2011 ATaxiBusinessIntelligenceSystem

• (Ge et al., 2011) ⇒ Yong Ge, Chuanren Liu, Hui Xiong, and Jian Chen. (2011). “A Taxi Business Intelligence System.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011). doi:10.1145/2020408.2020523

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Cited By

• http://scholar.google.com/scholar?q=%22A+taxi+business+intelligence+system%22+2011
• http://portal.acm.org/citation.cfm?doid=2020408.2020523&preflayout=flat#citedby

Quotes

Abstract

The increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for knowledge discovery in transportation systems. A particularly promising area is to extract useful business intelligence, which can be used as guidance for reducing inefficiencies in energy consumption of transportation sectors, improving customer experiences, and increasing business performances. However, extracting business intelligence from location traces is not a trivial task. Conventional data analytic tools are usually not customized for handling large, complex, dynamic, and distributed nature of location traces. To that end, we develop a taxi business intelligence system to explore the massive taxi location traces from different business perspectives with various data mining functions. Since we implement the system using the real-world taxi GPS data, this demonstration will help taxi companies to improve their business performances by understanding the behaviors of both drivers and customers. In addition, several identified technical challenges also motivate data mining people to develop more sophisticate techniques in the future.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 ATaxiBusinessIntelligenceSystem	Jian Chen Hui Xiong Chuanren Liu			A Taxi Business Intelligence System				10.1145/2020408.2020523