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Comparative Study of Spatial Data Mining Techniques

by Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 14
Year of Publication: 2015
Authors: Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa
10.5120/19734-1528

Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa . Comparative Study of Spatial Data Mining Techniques. International Journal of Computer Applications. 112, 14 ( February 2015), 19-22. DOI=10.5120/19734-1528

@article{ 10.5120/19734-1528,
author = { Kamalpreet Kaur Jassar, Kanwalvir Singh Dhindsa },
title = { Comparative Study of Spatial Data Mining Techniques },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 14 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 19-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number14/19734-1528/ },
doi = { 10.5120/19734-1528 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:49:28.487908+05:30
%A Kamalpreet Kaur Jassar
%A Kanwalvir Singh Dhindsa
%T Comparative Study of Spatial Data Mining Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 14
%P 19-22
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Spatial data mining is a mining knowledge from large amounts of spatial data. Spatial data mining algorithms can be separated into four general categories: clustering and outlier detection, association and co-location method, trend detection and classification. All these methods have been compared according to various attributes. This paper introduces the fundamental concepts of widely known spatial data mining algorithms in a comparative way. It focuses on techniques and their unique features.

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Index Terms

Computer Science
Information Sciences

Keywords

Spatial clustering Clustering and Outlier Detection Association and Co-Location Classification Trend-Detection Clustering algorithms Knowledge Discovery in Database

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