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A taxi business intelligence system

A taxi business intelligence system A Taxi Business Intelligence System Yong Ge1 , Chuanren Liu1 , Hui Xiong1 , Jian Chen2 Rutgers Business School, Rutgers University yongge@pegasus.rutgers.edu, {hxiong, chuanren.liu}@rutgers.edu 2 Tsinghua University jchen@mail.tsinghua.edu.cn 1 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 ine ƒciencies 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 di €erent 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 identi ed technical challenges also motivate data mining people to develop more sophisticate techniques in the future. Categories and Subject Descriptors H.2.8 [Database http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A taxi business intelligence system

Association for Computing Machinery — Aug 21, 2011

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Datasource
Association for Computing Machinery
Copyright
Copyright © 2011 by ACM Inc.
ISBN
978-1-4503-0813-7
doi
10.1145/2020408.2020523
Publisher site
See Article on Publisher Site

Abstract

A Taxi Business Intelligence System Yong Ge1 , Chuanren Liu1 , Hui Xiong1 , Jian Chen2 Rutgers Business School, Rutgers University yongge@pegasus.rutgers.edu, {hxiong, chuanren.liu}@rutgers.edu 2 Tsinghua University jchen@mail.tsinghua.edu.cn 1 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 ine ƒciencies 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 di €erent 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 identi ed technical challenges also motivate data mining people to develop more sophisticate techniques in the future. Categories and Subject Descriptors H.2.8 [Database

There are no references for this article.