Stealing attack against controlled information, along with the increasing number of
information leakage incidents, has become an emerging cyber security threat in recent …

In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …

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 …

The proliferation of trajectory data in various application domains has inspired tremendous
research efforts to analyze large-scale trajectory data from a variety of aspects. A …

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 …

In the last two decades, machine learning research and practice has focused on batch
learning, usually with small datasets. Nowadays there are applications in which the data are …

In this paper, we propose a novel method for discovering characteristic patterns in a time
series called SAX-VSM. This method is based on two existing techniques-Symbolic …

Anomaly Detection in multivariate, time-series data collected from aircraft's Flight Data
Recorder (FDR) or Flight Operational Quality Assurance (FOQA) data provide a powerful …

This chapter focuses on individual univariate time series sampled uniformly through time. It
describes the use of time-series features for tackling time-series forecasting. The chapter …

Time series motifs are approximately repeating patterns in real-valued time series data.
They are useful for exploratory data mining and are often used as inputs for various time …