Authors:
Chun-Hung Cheng
1
;
Chon-Huat Goh
2
and
Anita Lee-Post
3
Affiliations:
1
The Chinese University of Hong Kong, Hong Kong
;
2
School of Business, Rutgers University, United States
;
3
School of Management, University of Kentucky, United States
Keyword(s):
Internet Survey Data, Quality, TSP, genetic algorithm.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
e-Business and e-Commerce
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
Abstract:
In this work, we propose to develop a procedure to detect errors in data collected through Internet surveys.
Although several approaches have been developed, they suffer many limitations. For instance, many
approaches require prior knowledge of data and hence they need different procedures for different
applications. Others have to test a large number of parameter values and hence they are not very efficient.
To develop a procedure to overcome the limitations of existing approaches, we try to understand the nature
of this quality problem and establish its linkage to travelling salesman problem (TSP). Based on the TSP
problem structure, we propose to develop a two-staged approach based on a genetic algorithm to help ensure
the quality of Internet survey data.