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Relational Frequent Patterns Mining for Novelty Detection from Data Streams.

, , , , , , and . MLDM, volume 5632 of Lecture Notes in Computer Science, page 427-439. Springer, (2009)

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Discovering Emerging Patterns for Anomaly Detection in Network Connection Data., , , and . ISMIS, volume 4994 of Lecture Notes in Computer Science, page 179-188. Springer, (2008)A Data Mining Methodology for Anomaly Detection in Network Data: Choosing System-Defined Decision Boundaries.. SEBD, page 332-340. (2007)Relational Frequent Patterns Mining for Novelty Detection from Data Streams., , , , , , and . MLDM, volume 5632 of Lecture Notes in Computer Science, page 427-439. Springer, (2009)A Relational Approach to Novelty Detection in Data Streams., , , , , , and . SEBD, page 89-100. Edizioni Seneca, (2009)Learning the Daily Model of Network Traffic., , and . ISMIS, volume 3488 of Lecture Notes in Computer Science, page 131-141. Springer, (2005)Novelty Detection from Evolving Complex Data Streams with Time Windows., , , , , and . ISMIS, volume 5722 of Lecture Notes in Computer Science, page 563-572. Springer, (2009)A Data Mining Methodology for Anomaly Detection in Network Data., and . KES (2), volume 4693 of Lecture Notes in Computer Science, page 109-116. Springer, (2007)Identity Mining vs Identity Discovering: a new approach., , and . Open Identity Summit, volume P-264 of LNI, page 175-180. GI, (2016)