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Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Complements.

, , , , , , and . IEEE Access, (2023)

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3P-ECLAT: mining partial periodic patterns in columnar temporal databases., , , , , , , , and . Appl. Intell., 54 (11-12): 657-679 (January 2024)Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases., , , and . PAKDD (3), volume 13937 of Lecture Notes in Computer Science, page 29-41. Springer, (2023)A fundamental approach to discover closed periodic-frequent patterns in very large temporal databases., , , , , , , , and . Appl. Intell., 53 (22): 27344-27373 (November 2023)Discovering Fuzzy Frequent Spatial Patterns in Large Quantitative Spatiotemporal databases., , , , and . FUZZ-IEEE, page 1-8. IEEE, (2021)Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series., , , , , and . FUZZ, page 1-7. IEEE, (2023)Discovering Top-k Spatial High Utility Itemsets in Very Large Quantitative Spatiotemporal databases., , , , , , and . IEEE BigData, page 4925-4935. IEEE, (2021)Discovering Fuzzy Geo-referenced Periodic-Frequent Patterns in Geo-referenced Time Series Databases., , , , , , and . FUZZ-IEEE, page 1-8. IEEE, (2022)A Unified Framework to Discover Partial Periodic-Frequent Patterns in Row and Columnar Temporal Databases., , , , , and . ICDM (Workshops), page 607-614. IEEE, (2021)Discovering Maximal Partial Periodic Patterns in Very Large Temporal Databases., , , , and . IEEE BigData, page 1460-1469. IEEE, (2021)Towards Efficient Discovery of Periodic-Frequent Patterns in Dense Temporal Databases Using Complements., , , , , , and . DEXA (2), volume 13427 of Lecture Notes in Computer Science, page 204-215. Springer, (2022)