Estimation of the density of datasets with Decision Diagrams

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Abstract

We address the problem of loading transactional datasets into main memory and estimating the density of such datasets. We propose BoolLoader, an algorithm dedicated to these tasks; it relies on a compressed representation of all the transactions of the dataset. For sake of efficiency, we have chosen Decision Diagrams as the main data structure to the representation of datasets into memory. We give an experimental evaluation of our algorithm on both dense and sparse datasets. Experiments have shown that BoolLoader is efficient for loading some dense datasets and gives a partial answer about the nature of the dataset before time-consuming patterns extraction tasks. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Salleb, A., & Vrain, C. (2005). Estimation of the density of datasets with Decision Diagrams. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3488 LNAI, pp. 688–697). Springer Verlag. https://doi.org/10.1007/11425274_71

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