Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

Anomaly detection is an important problem that has been researched within diverse
research areas and application domains. Many anomaly detection techniques have been …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

Outliers are also referred to as abnormalities, discordants, deviants, or anomalies in the data
mining and statistics literature. In most applications, the data is created by one or more …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

Traditional databases store sets of relatively static records with no pre-defined notion of time,
unless timestamp attributes are explicitly added. While this model adequately represents …

Fast indexing in time sequence databases for similarity searching has attracted a lot of
research recently. Most of the proposals, however, typically centered around the Euclidean …

Publisher Summary Maintaining multistream and time-delayed statistics in a continuous
online fashion is a significant challenge in data management. This chapter solves this …

In many recent applications, data may take the form of continuous data streams, rather than
finite stored data sets. Several aspects of data management need to be reconsidered in the …

Outlier detection has been a very important concept in the realm of data analysis. Recently,
several application domains have realized the direct map** between outliers in data and …