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Detecting Changes in Rare Patterns from Data Streams.

, , , and . PAKDD (2), volume 8444 of Lecture Notes in Computer Science, page 437-448. Springer, (2014)

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Proactive drift detection: Predicting concept drifts in data streams using probabilistic networks., , and . IJCNN, page 780-787. IEEE, (2016)Fingerprinting Concepts in Data Streams with Supervised and Unsupervised Meta-Information., , , , , and . ICDE, page 1056-1067. IEEE, (2021)Feature Drift Detection in Evolving Data Streams., and . DEXA (2), volume 12392 of Lecture Notes in Computer Science, page 335-349. Springer, (2020)EWGen: Automatic Generation of Item Weights for Weighted Association Rule Mining., , and . ADMA (1), volume 6440 of Lecture Notes in Computer Science, page 36-47. Springer, (2010)Transaction Clustering Using a Seeds Based Approach., and . PAKDD, volume 5012 of Lecture Notes in Computer Science, page 916-922. Springer, (2008)Unsupervised Semantic and Syntactic Based Classification of Scientific Citations., , and . DaWaK, volume 9263 of Lecture Notes in Computer Science, page 28-39. Springer, (2015)HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values., and . DaWaK, volume 9263 of Lecture Notes in Computer Science, page 43-56. Springer, (2015)Tracking Drift Severity in Data Streams., , and . Australasian Conference on Artificial Intelligence, volume 9457 of Lecture Notes in Computer Science, page 96-108. Springer, (2015)Detecting Changes in Rare Patterns from Data Streams., , , and . PAKDD (2), volume 8444 of Lecture Notes in Computer Science, page 437-448. Springer, (2014)Kernel-Tree: Mining Frequent Patterns in a Data Stream Based on Forecast Support., , , and . Australasian Conference on Artificial Intelligence, volume 7691 of Lecture Notes in Computer Science, page 614-625. Springer, (2012)