A review of strengths and weaknesses of spatio-temporal data analysis techniques

Chandima D. Tilakaratne; Liwan Liyanage-Hansen

doi:10.1109/iCMLDE.2018.00020

A review of strengths and weaknesses of spatio-temporal data analysis techniques

Chandima D. Tilakaratne, Liwan Liyanage-Hansen

Western Sydney University

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

3 Citations (Scopus)

Abstract

![CDATA[Spatio-temporal data is voluminuous, and its analysis is complex. This review of the strengths and weaknesses of selected widely applicable algorithms aims to assist the reader with the choice of methods such as clustering and prediction of real time spatio-temporal data for different types of applications.]]

Original language	English
Title of host publication	Proceedings of 2018 International Conference on Machine Learning and Data Engineering (iCMLDE 2018), 3-7 December 2018, Sydney, Australia
Publisher	IEEE
Pages	53-55
Number of pages	3
ISBN (Print)	9781728104041
DOIs	https://doi.org/10.1109/iCMLDE.2018.00020
Publication status	Published - 2019
Event	International Conference on Machine Learning and Data Engineering - Duration: 3 Dec 2018 → …

Conference

Conference	International Conference on Machine Learning and Data Engineering
Period	3/12/18 → …

Keywords

cluster analysis
evaluation
machine learning
real-time data processing
spatiotemporal analysis

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10.1109/iCMLDE.2018.00020

Cite this

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title = "A review of strengths and weaknesses of spatio-temporal data analysis techniques",

abstract = "![CDATA[Spatio-temporal data is voluminuous, and its analysis is complex. This review of the strengths and weaknesses of selected widely applicable algorithms aims to assist the reader with the choice of methods such as clustering and prediction of real time spatio-temporal data for different types of applications.]]",

keywords = "cluster analysis, evaluation, machine learning, real-time data processing, spatiotemporal analysis",

author = "Tilakaratne, {Chandima D.} and Liwan Liyanage-Hansen",

year = "2019",

doi = "10.1109/iCMLDE.2018.00020",

language = "English",

isbn = "9781728104041",

pages = "53--55",

booktitle = "Proceedings of 2018 International Conference on Machine Learning and Data Engineering (iCMLDE 2018), 3-7 December 2018, Sydney, Australia",

publisher = "IEEE",

note = "International Conference on Machine Learning and Data Engineering ; Conference date: 03-12-2018",

}

Tilakaratne, CD & Liyanage-Hansen, L 2019, A review of strengths and weaknesses of spatio-temporal data analysis techniques. in Proceedings of 2018 International Conference on Machine Learning and Data Engineering (iCMLDE 2018), 3-7 December 2018, Sydney, Australia. IEEE, pp. 53-55, International Conference on Machine Learning and Data Engineering, 3/12/18. https://doi.org/10.1109/iCMLDE.2018.00020

A review of strengths and weaknesses of spatio-temporal data analysis techniques. / Tilakaratne, Chandima D.; Liyanage-Hansen, Liwan.
Proceedings of 2018 International Conference on Machine Learning and Data Engineering (iCMLDE 2018), 3-7 December 2018, Sydney, Australia. IEEE, 2019. p. 53-55.

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

TY - GEN

T1 - A review of strengths and weaknesses of spatio-temporal data analysis techniques

AU - Tilakaratne, Chandima D.

AU - Liyanage-Hansen, Liwan

PY - 2019

Y1 - 2019

N2 - ![CDATA[Spatio-temporal data is voluminuous, and its analysis is complex. This review of the strengths and weaknesses of selected widely applicable algorithms aims to assist the reader with the choice of methods such as clustering and prediction of real time spatio-temporal data for different types of applications.]]

AB - ![CDATA[Spatio-temporal data is voluminuous, and its analysis is complex. This review of the strengths and weaknesses of selected widely applicable algorithms aims to assist the reader with the choice of methods such as clustering and prediction of real time spatio-temporal data for different types of applications.]]

KW - cluster analysis

KW - evaluation

KW - machine learning

KW - real-time data processing

KW - spatiotemporal analysis

UR - http://handle.westernsydney.edu.au:8081/1959.7/uws:51416

U2 - 10.1109/iCMLDE.2018.00020

DO - 10.1109/iCMLDE.2018.00020

M3 - Conference Paper

SN - 9781728104041

SP - 53

EP - 55

BT - Proceedings of 2018 International Conference on Machine Learning and Data Engineering (iCMLDE 2018), 3-7 December 2018, Sydney, Australia

PB - IEEE

T2 - International Conference on Machine Learning and Data Engineering

Y2 - 3 December 2018

ER -

A review of strengths and weaknesses of spatio-temporal data analysis techniques

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Conference

Keywords

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