The UCR time series archive–introduced in 2002, has become an important resource in the
time series data mining community, with at least one thousand published papers making use …

Time series clustering is the act of grou** time series data without recourse to a label.
Algorithms that cluster time series can be classified into two groups: those that employ a time …

In this paper we describe our submission to the IJCRS'15 Data Mining Competition, which is
concerned with prediction of dangerous concentrations of methane in longwalls of a Polish …

As the research in Ambient Assisted Living (AAL) matures, we expect that data generated
from AAL IoT devices will benefit from analysis by well established machine learning …

Unsupervised semantic segmentation in the time series domain is a much studied problem
due to its potential to detect unexpected regularities and regimes in poorly understood data …

Time series data are ubiquitous in human society and nature, and classification is one of the
most significant problems in the field of time series mining. Although it has been intensively …

At their core, many time series data mining algorithms reduce to reasoning about the shapes
of time series subsequences. This requires an effective distance measure, and for last two …

Background Consumer-grade wearable devices enable detailed recordings of heart rate
and step counts in free-living conditions. Recent studies have shown that summary statistics …

Collecting data at regular time nowadays is ubiquitous. The most widely used type of data
that is being collected and analyzed is financial data and sensor readings. Various …

With the rapid development of the Internet and the continuous progress of computer science
and technology, Internet-based online trading has developed rapidly and improved the …