Last decades witness a huge growth in medical applications, genetic analysis, and in
performance of manufacturing technologies and automatised production systems. A …

Time series motifs are repeated segments in a long time series that, if exist, carry precise
information about the underlying source of the time series. Motif discovery in time series data …

Time series motifs are repeated patterns in long and noisy time series. Motifs are typically
used to understand the dynamics of the source because repeated patterns with high …

This paper has been prompted by observations of disparities between the observed fall-off
in irradiance for off-axis points and that accounted for by the cosine-fourth and vignetting …

Motifs are the most repetitive/frequent patterns of a time-series. The discovery of motifs is
crucial for practitioners in order to understand and interpret the phenomena occurring in …

In this paper, we introduce a new problem, called Top-k SAT, that consists in enumerating
the Top-k models of a propositional formula. A Top-k model is defined as a model with less …

As one of the most essential data mining tasks, finding frequently occurring patterns, ie, motif
discovery, has drawn a lot of attention in the past decade. Despite successes in speedup of …

Behavior exhibits a complex spatiotemporal structure consisting of discrete sub-behaviors,
or motifs. Continuous behavior data requires segmentation and clustering to reveal these …

Mining time series motifs is a fundamental, yet expensive task in exploratory data analytics.
In this paper, we therefore propose a fast method to find the top-k motifs with probabilistic …

Discovering frequent episodes over event sequences is an important data mining problem.
Existing methods typically require multiple passes over the data, rendering them unsuitable …