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Exploiting IoT Data Crossings for Gradual Pattern Mining Through Parallel Processing

Dickson Owuor 1, 2 Anne Laurent 1 Joseph Onderi Orero 2
1 FADO - Fuzziness, Alignments, Data & Ontologies
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Today, with the proliferation of Internet of Things (IoT) applications in almost every area of our society comes the trouble of deducing relevant information from real-time time-series data (from different sources) for decision making. In this paper, we propose a fuzzy temporal approach for crossing such data sets with the ultimate goal of exploiting them for temporal gradual pattern mining. A temporal gradual pattern may take the form: “the higher the humidity, the lower the temperature, almost 15 min later”. In addition, we apply parallel processing on our implementation and measure its computational performance.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03207259
Contributor : Anne Laurent <>
Submitted on : Saturday, April 24, 2021 - 11:39:02 AM
Last modification on : Thursday, April 29, 2021 - 3:36:40 AM

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Dickson Owuor, Anne Laurent, Joseph Onderi Orero. Exploiting IoT Data Crossings for Gradual Pattern Mining Through Parallel Processing. ADBIS, TPDL and EDA 2020 Common Workshops, Aug 2020, Lyon, France. pp.110-121, ⟨10.1007/978-3-030-55814-7_9⟩. ⟨lirmm-03207259⟩

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