A causal analysis for the expenditure data of business travelers

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.