A Framework of Implications for Smart Tourism Development in Hong Kong

Ye, Huiyue; Zhang, Ke; Law, Rob

doi:10.52255/smarttourism.2021.1.1.5

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…In addition to providing knowledge sharing, intelligent management, and other functions, the author believes that the purpose of smart tourism development is to provide tourists with more efficient and personalized high-quality tourism services [ 4 ]. The recommendation of personalized tourism routes is not only an important topic for the future of smart tourism but also one of the important solutions to provide users with personalized tourism services.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Personalized Scenic Spot Recommendation Algorithm Based on Generalized Regression Neural Network for 5G Smart Tourism System

Lin

2022

Computational Intelligence and Neuroscience

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On the basis of the analysis of the evolution dynamics and the process of smart tourism service, this paper constructs the evolutionary game model of smart tourism service and reveals the evolution mechanism of smart tourism service based on the network platform. Based on the strategic main line of “advantages,” it proposes the design ideas and overall framework of the smart tourism service model based on the network platform, including the smart tourism information interactive service model, the element collaborative service model, and the value cocreation service model. The comparison of recommendation results shows that the recommendation error of the genetically improved generalized regression neural network algorithm is reduced, and the recommendation accuracy is better than that of the unimproved generalized regression neural network algorithm. In the recommendation scenario of click-through rate recommendation, the existing recommendation models are difficult to meet the functions of memory and generalization at the same time and cannot fully mine and combine low-level features, and the model parameters of the deep learning model are difficult to learn under the high-dimensional sparse data set of the recommendation system. To solve the problem of generalization, this paper proposes a deep CTR recommendation model based on the gradient boosting tree and factorization machine. It can fully mine low-level feature information and automatically realize low-level feature combination, which can better learn model parameters on high-dimensional sparse data sets, and the recommendation results are no longer overgeneralized. In this paper, simulation experiments are carried out on the data set, and the related recommendation models are compared. The experimental results show that the model proposed in this paper achieves better results in both the AUC (area under ROC curve) evaluation index and the cross-entropy evaluation index.

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Section: Introductionmentioning

confidence: 99%

Implementation of Personalized Scenic Spot Recommendation Algorithm Based on Generalized Regression Neural Network for 5G Smart Tourism System

Lin

2022

Computational Intelligence and Neuroscience

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“…e construction of "smart tourism" is still in its infancy, and the construction of data centers, servers, and users is being carried out one after another [1,2]. e core of information system construction is data, and smart tourism construction is based on "smart data," using various modern information technologies to realize modern smart tourism services for tourists, managers, and enterprises [3]. According to the system and requirements of smart tourism, the intelligent integration of tourism data conforms to the overall construction ideas and speci cations of smart tourism.…”

Section: Introductionmentioning

confidence: 99%

Construction of a Virtual Reality Model of Smart Tourism Scenic Spot Based on Cloud Computing

2022

Mathematical Problems in Engineering

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This paper studies the technology and cloud platform of “cloud computing” in detail. Technically, this paper studies Map-Reduce, HDFS, and BigTable in cloud platform technology. Using the theoretical thinking of comprehensive advantages, the design ideas and principles of the smart tourism service model based on the network platform are proposed, and the overall architecture of the smart tourism service model based on the network platform is constructed according to the three dimensions of the tourist demand level, network platform development stage, and service resource aggregation and integration. The virtual network interaction platform is realized through Unity3D combined with Web3D technology, and the system interaction function is realized according to the communication principle of the front and back of the web page, including the fast switching of scenic spots, the selection of roaming methods, and the realization of navigation maps. In the user evaluation stage, usability and user satisfaction of the system were effectively measured by the SUS system usability scale and the heuristic experiment combined with Likert scale. The virtual reality system of smart tourist attractions based on somatosensory interaction integrates immersion, interactivity, gameplay, education, and dissemination. It can break the time and space barriers for the creation and experience of smart tourist attractions, improve the extremely cold experience environment of smart tourist attractions, increase the display and publicity dimensions of smart tourist attractions, change the situation of one-way passive reception of traditional smart tourist attractions, and improve the interaction and interaction of tourists. It also provides new teaching and design methods for creators of smart tourism scenic spots, which is conducive to the promotion of teaching in smart tourism scenic spots. It enhances the importance of ice and snow culture in the ice and snow industry, changes the traditional business model of ice and snow scenic spots, and uses modern technology to make up for the cultural development defects of smart tourism scenic spots. The digital sustainable development construction of smart tourism scenic spots provides new ideas.

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