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Published in 2018 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-018-0573-y
Abstract: Constrained clustering is becoming an increasingly popular approach in data mining. It offers a balance between the complexity of producing a formal definition of thematic classes—required by supervised methods—and unsupervised approaches, which ignore expert knowledge…
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Keywords:
time series;
clustering time;
distance;
time ... See more keywords
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Published in 2019 at "Statistics and Computing"
DOI: 10.1007/s11222-018-9830-6
Abstract: We present a new way to find clusters in large vectors of time series by using a measure of similarity between two time series, the generalized cross correlation. This measure compares the determinant of the…
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Keywords:
series linear;
time series;
clustering time;
series ... See more keywords
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Published in 2020 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2020.2970455
Abstract: In this article, we propose a two-stage time-series clustering approach to cluster time series with different shapes. The first step is to represent the time series by a suite of information granules following the principle…
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Keywords:
fuzzy clustering;
information;
time series;
clustering time ... See more keywords
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Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3184999
Abstract: This article aims to design a trend-oriented-granulation-based fuzzy C -means (FCM) algorithm that can cluster a group of time series at an abstract (granular) level. To achieve a better trend-oriented granulation of a time series,…
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Keywords:
time;
time series;
granule;
clustering time ... See more keywords