Time-series clustering–a decade review
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …
about classes. With emerging new concepts like cloud computing and big data and their vast …
Time-series data mining
P Esling, C Agon - ACM Computing Surveys (CSUR), 2012 - dl.acm.org
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 …
lead to a collection of organized data called time series. The purpose of time-series data …
A review on time series data mining
T Fu - Engineering Applications of Artificial Intelligence, 2011 - Elsevier
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 …
scientific and financial applications. A time series is a collection of observations made …
Review of low voltage load forecasting: Methods, applications, and recommendations
The increased digitalisation and monitoring of the energy system opens up numerous
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
opportunities to decarbonise the energy system. Applications on low voltage, local networks …
Experimental comparison of representation methods and distance measures for time series data
The previous decade has brought a remarkable increase of the interest in applications that
deal with querying and mining of time series data. Many of the research efforts in this context …
deal with querying and mining of time series data. Many of the research efforts in this context …
Querying and mining of time series data: experimental comparison of representations and distance measures
The last decade has witnessed a tremendous growths of interests in applications that deal
with querying and mining of time series data. Numerous representation methods for …
with querying and mining of time series data. Numerous representation methods for …
[KNIHA][B] Anomaly detection
Anomaly detection problems arise in multiple applications, as discussed in the preceding
chapter. such as financial fraud, cyber intrusion, video surveillance, and medical image …
chapter. such as financial fraud, cyber intrusion, video surveillance, and medical image …
Multivariate time series classification with parametric derivative dynamic time war**
Multivariate time series (MTS) data are widely used in a very broad range of fields, including
medicine, finance, multimedia and engineering. In this paper a new approach for MTS …
medicine, finance, multimedia and engineering. In this paper a new approach for MTS …
Return of the lernaean hydra: Experimental evaluation of data series approximate similarity search
Data series are a special type of multidimensional data present in numerous domains,
where similarity search is a key operation that has been extensively studied in the data …
where similarity search is a key operation that has been extensively studied in the data …
Comparing similarity perception in time series visualizations
A common challenge faced by many domain experts working with time series data is how to
identify and compare similar patterns. This operation is fundamental in high-level tasks, such …
identify and compare similar patterns. This operation is fundamental in high-level tasks, such …