1,658 research outputs found

    Personalization in cultural heritage: the road travelled and the one ahead

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    Over the last 20 years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed

    Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research

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    This paper reviews the published articles on eTourism in the past 20 years. Using a wide variety of sources, mainly in the tourism literature, this paper comprehensively reviews and analyzes prior studies in the context of Internet applications to Tourism. The paper also projects future developments in eTourism and demonstrates critical changes that will influence the tourism industry structure. A major contribution of this paper is its overview of the research and development efforts that have been endeavoured in the field, and the challenges that tourism researchers are, and will be, facing

    Divertimi: A Tourist Guide to a Unique and Enriching Experience

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    This project lays a foundation for the development of an e-tourism website by Azienda di Promozione Turistica della Provincia di Venezia, the provincial tourism authority in the Veneto region of Italy. Our design employs individual and group profiling to recommend destinations and attractions. Social networking and various forms of user-generated narratives support travel recommendations. Finally, we propose a system for offering a personalized trip package based on user interests

    Development of an Ontology of Tourist Attractions for Recommending Points of Interest in a Group Recommender System for Tourism

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    In recent years, the tourism industry has witnessed substantial growth, thanks to the pro liferation of digital technology and online platforms. Tourists now have greater access to information and the ability to make informed travel decisions. However, the abundance of available information often leaves tourists overwhelmed when selecting points of inter est (POI) that align with their preferences. Recommender Systems (RS) have emerged as a solution, personalising recommendations based on tourist behaviour, social networks, and contextual factors. To enhance RS efficacy, researchers have begun exploring the integration of psychological factors, such as personality traits. Yet, to meet the demands of modern tourists, a robust knowledge base, such as a tourist attractions ontology, is essential for seamless and rapid matching of tourist characteristics and preferences with available POI. With that in mind, this project aims to enhance a Group Recommender System (GRS) prototype, GrouPlanner, by creating a robust tourist attractions ontology. This ontology will facilitate rapid and accurate matching of points of interest with tourists’ character istics, including personality, preferences, and demographic data, ultimately improving POI recommendations. First, there needs to be an understanding of the personality of tourists and how it influences their choices when it comes to picking the best point of interest based on their personality. With that knowledge acquired, it is time to choose a way to represent this knowledge in the form of an ontology. In this project, the Protégé ontology editor was used to design the ontology and the rela tionships between the tourists’ personality and the points of interest. After designing the ontology, it had to be converted to a database so the Grouplanner system could access it. So, to do that, a solution was designed to integrate the designed ontology in a triple store data base, in this case, Apache Fuseki. With the database implemented, several tests were made to verify if the database would give the recommended points of interests based on the tourists’ preferences. This tests were later analysed.Nos anos mais recentes, a indústria do turismo presenciou um crescimento substancial dev ido à tecnologia digital e plataformas online. Cada vez mais, os turistas têm acesso a uma abundância de informação que influencia a habilidade de tomar decisões sobre viajar. No entanto, esta informação pode complicar a seleção dos pontos de interesse que alinhem com as preferências dos turistas. Para combater isso, sistemas de recomendação (SR) emergi ram como uma solução, personalizando as recomendações com base no comportamento do turista, redes socias e outros fatores. Para aumentar a eficácia destes sistemas, os investi gadores começaram a explorar a possibilidade de integração com fatores psicológicos, como traços de personalidade. Apesar disso, para cumprir as exigências dos turistas modernos, uma base de conhecimento robusta, como uma ontologia de atrações turísticas, é essencial para, de forma eficaz e eficiente, corresponder as características dos turistas com os pontos de interesse disponíveis. Com isso em mente, este projeto tem como objetivo melhorar um protótipo de um sistema de recomendação (GrouPlanner), criando uma ontologia robusta de atrações turísticas. Essa ontologia facilitará a correspondência rápida e precisa de pontos de interesse com as car acterísticas dos turistas, incluindo a sua personalidade e as suas preferências, melhorando assim as recomendações de pontos de interesse. Em primeiro lugar, é necessário compreender a personalidade dos turistas e como ela influ encia as suas escolhas ao selecionar o melhor ponto de interesse com base na sua person alidade. Com esse ponto adquirido, é necessário escolher uma maneira de representar esse conhecimento na forma de uma ontologia. Neste projeto, o editor de ontologias Protégé foi utilizado para projetar a ontologia e as relações entre a personalidade dos turistas e os pontos de interesse. Após a construção da ontologia, foi necessário convertê-la numa base de dados para que o sistema Grouplanner pudesse ter acesso. Para isso, foi desenhada uma solução para integrar a ontologia projetada numa base de dados "triple store", neste caso, o Apache Fuseki. Com a base de dados implementada, foram realizados vários testes para verificar se esta forneceria os pontos de interesse recomendados com base nas preferências dos turistas. Esses testes foram depois analisados

    A Design Concept for a Tourism Recommender System for Regional Development

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    Despite of tourism infrastructure and software, the development of tourism is hampered due to the lack of information support, which encapsulates various aspects of travel implementation. This paper highlights a demand for integrating various approaches and methods to develop a universal tourism information recommender system when building individual tourist routes. The study objective is proposing a concept of a universal information recommender system for building a personalized tourist route. The developed design concept for such a system involves a procedure for data collection and preparation for tourism product synthesis; a methodology for tourism product formation according to user preferences; the main stages of this methodology implementation. To collect and store information from real travelers, this paper proposes to use elements of blockchain technology in order to ensure information security. A model that specifies the key elements of a tourist route planning process is presented. This article can serve as a reference and knowledge base for digital business system analysts, system designers, and digital tourism business implementers for better digital business system design and implementation in the tourism sector

    Web-Based Recommendation System for Smart Tourism: Multiagent Technology

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    The purpose of the study is to design and develop a recommended system based on agent and web technologies, which utilizes a hybrid recommendation filtering for the smart tourism industry. A hybrid recommendation system based on agent technology is designed by considering the online communication with other sectors in the tourism industry, such as the tourism supply chain, agency etc. However, online communication between the sectors via agents is designed and developed based on the contract net protocol. Furthermore, the design system is developed on the java agent development framework and implemented as a web application. Case study-based results considering two scenarios involving 100 customers illustrated that the proposed web application improves the rate of the recommendation for the customers. In the first scenario without disturbances, this rate was improved by 20% and the second scenario with disturbances yielded a 30% rate of acceptable recommendation. In addition, based on the second scenario, real time data communication on the system occurred, thus the proposed system supported real time data communication
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