A model-based multivariate time series clustering algorithm

Pei Yuan Zhou, Chun Chung Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

11 Citations (Scopus)

Abstract

Given a set of multivariate time series, the problem of clustering such data is concerned with the discovering of inherent groupings of the data according to how similar or dissimilar the time series are to each other. Existing time series clustering algorithms can divide into three types, raw-based, feature-based and model-based. In this paper, a model-based multivariate time series clustering algorithm is proposed and its tasks in several steps: (i)data transformation, (ii)discovering time series temporal patterns using confidence value to represent the relationship between different variables, (iii) clustering of multi-variate time series based on the degree of patterns discovering in (ii). For evaluate performance of proposed algorithm, the proposed algorithm is tested with both synthetic data and real data. The result shows that it can be promising algorithm for multivariate time series clustering.

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8643
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshops on Data Mining and Decision Analytics for Public Health, Biologically Inspired Data Mining Techniques, Mobile Data Management, Mining, and Computing on Social Networks, Big Data Science and Engineering on E-Commerce, Cloud Service Discovery, MSMV-MBI, Scalable Dats Analytics, Data Mining and Decision Analytics for Public Health and Wellness, Algorithms for Large-Scale Information Processing in Knowledge Discovery, Data Mining in Social Networks, Data Mining in Biomedical informatics and Healthcare, Pattern Mining and Application of Big Data in conjunction with 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2014
CountryTaiwan
CityTainan
Period13/05/1416/05/14

Keywords

  • Model-based clustering algorithm
  • Multivariate time series
  • Time series clustering

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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