@inbook{dbc777b108564d85b371ef9df7777aee,
title = "Data = Normal + Anomalous + Noise",
abstract = "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.",
author = "Sanjay Chawla",
note = "Publisher Copyright: {\textcopyright} 2012, Australian Computer Society, Inc.",
year = "2012",
language = "English",
series = "Conferences in Research and Practice in Information Technology Series",
publisher = "Australian Computer Society",
pages = "3",
editor = "Yanchang Zhao and Peter Christen and Jiuyong Li and Kennedy, {Paul J.}",
booktitle = "Proceedings of the 10th Australasian Data Mining Conference, AusDM 2012",
}