Interacting and making personalized recommendations of places of interest to tourists

Advances in Intelligent Systems and Computing, 353Nowadays, applications that are developed to support tourists should go much further than simply providing information about places or recommending places or routes based on the user location. They should be able to provide users with simple mechanisms to interact with places of interest and provide them with relevant information and recommendations about new relevant places of interest or tours according to their preferences and the preferences of other tourists with similar interests. In this work we describe a system that explores information about tourists’ interactions with places of interest and their opinions about each place, to recommend new places of interest, pedestrian tours and to promote products and services which are in accordance with their expectations. First experiments show that the system can help the tourists to interact with places of interest, helping them in their visits and also to promote shops and services

Travel recommendations in a mobile tourist information system

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

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

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

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

Intelligent Destination Recommender and Community Builder

Recommendation engines make use of machine learning techniques and generally deal with ranking and rating of products/users. With the help of this system we aim to suggest different destinations to users based on their interest and previous visits. Along with recommendations we also aspire to enable users to build travel communities for people sharing similar interests .This shall help travelers with planning ,meeting like-minded people,safety and enthralling experience. As per the analysis done on pre-existing systems we discerned that enabling users to build a community of travelers visiting the same destination is an eccentric attribute proposed. This distinctive attribute of building communities shall be implemented using the basics of clustering algorithms in Machine learning

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

Smart destinations for smart Generation? – The requirements of Generation Y in the area of innovative communication

Social media and mobile-marketing all among the most challenging trends the tourism destinations facing with, particularly in the area of reaching the so called smart or Internet Generation, the tourists from the Generation Y. However the most innovative destinations’ objective is to implement SoCoMo (Social-context-based – mobile marketing), the main question is whether the members of the Generation Y need these kind of approaches. Generation Y is considered as the most technology savvy Generation, whose members are conscious consumers with well-defined, high needs regarding quality, and price/value ratio, and as sharing their most important life-events on several social media channels with their peers, Web.2.0. is crucial for them as a channel for communication and co-creation. The main dilemma is whether this opened Generation with an advanced technology-using habits would need “smart” solutions and “smart destinations” based on social-mobile marketing, and highly personalized services? The main objective of the paper is to introduce the results of a quantitative research with more than 430 answers from 45 countries from the members of Generation Y regarding their needs, limits in the area of highly innovative communication and product-development questions

SoCoMo marketing for travel and tourism: Empowering co-creation of value.

Advanced technology enables users to amalgamate information from various sources on their mobile devices, personalise their profile through applications and social networks, as well as interact dynamically with their context. Context-based marketing uses information and communication technologies (ICTs) that recognise the physical environment of their users. Tourism marketers are increasingly becoming aware of those cutting-edge ICTs that provide tools to respond more accurately to the context within and around their users. This paper connects the different concepts of context-based marketing, social media and personalisation, as well as mobile devices. It proposes social context mobile (SoCoMo) marketing as a new framework that enables marketers to increase value for all stakeholders at the destination. Contextual information is increasingly relevant, as big data collected by a wide range of sensors in a smart destination provide real-time information that can influence the tourist experience. SoCoMo marketing introduces a new paradigm for travel and tourism. It enables tourism organisations and destinations to revolutionise their offering and to co-create products and services dynamically with their consumers. The proposed SoCoMo conceptual model explores the emerging opportunities and challenges for all stakeholders

A context aware recommender system for tourism with ambient intelligence

Recommender system (RS) holds a significant place in the area of the tourism sector. The major factor of trip planning is selecting relevant Points of Interest (PoI) from tourism domain. The RS system supposed to collect information from user behaviors, personality, preferences and other contextual information. This work is mainly focused on user’s personality, preferences and analyzing user psychological traits. The work is intended to improve the user profile modeling, exposing relationship between user personality and PoI categories and find the solution in constraint satisfaction programming (CSP). It is proposed the architecture according to ambient intelligence perspective to allow the best possible tourist place to the end-user. The key development of this RS is representing the model in CSP and optimizing the problem. We implemented our system in Minizinc solver with domain restrictions represented by user preferences. The CSP allowed user preferences to guide the system toward finding the optimal solutions; RESUMO O sistema de recomendação (RS) detém um lugar significativo na área do sector do turismo. O principal fator do planeamento de viagens é selecionar pontos de interesse relevantes (PoI) do domínio do turismo. O sistema de recomendação (SR) deve recolher informações de comportamentos, personalidade, preferências e outras informações contextuais do utilizador. Este trabalho centra-se principalmente na personalidade, preferências do utilizador e na análise de traços fisiológicos do utilizador. O trabalho tem como objetivo melhorar a modelação do perfil do utilizador, expondo a relação entre a personalidade deste e as categorias dos POI, assim como encontrar uma solução com programação por restrições (CSP). Propõe-se a arquitetura de acordo com a perspetiva do ambiente inteligente para conseguir o melhor lugar turístico possível para o utilizador final. A principal contribuição deste SR é representar o modelo como CSP e tratá-lo como problema de otimização. Implementámos o nosso sistema com o solucionador em Minizinc com restrições de domínio representadas pelas preferências dos utilizadores. O CSP permitiu que as preferências dos utilizadores guiassem o sistema para encontrar as soluções ideais