A survey on time series data mining

Amin Fakhrazari, Hamid Vakilzadian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, an overview on existing data mining techniques for time series modeling and analysis will be provided. Classification of available literature on time series data mining shows that the main research orientations can be divided into three subfields: Dimensionality Reduction (Time Series Representation), Similarity Measures and Data Mining Tasks.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Electro Information Technology, EIT 2017
PublisherIEEE Computer Society
Pages476-481
Number of pages6
ISBN (Electronic)9781509047673
DOIs
Publication statusPublished - Sep 27 2017
Event2017 IEEE International Conference on Electro Information Technology, EIT 2017 - Lincoln, United States
Duration: May 14 2017May 17 2017

Publication series

NameIEEE International Conference on Electro Information Technology
ISSN (Print)2154-0357
ISSN (Electronic)2154-0373

Other

Other2017 IEEE International Conference on Electro Information Technology, EIT 2017
CountryUnited States
CityLincoln
Period5/14/175/17/17

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Keywords

  • Time series analysis
  • artificial intelligence
  • data mining
  • machine learning

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Fakhrazari, A., & Vakilzadian, H. (2017). A survey on time series data mining. In 2017 IEEE International Conference on Electro Information Technology, EIT 2017 (pp. 476-481). [8053409] (IEEE International Conference on Electro Information Technology). IEEE Computer Society. https://doi.org/10.1109/EIT.2017.8053409