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Application of text mining in analysing road crashes for road asset management

Nayak, Richi, Piyatrapoomi, Noppadol, & Weligamage, Justin (2009) Application of text mining in analysing road crashes for road asset management. In Proceedings of the 4th World Congress on Engineering Asset Management (WCEAM 2009), World Congress on Engineering Asset Management , Athens Ledra Marriott Hotel, Greece.

Abstract

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

Impact and interest:

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ID Code: 30079
Item Type: Conference Paper
Additional URLs:
Keywords: Data Mining, Text Mining, Road Safety
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Information Technology
Copyright Owner: Copyright 2009 [please consult the authors]
Deposited On: 29 Jan 2010 13:51
Last Modified: 01 Mar 2012 00:13

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