Time series shapelets are a recent promising concept in time series data mining. Shapelets
are time series snippets that can be used to classify unlabeled time series. Shapelets not …

The ubiquity of time series data across almost all human endeavors has produced a great
interest in time series data mining in the last decade. While dozens of classification …

Recent years have seen significant progress in improving both the efficiency and
effectiveness of time series classification. However, because the best solution is typically the …

Thanks to the rapid proliferation of connected devices, sensor-generated time series
constitute a large and growing portion of the world's data. Often, this data is collected from …

In this paper, we present TACO (Textual Analysis for Code Smell Detection), a technique
that exploits textual analysis to detect a family of smells of different nature and different …

A concerted research effort over the past two decades has heralded significant
improvements in both the efficiency and effectiveness of time series classification. The …

Most literature on time series classification assumes that the beginning and ending points of
the pattern of interest can be correctly identified, both during the training phase and later …

The ability to make predictions about future events is at the heart of much of science; so, it is
not surprising that prediction has been a topic of great interest in the data mining community …

Mining patterns is a core task in data analysis and, beyond issues of efficient enumeration,
the selection of patterns constitutes a major challenge. The Minimum Description Length …

Multidimensional Scaling (MDS) is one of the most versatile tools used for exploratory data
mining. It allows a first glimpse of possible structure in the data, which can inform the choice …