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.
|Number of pages||1|
|Publication status||Published - 2012|
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Information Systems