Data mining in tourism demand analysis: A retrospective analysis

Chun Hung Roberts Law; Henry Mok; Carey Goh

Data mining in tourism demand analysis: A retrospective analysis

Chun Hung Roberts Law, Henry Mok, Carey Goh

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

12 Citations (Scopus)

Abstract

Despite numerous studies have applied various forecasting models to tourism demand analysis, data mining techniques have been largely overlooked by academic researchers in tourism forecasting prior to 1999. Based on our review of published articles in tourism journals that applied data mining techniques to tourism demand forecasting, we find that the application of data mining techniques are still at their infancy. This paper concludes with practical implications and future research areas.

Original language	English
Title of host publication	Advanced Data Mining and Applications - Third International Conference, ADMA 2007, Proceedings
Pages	508-515
Number of pages	8
Publication status	Published - 1 Dec 2007
Event	3rd International Conference on Advanced Data Mining and Applications, ADMA 2007 - Harbin, China Duration: 6 Aug 2007 → 8 Aug 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4632 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Advanced Data Mining and Applications, ADMA 2007
Country/Territory	China
City	Harbin
Period	6/08/07 → 8/08/07

Keywords

Business applications
Data mining
Demand forecasting
Tourism

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

Law, C. H. R., Mok, H., & Goh, C. (2007). Data mining in tourism demand analysis: A retrospective analysis. In Advanced Data Mining and Applications - Third International Conference, ADMA 2007, Proceedings (pp. 508-515). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4632 LNAI).

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title = "Data mining in tourism demand analysis: A retrospective analysis",

abstract = "Despite numerous studies have applied various forecasting models to tourism demand analysis, data mining techniques have been largely overlooked by academic researchers in tourism forecasting prior to 1999. Based on our review of published articles in tourism journals that applied data mining techniques to tourism demand forecasting, we find that the application of data mining techniques are still at their infancy. This paper concludes with practical implications and future research areas.",

keywords = "Business applications, Data mining, Demand forecasting, Tourism",

author = "Law, {Chun Hung Roberts} and Henry Mok and Carey Goh",

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

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Law, CHR, Mok, H & Goh, C 2007, Data mining in tourism demand analysis: A retrospective analysis. in Advanced Data Mining and Applications - Third International Conference, ADMA 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4632 LNAI, pp. 508-515, 3rd International Conference on Advanced Data Mining and Applications, ADMA 2007, Harbin, China, 6/08/07.

Data mining in tourism demand analysis: A retrospective analysis. / Law, Chun Hung Roberts; Mok, Henry; Goh, Carey.

Advanced Data Mining and Applications - Third International Conference, ADMA 2007, Proceedings. 2007. p. 508-515 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4632 LNAI).

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

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N2 - Despite numerous studies have applied various forecasting models to tourism demand analysis, data mining techniques have been largely overlooked by academic researchers in tourism forecasting prior to 1999. Based on our review of published articles in tourism journals that applied data mining techniques to tourism demand forecasting, we find that the application of data mining techniques are still at their infancy. This paper concludes with practical implications and future research areas.

AB - Despite numerous studies have applied various forecasting models to tourism demand analysis, data mining techniques have been largely overlooked by academic researchers in tourism forecasting prior to 1999. Based on our review of published articles in tourism journals that applied data mining techniques to tourism demand forecasting, we find that the application of data mining techniques are still at their infancy. This paper concludes with practical implications and future research areas.

KW - Business applications

KW - Data mining

KW - Demand forecasting

KW - Tourism

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Data mining in tourism demand analysis: A retrospective analysis

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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