A causal analysis for the expenditure data of business travelers

Chun Hung Roberts Law, Gang Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


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.
Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications - Third International Conference, ADMA 2007, Proceedings
Number of pages8
Publication statusPublished - 1 Dec 2007
Event3rd International Conference on Advanced Data Mining and Applications, ADMA 2007 - Harbin, China
Duration: 6 Aug 20078 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4632 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Advanced Data Mining and Applications, ADMA 2007

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this