Ontological Approach to Personalized Situational Planning: Concept and Scenarios

Tang, Zi‐Qiang; Pyshkin, Evgeny

doi:10.1109/iucc/dsci/smartcns.2019.00118

Cited by 1 publication

(4 citation statements)

References 18 publications

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“…Some various approach was conducted at the existing research in different regions. Ten papers were selected at final review: [8], [9], [10], [21], [22], [23], [24], [25], [26], [27].…”

Section: B Digital Tourismmentioning

confidence: 99%

“…The author in [10] used blockchain technology to develop a tourism information intelligent service platform for tourism enterprises, tourists, government and promoted tourism management and service coordination, and economic development in China. In [21], it was developed a system to automatically recommend tourists to visit a particular tourist destination through an ontological approach. This approach included current situation detection such as location, existing fixed schedule, time, means of transportation, place accessibility to visit Japan in 2019.…”

Section: B Digital Tourismmentioning

confidence: 99%

“…Tourism Management 2 [23], [24] Tourist Experience 7 [22], [21], [10], [9], [25], [26], [27] Tourist Motivation 1 [8] TOTAL 10…”

Section: ∑ Papers Selected Papersmentioning

confidence: 99%

“…All of them can be seen in Table IX. Web Site 3 [10], [25], [26] Questionnaire 1 [8] Google Map 1 [10] Paper/ Report 8 [22], [21], [9], [23], [25], [24], [26], [27] TOTAL 14…”

Section: ∑ Papers Selected Papersmentioning

confidence: 99%

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Smart Tourism Recommendation Model: A Systematic Literature Review

Huda¹,

Ramadhan²,

Trisetyarso³

et al. 2021

IJACSA

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The tourism industry has become a potential sector to leverage economic growth. Many attractions are detected on several platforms. Machine learning and data mining are some potential technologies to improve the service of tourism by providing recommendations for a specific attraction for tourists according to their location and profile. This research applied for a systematic literature review on tourism, digital tourism, smart tourism, and recommender system in tourism. This research aims to evaluate the most relevant and accurate techniques in tourism that focused on recommendations or similar efforts. Several research questions were defined and translated into search strings. The result of this research was promoting 41 research that discussed tourism, digital tourism, smart tourism, and recommender systems. All of the literature was reviewed on some aspects, in example the problem addressed, methodology used, data used, strength, and the limitation that can be an opportunity for improvement in future research. This study proposed some references for further study based on reviewed papers regarding tourism management, tourist experience, tourist motivation, and tourist recommendation system. The opportunities for a further research study can be conducted with more data usage especially for a smart recommender system in tourism through many types of recommendation techniques such as content-based, collaborative filtering, demographic, knowledge-based, community-based, and hybrid recommender systems.

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“…Some various approach was conducted at the existing research in different regions. Ten papers were selected at final review: [8], [9], [10], [21], [22], [23], [24], [25], [26], [27].…”

Section: B Digital Tourismmentioning

confidence: 99%

Section: B Digital Tourismmentioning

confidence: 99%

“…Tourism Management 2 [23], [24] Tourist Experience 7 [22], [21], [10], [9], [25], [26], [27] Tourist Motivation 1 [8] TOTAL 10…”

Section: ∑ Papers Selected Papersmentioning

confidence: 99%

“…All of them can be seen in Table IX. Web Site 3 [10], [25], [26] Questionnaire 1 [8] Google Map 1 [10] Paper/ Report 8 [22], [21], [9], [23], [25], [24], [26], [27] TOTAL 14…”

Section: ∑ Papers Selected Papersmentioning

confidence: 99%

See 2 more Smart Citations