The massive data generated by the Internet of Things (IoT) are considered of high business
value, and data mining algorithms can be applied to IoT to extract hidden information from …

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 …

Most time series data mining algorithms use similarity search as a core subroutine, and thus
the time taken for similarity search is the bottleneck for virtually all time series data mining …

Most time series data mining algorithms use similarity search as a core subroutine, and thus
the time taken for similarity search is the bottleneck for virtually all time series data mining …

Time series analysis, as an application for high dimensional data mining, is a common task
in biochemistry, meteorology, climate research, bio-medicine or marketing. Similarity search …

Current research in indexing and mining time series data has produced many interesting
algorithms and representations. However, the algorithms and the size of data considered …

There is an increasingly pressing need, by several applications in diverse domains, for
developing techniques able to index and mine very large collections of time series …

Eucalyptus, Open Nebula and Nimbus are three major open-source cloud-computing
software platforms. The overall function of these systems is to manage the provisioning of …

We propose Hashedcubes, a data structure that enables real-time visual exploration of large
datasets that improves the state of the art by virtue of its low memory requirements, low …

There is an increasingly pressing need, by several applications in diverse domains, for
developing techniques able to index and mine very large collections of time series …