39,277 research outputs found

    Travel recommendations in a mobile tourist information system

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    An advanced mobile tourist information system delivers information about sights and events on a tourists travel route. The system should be personalized in its interaction with the tourist. Data that can be used for personalization are: the tourists interest profile, an analysis of their travel history, and the tourists feedback about sights. Existing mobile information systems for tourists do not tailor their information delivery to the tourists interests. In this paper, we propose the use of personalised recommendations that consider all of the personal information a tourist provides. We adopt and modify techniques from recommended systems to the new application area of mobile tourist information. We propose a number of methods for personalised recommendations; and select a subset of these for implementation. This paper then presents the implemented recommended component of our TIP system for mobile tourist informatio

    Factors Affecting Tourist Satisfaction with Theatrical Performances: A Case Study of 'The Romance of the Song Dynasty' in Hangzhou, China

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    This study, for the first time, attempts to explore the factors affecting tourist satisfaction with a theatrical performance, The Romance of the Song Dynasty in Hangzhou, China. Four factors are identified to have affected tourist satisfaction: “Performance,” “Venue Environment,” “Service,” and “Stage Facilities”. These theatrical performance factors are examined to assess the relative influence on tourist overall satisfaction. Tourists have the highest satisfaction with “Stage Facilities” among all factors, however, “Service” is the most influential predictor of tourist overall satisfaction. Tourist demographic and travel characteristics towards these four theatrical performance factors reveal several significant differences. Discussions and implications are provided to theatre operators to improve tourist satisfaction with theatrical performance not only in Hangzhou, but also in the whole China

    eEnabled internet distribution for small and medium sized hotels: the case of hospitality SMEs in Athens

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    Advances in information and communications technologies (ICTs) have strategic implications for a wide range of industries. Tourism and hospitality have dramatically changed by the ICTs and the Internet and gradually emerge as the leading industry on online expenditure. The Internet revolutionised traditional distribution models, enabled new entries propelled both disintermediation and reintermediation and altered the sources of competitive advantage. This paper explores the strategic implications of ICTs and the perceived advantages and disadvantages of Internet distribution for small and medium-sized hospitality enterprises (SMEs). Primary research in Athens hotels demonstrates the effects of the Internet and ICTs for secondary markets, where there is lower penetration and ICT adoption. Interviews and questionnaires identified a number of strategies in order to optimise distribution. The analysis illustrates the strategic role of ICTs and the Internet for hospitality organisations and Small and Medium-sized organisations in general. Most hotels employ a distribution mix that determines the level and employment of the Internet. The paper demonstrates that only organisations that use ICTs strategically will be able to develop their electronic distribution and achieve competitive advantages in the future

    Advanced recommendations in a mobile tourist information system

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    An advanced tourist information provider system delivers information regarding sights and events on their users' travel route. In order to give sophisticated personalized information about tourist attractions to their users, the system is required to consider base data which are user preferences defined in their user profiles, user context, sights context, user travel history as well as their feedback given to the sighs they have visited. In addition to sights information, recommendation on sights to the user could also be provided. This project concentrates on combinations of knowledge on recommendation systems and base information given by the users to build a recommendation component in the Tourist Information Provider or TIP system. To accomplish our goal, we not only examine several tourist information systems but also conduct the investigation on recommendation systems. We propose a number of approaches for advanced recommendation models in a tourist information system and select a subset of these for implementation to prove the concept

    Tour recommendation for groups

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    Consider a group of people who are visiting a major touristic city, such as NY, Paris, or Rome. It is reasonable to assume that each member of the group has his or her own interests or preferences about places to visit, which in general may differ from those of other members. Still, people almost always want to hang out together and so the following question naturally arises: What is the best tour that the group could perform together in the city? This problem underpins several challenges, ranging from understanding people’s expected attitudes towards potential points of interest, to modeling and providing good and viable solutions. Formulating this problem is challenging because of multiple competing objectives. For example, making the entire group as happy as possible in general conflicts with the objective that no member becomes disappointed. In this paper, we address the algorithmic implications of the above problem, by providing various formulations that take into account the overall group as well as the individual satisfaction and the length of the tour. We then study the computational complexity of these formulations, we provide effective and efficient practical algorithms, and, finally, we evaluate them on datasets constructed from real city data

    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

    Enabling a Pepper Robot to provide Automated and Interactive Tours of a Robotics Laboratory

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    The Pepper robot has become a widely recognised face for the perceived potential of social robots to enter our homes and businesses. However, to date, commercial and research applications of the Pepper have been largely restricted to roles in which the robot is able to remain stationary. This restriction is the result of a number of technical limitations, including limited sensing capabilities, and have as a result, reduced the number of roles in which use of the robot can be explored. In this paper, we present our approach to solving these problems, with the intention of opening up new research applications for the robot. To demonstrate the applicability of our approach, we have framed this work within the context of providing interactive tours of an open-plan robotics laboratory.Comment: 8 pages, Submitted to IROS 2018 (2018 IEEE/RSJ International Conference on Intelligent Robots and Systems), see https://bitbucket.org/pepper_qut/ for access to the softwar

    Hybrid group recommendations for a travel service

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    Recommendation techniques have proven their usefulness as a tool to cope with the information overload problem in many classical domains such as movies, books, and music. Additional challenges for recommender systems emerge in the domain of tourism such as acquiring metadata and feedback, the sparsity of the rating matrix, user constraints, and the fact that traveling is often a group activity. This paper proposes a recommender system that offers personalized recommendations for travel destinations to individuals and groups. These recommendations are based on the users' rating profile, personal interests, and specific demands for their next destination. The recommendation algorithm is a hybrid approach combining a content-based, collaborative filtering, and knowledge-based solution. For groups of users, such as families or friends, individual recommendations are aggregated into group recommendations, with an additional opportunity for users to give feedback on these group recommendations. A group of test users evaluated the recommender system using a prototype web application. The results prove the usefulness of individual and group recommendations and show that users prefer the hybrid algorithm over each individual technique. This paper demonstrates the added value of various recommendation algorithms in terms of different quality aspects, compared to an unpersonalized list of the most-popular destinations
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