Towards a rough classification of business travelers

Chun Hung Roberts Law; Thomas Bauer; Karin Weber; Sze Ming Tse

Towards a rough classification of business travelers

Chun Hung Roberts Law, Thomas Bauer, Karin Weber, Sze Ming Tse

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

9 Citations (Scopus)

Abstract

The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.

Original language	English
Title of host publication	Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings
Publisher	Springer Verlag
Pages	135-142
Number of pages	8
ISBN (Electronic)	9783540370253
ISBN (Print)	3540370250
Publication status	Published - 1 Jan 2006
Event	2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 - Xi'an, China Duration: 14 Aug 2006 → 16 Aug 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4093 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Advanced Data Mining and Applications, ADMA 2006
Country/Territory	China
City	Xi'an
Period	14/08/06 → 16/08/06

ASJC Scopus subject areas

General Computer Science
Theoretical Computer Science

Cite this

Law, C. H. R., Bauer, T., Weber, K., & Tse, S. M. (2006). Towards a rough classification of business travelers. In Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings (pp. 135-142). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4093 LNAI). Springer Verlag.

Law, Chun Hung Roberts ; Bauer, Thomas ; Weber, Karin et al. / Towards a rough classification of business travelers. Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. Springer Verlag, 2006. pp. 135-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{6904fdfb6a8543ebaf51fdbabbe21432,

title = "Towards a rough classification of business travelers",

abstract = "The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.",

author = "Law, {Chun Hung Roberts} and Thomas Bauer and Karin Weber and Tse, {Sze Ming}",

year = "2006",

month = jan,

day = "1",

language = "English",

isbn = "3540370250",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "135--142",

booktitle = "Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings",

address = "Germany",

note = "2nd International Conference on Advanced Data Mining and Applications, ADMA 2006 ; Conference date: 14-08-2006 Through 16-08-2006",

}

Law, CHR, Bauer, T, Weber, K & Tse, SM 2006, Towards a rough classification of business travelers. in Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4093 LNAI, Springer Verlag, pp. 135-142, 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, Xi'an, China, 14/08/06.

Towards a rough classification of business travelers. / Law, Chun Hung Roberts; Bauer, Thomas; Weber, Karin et al.
Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings. Springer Verlag, 2006. p. 135-142 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4093 LNAI).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Towards a rough classification of business travelers

AU - Law, Chun Hung Roberts

AU - Bauer, Thomas

AU - Weber, Karin

AU - Tse, Sze Ming

PY - 2006/1/1

Y1 - 2006/1/1

N2 - The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.

AB - The significant economic contributions of the fast growing tourism industry have drawn worldwide attention on understanding the behavioral and demographic patterns of visitors. This research makes an attempt to develop a rough sets based model that can capture the essential information from business travelers, a segment of the market that to date has been entirely overlooked by academic researchers in data mining. Utilizing the primary data collected from an Omnibus survey carried out in Hong Kong in late 2005, experimental findings showed that the induced decision rules could classify 82% of the cases in the testing set and 41% of the classified cases were correctly estimated. Most importantly, there was no statistically significant difference between the estimated values and actual values.

UR - http://www.scopus.com/inward/record.url?scp=33749413717&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 3540370250

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 135

EP - 142

BT - Advanced Data Mining and Applications - Second International Conference, ADMA 2006, Proceedings

PB - Springer Verlag

T2 - 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006

Y2 - 14 August 2006 through 16 August 2006

ER -

Towards a rough classification of business travelers

Abstract

Publication series

Conference

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this