High-utility and diverse itemset mining
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-020-02063-x.pdf
Reference28 articles.
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3. Aryabarzan N, Minaei-Bidgoli B, Teshnehlab M (2018) NegFIN: an efficient algorithm for fast mining frequent itemsets. Expert Syst Appl 105:129–143. https://doi.org/10.1016/j.eswa.2018.03.041
4. Dawar S, Goyal V (2015) UP-Hist tree: An efficient data structure for mining high utility patterns from transaction databases. In: Proceedings of the 19th international database engineering & applications symposium. ACM, New York, pp 56–61, DOI https://doi.org/10.1145/2790755.2790771, (to appear in print)
5. Dawar S, Goyal V, Bera D (2017) A hybrid framework for mining high-utility itemsets in a sparse transaction database. Appl Intell 47(3):809–827. https://doi.org/10.1007/s10489-017-0932-1
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