Tourism mobile and recommendation systems - a state of the art

Recommendation systems have been growing in number for the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.

Recommendation & mobile systems - a state of the art for tourism

Recommendation systems have been growing in number over the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. These approaches contain strengths and weaknesses that need to be evaluated according to the knowledge area in which the system is going to be implemented. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages.

Recommendation and planning through mobile devices in tourism context

In this paper we present a mobile recommendation and planning system, named PSiS Mobile. It is designed to provide effective support during a tourist visit through context-aware information and recommendations about points of interest, exploiting tourist preferences and context. Designing a tool like this brings several challenges that must be addressed. We discuss how these challenges have been overcame, present the overall system architecture, since this mobile application extends the PSiS project website, and the mobile application architecture.

Organisational influence on volunteer satisfaction and attitudes towards HRM practices: the case of hospital volunteers

We examine volunteer satisfaction with HRM practices, namely recruitment, training and reward in NPOs and attitudes regarding the appropriateness of these practices. The participants in this study are 76 volunteers affiliated with four different NPOs, who work in hospitals and have direct contact with patients and their families. Analysing aggregate results we show that volunteers are more satisfied with training, and consider the training strategies to be very appropriate. After identifying differences between organisations we discover that in some organisations volunteers are satisfied with rewards but they have negative attitudes regarding the appropriateness of the recognition strategies. We also identify the volunteers who are the most and the least satisfied.

User modeling and recommendation strategies for tourism

Mestrado em Engenharia Informática

How does gender affect visiting a world heritage site?

To date few studies have been undertaken in Portugal dealing with the attitudes, motivations, and profile of tourists who visit World Heritage Sites. Also, few studies have dealt with destination image (e.g., Agapito, Mendes & Valle, 2010; Lopes, 2011). As far as it is known, none have approached the issue of gender differences in the choice of a Portuguese heritage destination. Since cultural tourism destinations need to differentiate themselves from each other, appropriate market segmentation must be based on a deep understanding of the customers’ motivations and preferences. Keeping in mind results from empirical literature (e.g., Silberberg, 1995; Beerli & Martin, 2004; Richards, 2004; Pérez, 2009; Sheng, Shen, & Chen, 2008), gender seems to be a possible approach to market segmentation, whether for Guimarães or for other cultural tourism destinations around the world. Located in the north-western region of Portugal, Guimarães is a city of strong symbolic and cultural significance, and the nomination of its historical centre as a World Heritage Site in 2001 enhanced its tourism potential. This study analyses the possible relation between gender and attitudes and motivations towards a World Heritage Site, such as Guimarães. Additionally, the empirical approach used in the study tries to capture differences in the perceived attributes of the city. Commonalities and distinctions within and between groups of tourists, by focusing on the specific characteristic of gender, were analysed. The study addressed two main questions: first, whether males and females have similar or different preferences in choosing the city as their destination; and, second, whether there are gender differences in the perception of the attributes of Guimarães. A better understanding of the gendered nature of the destination is a valuable cue for shaping products and services according to visitors’ preferences.

Recommendation of Tourism Resources Supported by Crowdsourcing

Context-aware recommendation of personalised tourism resources is possible because of personal mobile devices and powerful data filtering algorithms. The devices contribute with computing capabilities, on board sensors, ubiquitous Internet access and continuous user monitoring, whereas the filtering algorithms provide the ability to match the profile (interests and the context) of the tourist against a large knowledge bases of tourism resources. While, in terms of technology, personal mobile devices can gather user-related information, including the user context and access multiple data sources, the creation and maintenance of an updated knowledge base of tourism-related resources requires a collaborative approach due to the heterogeneity, volume and dynamic nature of the resources. The current PhD thesis aims to contribute to the solution of this problem by adopting a Crowdsourcing approach for the collaborative maintenance of the knowledge base of resources, Trust and Reputation for the validation of uploaded resources as well as publishers, Big Data for user profiling and context-aware filtering algorithms for the personalised recommendation of tourism resources.

User Profiling and Knowledge Extraction For Tourism

O sector do turismo é uma área francamente em crescimento em Portugal e que tem desenvolvido a sua divulgação e estratégia de marketing. Contudo, apenas se prende com indicadores de desempenho e de oferta instalada (número de quartos, hotéis, voos, estadias), deixando os indicadores estatísticos em segundo plano. De acordo com o “ Travel & tourism Competitiveness Report 2013”, do World Economic Forum, classifica Portugal em 72º lugar no que respeita à qualidade e cobertura da informação estatística, disponível para o sector do Turismo. Refira-se que Espanha ocupa o 3º lugar. Uma estratégia de mercado, sem base analítica, que sustente um quadro de orientações específico e objetivo, com relevante conhecimento dos mercados alvo, dificilmente é compreensível ou até mesmo materializável. A implementação de uma estrutura de Business Intelligence que permita a realização de um levantamento e tratamento de dados que possibilite relacionar e sustentar os resultados obtidos no sector do turismo revela-se fundamental e crucial, para que sejam criadas estratégias de mercado. Essas estratégias são realizadas a partir da informação dos turistas que nos visitam, e dos potenciais turistas, para que possam ser cativados no futuro. A análise das características e dos padrões comportamentais dos turistas permite definir perfis distintos e assim detetar as tendências de mercado, de forma a promover a oferta dos produtos e serviços mais adequados. O conhecimento obtido permite, por um lado criar e disponibilizar os produtos mais atrativos para oferecer aos turistas e por outro informá-los, de uma forma direcionada, da existência desses produtos. Assim, a associação de uma recomendação personalizada que, com base no conhecimento de perfis do turista proceda ao aconselhamento dos melhores produtos, revela-se como uma ferramenta essencial na captação e expansão de mercado.