Data = Normal + Anomalous + Noise

Sanjay Chawla

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Our world at the micro, macro and personal level is now highly instrumented. A consequence of this instrumentation is that now it is possible to obtain fine-grained data about almost anything of interest. Once we focus on an application or a domain, it is reasonable to assume that much of the data obtained captures the "normal" behavior of the underlying phenomenon. Historically, "knowledge discovery," if any, has been triggered by the non-normal or anomalous part of the data. In this talk I will present some classic examples of data anomalies and how their discovery has changed our understanding of the world. Then I will present a modern and algorithmic viewpoint of anomaly detection as is currently practiced in the data mining community.

Original languageEnglish
Title of host publicationProceedings of the 10th Australasian Data Mining Conference, AusDM 2012
EditorsYanchang Zhao, Peter Christen, Jiuyong Li, Paul J. Kennedy
PublisherAustralian Computer Society
Number of pages1
ISBN (Electronic)9781921770142
StatePublished - 2012
Externally publishedYes

Publication series

NameConferences in Research and Practice in Information Technology Series
ISSN (Print)1445-1336


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