DocumentCode :
3081635
Title :
Analysis of Spatial Autocorrelation for Traffic Accident Data Based on Spatial Decision Tree
Author :
Ghimire, Bishad ; Bhattacharjee, Sangeeta ; Ghosh, Soumya K.
Author_Institution :
Inst. of Eng. (IOE), Dept. of Comput. & Electron, Tribhuvan Univ., Purwanchal, Nepal
fYear :
2013
fDate :
22-24 July 2013
Firstpage :
111
Lastpage :
115
Abstract :
With rapid increase of scope, coverage and volume of geographic datasets, knowledge discovery from spatial data have drawn a lot of research interest for last few decades. Traditional analytical techniques cannot easily discover new, implicit patterns, and relationships that are hidden into geographic datasets. The principle of this work is to evaluate the performance of traditional and spatial data mining techniques for analysing spatial certainty, such as spatial autocorrelation. Analysis is done by classification technique, i.e. a Decision Tree (DT) based approach on a spatial diversity coefficient. ID3 (Iterative Dichotomiser 3) algorithm is used for building the conventional and spatial decision trees. A synthetically generated spatial accident dataset and real accident dataset are used for this purpose. The spatial DT (SDT) is found to be more significant in spatial decision making.
Keywords :
accident prevention; data mining; decision making; decision trees; geographic information systems; iterative methods; pattern classification; road traffic; DT-based approach; ID3 algorithm; SDT; classification technique; decision tree-based approach; geographic datasets; iterative dichotomiser 3 algorithm; knowledge discovery; spatial autocorrelation; spatial data mining techniques; spatial decision making; spatial decision tree-based traffic accident data; spatial diversity coefficient; Accidents; Correlation; Data mining; Decision trees; Entropy; Roads; Spatial databases; Spatial Autocorrelation; Spatial Decision Tree; Spatial Knowledge Discovery; Traffic Accident Data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing for Geospatial Research and Application (COM.Geo), 2013 Fourth International Conference on
Conference_Location :
San Jose, CA
Type :
conf
DOI :
10.1109/COMGEO.2013.19
Filename :
6602050
Link To Document :
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