High Occupancy Itemset Mining with Consideration of Transaction Occupancy
Author:
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-021-06075-8.pdf
Reference43 articles.
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3. Luna, J.M.; Fournier-Viger, P.; Ventura, S.: Frequent itemset mining: a 25 years review. WIREs Data Min. Knowl. Discov. 9(6), e1329 (2019)
4. Raj, S.; Ramesh, D.; Sreenu, M.; Sethi, K.K.: EAFIM: efficient apriori-based frequent itemset mining algorithm on Spark for big transactional data. Knowl. Inf. Syst. 62, 3565–3583 (2020)
5. Datta, S.; Mali, K.; Ghosh, S.: Mining frequent patterns partially devoid of dissociation with automated MMS specification strategy. IETE J. Res. (2020). https://doi.org/10.1080/03772063.2020.1838343
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