Personalized Recommendation of Rural Tourism Based on Traffic Classification and User Data Analysis

Bi, Wei; Wang, Guangming; Zhang, Meijuan

doi:10.1155/2022/4434833

Cited by 4 publications

(3 citation statements)

References 26 publications

(24 reference statements)

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“…On the other hand, large amount of online information could be overwhelming and negatively influence their tourism experience during the stay. Offering people information, goods and other services based on their requirements, individualized information and personal interests is one way to combat the issue of information overload (Bi et al, 2022). Thus, customization of mobile application services and promotions is necessary in order to satisfy the heterogeneous needs of modern rural tourists.…”

Section: Resultsmentioning

confidence: 99%

Developing a “Smart Village” through the Implementation of Mobile Applications

2022

Proceedings of the the International Scientific Conference in the Field Of Tourism and Hospitality SITCON 2

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The future of rural tourism development has been shaped by the new wave of technological possibilities. The concept of smart village emerged as an innovative model that includes technology-based tourism experience in a rural area. This model has been established considering the advantages of mobile tourism applications, among the other technologies, designed to help tourists in decision making process when choosing a rural destination, and to augment their enjoyment during the stay. Hence, the subject of this paper is to determine the role of mobile applications in the development of rural tourism and to define the future direction of academic research related to smart villages and mobile-based tourism. The research is based on the secondary data analysis of various academic publications related to the rural tourism and information communication technology (ICT). Research results indicate that implementation of mobile applications in rural tourism has positive influence on the rural tourism development, thus creating valuable opportunities for service providers in this tourism niche. The significance of this study has been presented as a theoretical contribution to literature regarding the rural tourism, as well as the practical contribution to the process of creating the updated version of rural tourism destinations.

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Section: Resultsmentioning

confidence: 99%

Developing a “Smart Village” through the Implementation of Mobile Applications

2022

Proceedings of the the International Scientific Conference in the Field Of Tourism and Hospitality SITCON 2

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“…Firstly, the study enhances the planning influence of agriculture ecology scenery by including the customary rural culture paradigm in the design phase. The circular economy (CE) has arisen to lessen resource consumption and waste creation, mitigate the damaging effects on agriculture ecosystems, and boost productivity [13]. The CE is a way of producing and consuming goods that maximize the lifespan of resources by maximizing their communication, letting, reuse, repair, refurbishment, and disposal.…”

Section: Introductionmentioning

confidence: 99%

Research on the "Agricultural and Tourism Dual Chain" Model of Leisure Agriculture from the Perspective of Circular Economy

2024

Teh. vjesn.

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Leisure agriculture is a growing trend in the agricultural tourism industry. Human activities negatively affect ecosystem and agricultural output, and these effects worsen as the economy grows. Therefore, most conventional agricultural firms rely on external sources for technological advancement to outsource development or only engage in a limited number of innovation chains. A novel model named the Agricultural and Tourism Dual Chain Model of Leisure Agriculture (ATDCM-LA), is proposed after a thorough examination of the circular economy and presented in this study. Improvements in modern Leisure Agriculture tourism base planning may be attained via ecological agriculture by analyzing the impacts on regional planning. Fuzzy Analytical Hierarchy Technique (FAHT) was used to generate administrators' relative weights for farm leisure growth, and indicators were dynamically ranked by importance. Data Envelope Analysis (DEA) based on Circular Economy (CE) has applied to the existing state of leisure and tourism agriculture, which scales back the expansion of leisure agriculture and prioritizes growth initiatives that will have the most significant impact. This research integrates the goals of promoting rural culture with those of tourism administration and economic theory in agriculture, and it concludes with recommendations for regional growth of leisure agricultural tourist facilities. Leisure agricultural tourist base planning and administration results reveal the necessity to merge rural tradition with the sector's agrarian investment. Finally, the findings indicate that a rural-culture-based Leisure Agriculture tourist basis has some potential for success in regional development.

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“…The tourism data analysis also analyses the user's behaviors, interests, likes, and preferences to provide necessary services at the needed time. The support vector regression (SVR) model is an ML-based model that is used in the tourism data analysis process [ 13 ]. SVR improves the accuracy rate in the analysis process, which enhances the feasibility of the recommendation system.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Personalized Tourism Recommendation System Based on the Data Mining and Collaborative Filtering Algorithm

Nan¹,

kanato

Wang³

2022

Computational Intelligence and Neuroscience

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A personalized tourism recommendation system provides convenient and economically affordable travel information for individuals/groups. This recommendation system banks on accumulated and analyzed data for providing context-aware travel solutions. For improving the recommendation efficiency and data analysis of such systems, this article introduces a mining and filtering harmonized collaborative process, named as the collaborative mining and filtering process (CMFP), for reducing the data processing overheads and improving the recommendation ratio. In this process, the accumulated data from the global and personal travel, expenditure, and other information are collaboratively analyzed. This analysis is powered by knowledge-based transfer learning for reducing the retardation in the large data processing. Based on the context-based data analysis, the filtering and mining are jointly performed for providing recommendations. In the filtering process, the maximum processed contextual data are extracted for updating the current knowledge base. From this base, the recommendation for adaptable travel is recommended for the user. This process’s performance is analyzed using the metrics accuracy, data handling rate, mining time, and overhead.

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Personalized Recommendation of Rural Tourism Based on Traffic Classification and User Data Analysis

Cited by 4 publications

References 26 publications

Developing a “Smart Village” through the Implementation of Mobile Applications

Developing a “Smart Village” through the Implementation of Mobile Applications

Research on the "Agricultural and Tourism Dual Chain" Model of Leisure Agriculture from the Perspective of Circular Economy

Design and Implementation of a Personalized Tourism Recommendation System Based on the Data Mining and Collaborative Filtering Algorithm

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