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A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining

R. Sarala1 , V. Saravanan2

  1. Hindusthan College of Arts and Science, Coimbatore, Tamil Nadu, India.
  2. Department of IT, Hindusthan College of Arts and Science, Coimbatore, Tamil Nadu, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 317-324, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.317324

Online published on May 31, 2018

Copyright © R. Sarala, V. Saravanan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R. Sarala, V. Saravanan, “A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.317-324, 2018.

MLA Style Citation: R. Sarala, V. Saravanan "A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining." International Journal of Computer Sciences and Engineering 6.5 (2018): 317-324.

APA Style Citation: R. Sarala, V. Saravanan, (2018). A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining. International Journal of Computer Sciences and Engineering, 6(5), 317-324.

BibTex Style Citation:
@article{Sarala_2018,
author = {R. Sarala, V. Saravanan},
title = {A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {317-324},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1979},
doi = {https://doi.org/10.26438/ijcse/v6i5.317324}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.317324}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1979
TI - A Comparative Study on Spatio-Temporal Data Correlation and Pattern Discovery Techniques for Prediction Mining
T2 - International Journal of Computer Sciences and Engineering
AU - R. Sarala, V. Saravanan
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 317-324
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

A spatiotemporal database handles both the space and time information. A spatiotemporal database includes spatial (i.e., location and geometry of the object) and temporal data (i.e., timestamp or time interval of valid objects) where geometry of object changes over time. Spatio-temporal correlation analysis is used for identifying the spatial and temporal relationships of multiple events. The spatio-temporal objects contain number of features in pattern discovery process. However, the existing spatio-temporal pattern discovery and prediction techniques are failed to predict the future event in accurate manner and time consumption remained unaddressed. Our main objective of the research is the spatio-temporal correlation, spatio-temporal pattern discovery and prediction with higher accuracy. In order to increase the performance of spatio-temporal pattern discovery and prediction, machine learning technique are employed in our work.

Key-Words / Index Term

Spatiotemporal database, correlation analysis, features, pattern discovery, prediction, machine learning technique

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