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DynTARM: An In-Memory Data Structure for Targeted Strong and Rare Association Rule Mining over Time-Varying Domains.

, , , and . Web Intelligence, page 298-306. IEEE Computer Society, (2013)

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Targeted Action Rule Discovery., , , and . ICMLA (1), page 348-353. IEEE, (2013)Min-Max Itemset Trees for Dense and Categorical Datasets., , and . ISMIS, volume 7661 of Lecture Notes in Computer Science, page 51-60. Springer, (2012)Exploiting multi-layered vector spaces for signal peptide detection., , , , , , and . Int. J. Data Min. Bioinform., 13 (2): 141-157 (2015)Detecting adverse drug effects using link classification on twitter data., , , , and . BIBM, page 675-679. IEEE Computer Society, (2015)DynTARM: An In-Memory Data Structure for Targeted Strong and Rare Association Rule Mining over Time-Varying Domains., , , and . Web Intelligence, page 298-306. IEEE Computer Society, (2013)Estimating Size of Search Engines in an Uncooperative Environment., , , , , and . Workshop on Web-based Support Systems, page 81-87. Saint Mary's University, Canada, (2004)TADS: Transformation of Anomalies in Data Streams., , and . IEEE BigData, page 4284-4292. IEEE, (2020)Detection of event onset using Twitter., , , and . IJCNN, page 1539-1546. IEEE, (2016)Sub-event detection from tweets., , and . IJCNN, page 2128-2135. IEEE, (2017)Discovery of Action Rules for Continuously Valued Data., , , , , and . CogMI, page 127-135. IEEE, (2019)