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ICDE
2005
IEEE

Knowledge Discovery from Transportation Network Data

9 years 6 months ago
Knowledge Discovery from Transportation Network Data
Transportation and Logistics are a major sector of the economy, however data analysis in this domain has remained largely in the province of optimization. The potential of data mining and knowledge discovery techniques is largely untapped. Transportation networks are naturally represented as graphs. This paper explores the problems in mining of transportation network graphs: We hope to find how current techniques both succeed and fail on this problem, and from the failures, we hope to present new challenges for data mining. Experimental results from applying both existing graph mining and conventional data mining techniques to real transportation network data are provided, including new approaches to making these techniques applicable to the problems. Reasons why these techniques are not appropriate are discussed. We also suggest several challenging problems to precipitate research and galvanize future work in this area.
Wei Jiang, Jaideep Vaidya, Zahir Balaporia, Chris
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2005
Where ICDE
Authors Wei Jiang, Jaideep Vaidya, Zahir Balaporia, Chris Clifton, Brett Banich
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