Discovering tourist preference for electing destinations: a pattern mining based approach

Md Rafiqul Islam; Munshi Muhammad Abdul Kader Jilani; Shah Jahan Miah; Sanjita Akter; Anwaar Ulhaq

doi:10.1080/10941665.2021.1954676

Discovering tourist preference for electing destinations: a pattern mining based approach

Md Rafiqul Islam, Munshi Muhammad Abdul Kader Jilani, Shah Jahan Miah, Sanjita Akter, Anwaar Ulhaq

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

Awareness and access to information on travel benefits may bear importance for tourist preference in selecting popular destination. Tourism businesses are continuously exploring to improve their competitive advantage and offering an effective method for assisting tourist in electing their preferred destinations. However, current studies are still at an emergent stage. This paper presents a tourists preferences dataset and introduces preference pattern mining (PPM) method as a solution framework for discovering tourist spots. Our PPM method finds and validates the most active tourist hot spots from tourist preferences dataset. The proposed framework facilitates an unbiased approach for optimal tourism destination management in tourism-friendly countries.

Original language	English
Pages (from-to)	1081-1096
Number of pages	16
Journal	Asia Pacific Journal of Tourism Research
Volume	26
Issue number	10
DOIs	https://doi.org/10.1080/10941665.2021.1954676
Publication status	Published - 31 Aug 2021

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10.1080/10941665.2021.1954676

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title = "Discovering tourist preference for electing destinations: a pattern mining based approach",

abstract = "Awareness and access to information on travel benefits may bear importance for tourist preference in selecting popular destination. Tourism businesses are continuously exploring to improve their competitive advantage and offering an effective method for assisting tourist in electing their preferred destinations. However, current studies are still at an emergent stage. This paper presents a tourists preferences dataset and introduces preference pattern mining (PPM) method as a solution framework for discovering tourist spots. Our PPM method finds and validates the most active tourist hot spots from tourist preferences dataset. The proposed framework facilitates an unbiased approach for optimal tourism destination management in tourism-friendly countries.",

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T2 - a pattern mining based approach

AU - Islam, Md Rafiqul

AU - Abdul Kader Jilani, Munshi Muhammad

AU - Miah, Shah Jahan

AU - Akter, Sanjita

AU - Ulhaq, Anwaar

PY - 2021/8/31

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N2 - Awareness and access to information on travel benefits may bear importance for tourist preference in selecting popular destination. Tourism businesses are continuously exploring to improve their competitive advantage and offering an effective method for assisting tourist in electing their preferred destinations. However, current studies are still at an emergent stage. This paper presents a tourists preferences dataset and introduces preference pattern mining (PPM) method as a solution framework for discovering tourist spots. Our PPM method finds and validates the most active tourist hot spots from tourist preferences dataset. The proposed framework facilitates an unbiased approach for optimal tourism destination management in tourism-friendly countries.

AB - Awareness and access to information on travel benefits may bear importance for tourist preference in selecting popular destination. Tourism businesses are continuously exploring to improve their competitive advantage and offering an effective method for assisting tourist in electing their preferred destinations. However, current studies are still at an emergent stage. This paper presents a tourists preferences dataset and introduces preference pattern mining (PPM) method as a solution framework for discovering tourist spots. Our PPM method finds and validates the most active tourist hot spots from tourist preferences dataset. The proposed framework facilitates an unbiased approach for optimal tourism destination management in tourism-friendly countries.

KW - destination management

KW - Destination spots

KW - pattern mining

KW - tourism management

KW - tourist behaviour

KW - tourist preference

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Discovering tourist preference for electing destinations: a pattern mining based approach

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