A Research on Smart Tourism Service Mechanism Based on Context Awareness

Feng, Wen; Duan, Yu Cong; Huang, Meng Xin; Dong, Lu; Zhou, Xiaoyi; Hu, Tao

doi:10.4028/www.scientific.net/amm.519-520.752

Cited by 10 publications

(4 citation statements)

References 3 publications

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“…e probability of good economic benefit of the project is 44.64%, so we can determine that the overall evaluation of the economic benefit of the smart city construction project in this city is good. In addition, we should 8 Complexity also see that the project's economic efficiency is good or general probability is 73.62%, greater than 50%; this conclusion indicates that, at this stage of the preproject evaluation, the smart city complex construction project of the financial profitability and project risk are acceptable to the project investment body. Respectively, draw radar chart for index combination weight analysis, as shown in Figure 5.…”

Section: Judgment Matrix Rowmentioning

confidence: 90%

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Impact of Smart City Planning and Construction on Economic and Social Benefits Based on Big Data Analysis

Zhao

Zhang

2020

Complexity

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With the progress of urbanization, urban management is facing a series of challenges in the new situation. The scale of the city is growing, urban management problems are increasingly prominent, the urban population is showing a rapid growth trend, and various elements of urban infrastructure management, such as rapid growth and urban expansion, have increased the load of urban infrastructure. To make overall planning for urban transportation, municipal administration, economic industry, and public service, intelligent urban planning and construction came into being. Big data technology provides important support for the construction and development of smart city, which is not only an effective means to improve the design of smart city, but also the premise for the development of smart city. Therefore, this paper first introduces the characteristics of smart city, analyses the application of big data technology in smart city design, and finally evaluates the impact of smart city planning and construction based on big data on economic and social benefits.

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Section: Judgment Matrix Rowmentioning

confidence: 90%

“…Its development mainly depends on the continuous progress of science and technology. Now we live in an information society, and all kinds of living conditions are developing to a high level [8,9]. Smart city is now a collection of higher concepts.…”

Section: Planning and Construction Of Smart City In The Era Of Big Datamentioning

confidence: 99%

Impact of Smart City Planning and Construction on Economic and Social Benefits Based on Big Data Analysis

Zhao

Zhang

2020

Complexity

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“…Kozuch et al (2009) demonstrated that location-aware applications outperform those with no location-aware capability by factor of 3-11 in the performance. Based on context awareness of data, platform and services, Feng et al (2014) presented a tourism service mechanism that dynamically adjusts the service mode based on the user context information and meets the demand for tourism services in conjunction with the individual user characteristics.…”

Section: Optimizing Big Data Platforms With Spatiotemporal Principlesmentioning

confidence: 99%

Big Data and cloud computing: innovation opportunities and challenges

Yang

Huang

et al. 2016

International Journal of Digital Earth

645

289

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Big Data has emerged in the past few years as a new paradigm providing abundant data and opportunities to improve and/or enable research and decision-support applications with unprecedented value for digital earth applications including business, sciences and engineering. At the same time, Big Data presents challenges for digital earth to store, transport, process, mine and serve the data. Cloud computing provides fundamental support to address the challenges with shared computing resources including computing, storage, networking and analytical software; the application of these resources has fostered impressive Big Data advancements. This paper surveys the two frontiers-Big Data and cloud computingand reviews the advantages and consequences of utilizing cloud computing to tackling Big Data in the digital earth and relevant science domains. From the aspects of a general introduction, sources, challenges, technology status and research opportunities, the following observations are offered: (i) cloud computing and Big Data enable science discoveries and application developments; (ii) cloud computing provides major solutions for Big Data; (iii) Big Data, spatiotemporal thinking and various application domains drive the advancement of cloud computing and relevant technologies with new requirements; (iv) intrinsic spatiotemporal principles of Big Data and geospatial sciences provide the source for finding technical and theoretical solutions to optimize cloud computing and processing Big Data; (v) open availability of Big Data and processing capability pose social challenges of geospatial significance and (vi) a weave of innovations is transforming Big Data into geospatial research, engineering and business values. This review introduces future innovations and a research agenda for cloud computing supporting the transformation of the volume, velocity, variety and veracity into values of Big Data for local to global digital earth science and applications.

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“…The authors of [142][143][144][145][146] proposed a context-aware recommendation system using smartphone sensors integrated with smart city applications and e-tourism, another recommendation system based on tourist context [147,148]. The authors of [49,73,149,150] proposed a system of travel recommendations that mines appropriate locations, context, user preferences [151][152][153] users' reviews [154], sentiments analysis [1], and users' physical and psychological functionality levels [155].…”

Section: Traveling and Poimentioning

confidence: 99%

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

et al. 2021

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Agenda 2030 of Sustainable Development Goals (SDGs) 9 and 11 recognizes tourism as one of the central industries to global development to tackle global challenges. With the transformation of information and communication technologies (ICT), e-tourism has evolved globally to establish commercial relationships using the Internet for offering tourism-related products, including giving personalised suggestions. The contextual suggestion has emerged as a modified recommendation system that is integrated with information-retrieval techniques within large databases to provide tourists with a list of suggestions based on contexts, such as location, time of day, or day of the week (weekdays or weekends). This study surveyed literature in the field of contextual suggestion and recommendation systems with a focus on e-tourism. The concerns linked with approaches used in contextual suggestion and recommendation systems are highlighted in this systematic review, while motivations, recommendations, and practical implications in e-tourism are also discussed in this paper. A query search using the keywords “contextual suggestion system”, “recommendation system”, and “tourism” identified 143 relevant articles published from 2012 to 2020. Four major repositories are considered for searching, namely, (i) Science Direct, (ii) Scopus, (iii) IEEE, and (iv) Web of Science. This review was carried out under the protocols of four phases, namely, (i) query searching in major article repositories, (ii) removal of duplicates, (iii) scan of title and abstract, and (iv) complete reading of articles. To identify the gaps in current research, a taxonomy analysis was exemplified into categories and subcategories. The main categories were highlighted as (i) review articles, (ii) model/framework, and (iii) applications. Critical analysis was carried out on the basis of the available literature on the limitations of approaches used in contextual suggestion and recommendation systems. In conclusion, the approaches used are mainly based on content-based filtering, collaborative filtering, preference-based product ranking, and language modelling. The evaluation measures for the contextual suggestion system include precision, normalized discounted cumulative, and mean reciprocal rank, while test collections comprise Internet resources. Given that the tourism industry contributed to the environmental and social-economic development, contextual suggestion and recommendation systems have presented themselves to be relevant in integrating and achieving SDG 9 and SDG 11 in many ways such as web-based e-services by the government sector and smart gadgets based on reliable and real-time data and information for city planners as well as law enforcement personnel in a sustainable city.

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A Research on Smart Tourism Service Mechanism Based on Context Awareness

Cited by 10 publications

References 3 publications

Impact of Smart City Planning and Construction on Economic and Social Benefits Based on Big Data Analysis

Impact of Smart City Planning and Construction on Economic and Social Benefits Based on Big Data Analysis

Big Data and cloud computing: innovation opportunities and challenges

Systematic Review of Contextual Suggestion and Recommendation Systems for Sustainable e-Tourism

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