A Causal Analysis for the Expenditure Data of Business Travelers

  • Rob Law
  • Gang Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4632)


Determining the causal relation among attributes in a domain is a key task in the data mining and knowledge discovery. In this paper, we applied a causal discovery algorithm to the business traveler expenditure survey data [1]. A general class of causal models is adopted in this paper to discover the causal relationship among continuous and discrete variables. All those factors which have direct effect on the expense pattern of travelers could be detected. Our discovery results reinforced some conclusions of the rough set analysis and found some new conclusions which might significantly improve the understanding of expenditure behaviors of the business traveler.


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Rob Law
    • 1
  • Gang Li
    • 2
  1. 1.School of Hotel and Tourism Management, Hong Kong Polytechnic UniversityHong Kong
  2. 2.School of Engineering and Information Technology, Deakin University, 221 Burwood Highway, Vic 3125Australia

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