Smart Tourism Platform Based on Microservice Architecture and Recommender Services

García, Laura Martínez; Aciar, Silvana; Mendoza, Raynel; Puello, Juan

doi:10.1007/978-3-319-97163-6_14

Cited by 23 publications

(12 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [43], the authors proposed a suite of small applications in tourism, by using a recommendation approach and supported in a microservice pattern, via a set of independent deployable services. The authors define the following functions: (1) to suggest routes and point of interest to users with respect to the choice of tourism activities; (2) the mutual supporting tourist and tourism services suppliers with location services; (3) to help communities in the preservation and valorization of cultural heritages; (4) to enable tourist to share their travel experiences to help other travelers in their decision-making process.…”

Section: Related Workmentioning

confidence: 99%

An Architecture for Service Integration to Fully Support Novel Personalized Smart Tourism Offerings

Sabbioni

Villano

Corradi

2022

Sensors

View full text Add to dashboard Cite

The continuous evolution of IT (information technology) technologies is radically transforming many technical areas and social aspects, also reshaping the way we behave and looking for entertainment and leisure services. In that context, tourism experiences request to enhance the level of user involvement and integration and to create an ever more personalized and connected experience, by leveraging on the differentiated tourist services and information locally present in the territory, by pushing active participation of customers, and by taking advantage of the ever-increasing presence of sensors and IoT (Internet of Things) devices deployed in many realities. However, the deep fragmentation of services and technologies adopted in tourism context characterizes the whole information provided also by customer sensing and IoTs (Internet of Things) heterogeneity and deep clashes with an effective organization of smart tourism. This article presents APERTO5.0 (an Architecture for Personalization and Elaboration of services and data to Reshape Tourism Offers 5.0), an innovative architecture aiming at a whole integration and deep facilitation of tourism service and information organization and blending, to enable the re-provisioning of novel services as advanced aggregates or re-elaborated ones. The proposed solution will demonstrate its effectiveness in the context of Smart Tourism by choosing the real use case of the “Francigena way” (a pilgrim historical path), the Italian part.

show abstract

Section: Related Workmentioning

confidence: 99%

An Architecture for Service Integration to Fully Support Novel Personalized Smart Tourism Offerings

Sabbioni

Villano

Corradi

2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Enhancing tourism services. With the aim of enhancing the dissemination and protection of the cultural heritage of a city, as part of a smart tourism application, the reader is referred to (Barile et al, 2014;Cha et al, 2016;Massimo, 2018;Amato et al, 2012;García et al, 2018). Large amounts of tourists in few city areas may cause mobility problems, such as traffic congestion, and an unbalanced economy or discordance between tourists and residents.…”

Section: Recommender Systems and Smart Livingmentioning

confidence: 99%

Recommender systems for smart cities

Quijano-Sánchez

Cantador

Cortés-Cediel

et al. 2020

Information Systems

103

View full text Add to dashboard Cite

“…This concept refers to real-time data exploitation, data sharing, analysis, modeling, and optimization to achieve improved operational decisions. 8 Hence, the term has been added to cities to describe efforts to achieve optimal resource utilization and sustainability in quality of life. 9 "Smart e-tourism" has become a new buzzword to describe technological developments that rely on sensors, large amounts of open data, and new ways of exchanging information.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, smart is the interconnectedness and interdependence in the use of different technologies. This concept refers to real‐time data exploitation, data sharing, analysis, modeling, and optimization to achieve improved operational decisions 8 . Hence, the term has been added to cities to describe efforts to achieve optimal resource utilization and sustainability in quality of life 9 .…”

Section: Introductionmentioning

confidence: 99%

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Krishnan

Mohammed

Alnoor

et al. 2021

Int J of Intelligent Sys

View full text Add to dashboard Cite

The benchmarking of smart e‐tourism data management applications falls under the problem of multicriteria decision‐making (MCDM). This claim is supported by three issues: 12 smart key concepts need to be considered in the evaluation, criteria importance, and data variation among these criteria. Thus, an MCDM solution is essential to overcome problem complexity. To end this, this study presents a decision‐making framework on the basis of the extension of interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency (IT2TR‐FWZIC) integrated with the Vlsekriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) method for evaluating and benchmarking the smart e‐tourism data management applications. Our methodology comprises two consecutive phases. In the first phase, a decision matrix is constructed using the intersection between the 12 key concepts and smart e‐tourism data management applications of each category and subcategory in smart e‐tourism. In the second phase, the integration of the IT2TR‐FWZIC formulation and VIKOR is presented to compute the weights for the 12 key concepts and benchmark the smart e‐tourism data management applications for each category. The results are as follows: (1) A clear difference is found among the criteria weights (12 smart key concepts). Specifically, the real‐time criterion achieves the highest importance weight (0.098), whereas augmented reality obtains the lowest weight (0.068). The context‐awareness and recommender systems have the same weight value (0.087), and the other eight criteria are distributed in between. (2) The smart e‐tourism data management applications are evaluated and benchmarked effectively per category and subcategories. (3) Benchmarked applications in each category are subjected to a systematic ranking in the evaluation process. The sensitivity analysis has shown high correlation outcomes to the systematic ranking results over the 31 scenarios of criteria weight changing. Moreover, a comparative analysis of the proposed work with other existing studies is also discussed.

show abstract

Smart Tourism Platform Based on Microservice Architecture and Recommender Services

Cited by 23 publications

References 38 publications

An Architecture for Service Integration to Fully Support Novel Personalized Smart Tourism Offerings

An Architecture for Service Integration to Fully Support Novel Personalized Smart Tourism Offerings

Recommender systems for smart cities

Interval type 2 trapezoidal‐fuzzy weighted with zero inconsistency combined with VIKOR for evaluating smart e‐tourism applications

Contact Info

Product

Resources

About