SMIM Framework to Generalize High-Utility Itemset Mining
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-95408-6_1
Reference23 articles.
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3. Cerf, L., Meira, W.: Complete discovery of high-quality patterns in large numerical tensors. In: 2014 IEEE 30th International Conference on Data Engineering (2014)
4. Coussat, A., Nadisic, N., Cerf, L.: Mining high-utility patterns in uncertain tensors. Procedia Comput. Sci. 126, 404–412 (2018)
5. Dawar, S., Goyal, V., Bera, D.: A hybrid framework for mining high-utility itemsets in a sparse transaction database. Appl. Intell. 47(3), 809–827 (2017). https://doi.org/10.1007/s10489-017-0932-1
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