Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23175
Title: Categorical classification of tourism dining
Authors: Au, N 
Law, R 
Keywords: Dining
Food
Forecasting
Hong Kong
Rough set
Issue Date: 2002
Publisher: Pergamon Press
Source: Annals of tourism research, 2002, v. 29, no. 3, p. 819-833 How to cite?
Journal: Annals of tourism research 
Abstract: Traditional quantitative techniques in foodservice and tourism are unable to discover hidden relationships from a database with numeric and non-numeric data. This paper reports on an initial study about applying an alternative approach that incorporates the rough set theory into relationship modeling in tourism dining. This theory deals with the non-numeric classification analysis of imprecise, uncertain, or incomplete knowledge by incorporating the classical set theory. Using officially published data on tourism dining, decision rules were generated which describe the relationship model. Empirical findings indicated that among the classified cases, 83% of the forecast values were identical to their actual counterparts.
URI: http://hdl.handle.net/10397/23175
ISSN: 0160-7383
EISSN: 1873-7722
DOI: 10.1016/S0160-7383(01)00078-0
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