient algorithm for maintaining the generator representation in dynamic datasets. The generators representation is a kind of lossless, concise representation of the set of frequent itemsets. Furthermore, the algorithm utilizes a novel optimization based on generators borders for the first time in the literature. Generators borders are the borderline between frequent generators and other itemsets. New frequent generators can be generated through monitoring them. Experiments show that our algorithm is more efficient than previous solutions.
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© 2005 Springer-Verlag Berlin Heidelberg
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Xu, L., Xie, K. (2005). An Incremental Algorithm for Mining Generators Representation. In: Jorge, A.M., Torgo, L., Brazdil, P., Camacho, R., Gama, J. (eds) Knowledge Discovery in Databases: PKDD 2005. PKDD 2005. Lecture Notes in Computer Science(), vol 3721. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564126_75
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DOI: https://doi.org/10.1007/11564126_75
Publisher Name: Springer, Berlin, Heidelberg
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