In 21st century, the big data revolution is happening and has found its place, also within the banking Industry, Bank can leverage big data analytics to gain deeper insights for customers, channels, a...

Financial time series usually exhibit non-stationarity and time-varying volatility. Extraction and analysis of complicated patterns, such as trends and transient changes, are at the core of modern fin...

Emotion recognition based on electroencephalogram (EEG) signals provides a direct access to inner state of a user, which is considered an important factor in Human-Machine-Interaction (HMI). Tradition...

Data representation is one of the most important tasks in time series data pre-processing. Time series data representation is required to make the data more suitable for data mining specifically for p...

Clustering streaming time series is a difficult problem. Most traditional algorithms are too inefficient for large amounts of data and outliers in them. In this paper, we propose a new clustering meth...

Abstract This paper starts by presenting a study from a computational performance standpoint of SAX/GA, an algorithm that uses the Symbolic Aggregate approXimation (SAX), to dimensionally reduce time ...

Abstract This paper proposes a method that discovers various sequential patterns from sequential data. The sequential data is a set of sequences. Each sequence is a row of item sets. Many previous met...

Abstract The most promising configuration of a nuclear energy fusion system is the tokamak, the largest of which, called ITER, is under construction in Cadarache, France, which uses a complex system o...

Abstract Many researchers have taken interests in time series data mining to discover potential knowledge and information as the amount of data from various domains rapidly increases. Representation, ...

Abstract In order to achieve an optimum and successful operation of an industrial process, it is important firstly to detect upsets, equipment malfunctions or other abnormal events as early as possibl...

Abstract Cervical cancer represents the fourth cause of death in women worldwide. One of the efforts to decrease this mortality has focused on implementing automatic tools for supporting the experts i...

A time series is a collection of values made or recorded over time. Dynamic Time Warping (DTW) is an algorithm for measuring similarity between two time series. DTW is one the most successful similari...

A symbolic representation for any data can be used as a tool for reducing the irrelevant noise. Any methods of reducing noise are extremely useful in the field of financial data, where a good trading ...

A myriad of data is produced in intensive care units (ICU) even for short periods of time. This data is frequently used for monitoring patient’s immediate health status, not for real-time analysis bec...

A modified framework, that applies temporal association rule mining to financial time series, is proposed in this paper. The top four components stocks of Dow Jones Industrial Average DJIA in terms of...

A modified framework, that applies temporal association rule mining to financial time series, is proposed in this paper. The top four components stocks (stock price time series, in USD) of Dow Jones I...