A mobile 3D-GIS hybrid recommender system for tourism

Noguera, José M.; Barranco, Manuel; Segura, Rafael J.; Martínez, Luis

doi:10.1016/j.ins.2012.05.010

Cited by 204 publications

(105 citation statements)

References 63 publications

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“…Uma forma de atender a esse público é considerar o ciberespaço como um canal de comunicação importante o qual, segundo Souza (2016) está diretamente relacionado ao turismo por viabilizar e auxiliar em diversas situações, tais como sistemas de reserva hoteleira online, usar as redes sociais para o compartilhamento de informações e serviços turísticos. Vários estudos recentes têm mostrado a importância de aplicações móveis para fazer reservas em hotel, organizar excursões, e fornecer informação turística (Noguera, Barranco, Segura & Martínez, 2012;Rodriguez-Sanchez, Martinez-Romo, Borromeo, & Hernandez-Tamames;2013).…”

Section: A Terceira Idade O Turismo E a Tecnologiaunclassified

Aceitação e uso da tecnologia para escolha de destinos turísticos por pessoas da terceira idade: um estudo usando a UTAUT2

Moura

Gosling

Christino

et al. 2017

RBTUR

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Os idosos têm demonstrado crescente interesse por novas tecnologias e as relacionam com a aprendizagem, inserção social e lazer. Considerando-se o elevado número de mudanças no perfil dos idosos brasileiros e os contextos turístico e tecnológico, esse trabalho tem como objetivo compreender as intenções comportamentais e o uso da internet pela terceira idade com fins de escolhas de destinos turísticos. Para isso, o trabalho estendeu o Modelo UTAUT2 de Venkatesh, Thong e Xu (2012), inserindo novos construtos relacionados à tecnologia: Risco Percebido e Confiança, de Slade et al (2015) e também adicionando a Atitude, fundamentada por Curras-Perez, Ruiz-Mafe e Sanz-Blas (2014). O estudo caracteriza-se como exploratório-descritivo. Para tanto, realizou-se um Survey, online e presencial, sendo aplicado por dois meses. Para as análises utilizou-se técnicas estatísticas de análise multivariada, processadas pelo SPSS20 e a análise de modelagem de equações estruturais utilizando-se o SmartPLS. A amostra obtida foi de 211 idosos que usam internet para fins turísticos. Como resultado, têm-se as relações dos construtos Hábito, Motivação Hedônica, Confiança e Expectativa de Desempenho como determinantes da Atitude de uso da Internet para fins turísticos e, acrescentando-se a isso, a relação do construto Hábito afetando positivamente o Comportamento de uso. No que tange à originalidade o trabalho apresentou a Atitude como um conceito novo utilizado para compor o modelo, trazendo algo inédito a este campo de estudos no Brasil. Além disso, apresenta-se como uma inovação à aplicação do modelo UTAUT2 no contexto brasileiro, em um segmento e setor de mercado ainda não explorado neste campo de pesquisa - a terceira idade e o turismo.

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Section: A Terceira Idade O Turismo E a Tecnologiaunclassified

Aceitação e uso da tecnologia para escolha de destinos turísticos por pessoas da terceira idade: um estudo usando a UTAUT2

Moura

Gosling

Christino

et al. 2017

RBTUR

View full text Add to dashboard Cite

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“…Representative examples include the POI recommendation system by Yu et al, 2009 [15], which supports travel planning, the POI recommendation system by Noguera et al, 2012 [16], which is based on current location information, and the POI recommendation system proposed by Baltrunas et al, 2011 [17], which is based on location information and user preference. Ye et al, 2011 [18], and Ying et al, 2012 [19], proposed a POI recommendation system that is based on location information and user preferences, as well as social networks.…”

Section: Related Workmentioning

confidence: 99%

“…However, if the number of evaluators is extremely low, the evaluation values obtained from the aforementioned preceding study are used, and the evaluators are each counted as one person. Referring to Ikeda et al, 2014 [29], Fujita et al, 2016 [8], and Zhou et al, 2016 [16], the system categorized all sightseeing spots into six categories including "food and drink", "shopping", "amusement parks and parks", "famous and historical sights", "art and historic museums" and "others (events, etc.)". …”

Section: Sightseeing Spot Datamentioning

confidence: 99%

A Sightseeing Spot Recommendation System That Takes into Account the Change in Circumstances of Users

Mizutani

Yamamoto

2017

IJGI

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Abstract:The present study aimed to design, develop, operate and evaluate a sightseeing spot recommendation system for urban sightseeing spots in order to support individual, as well as group sightseeing activities while taking into consideration the user's needs, which can change according to the circumstances (each user's important conditions and sightseeing unit). The system was developed by integrating Web-GIS (Geographic Information Systems), the pairing system, the evaluation system, as well as the recommendation system into a single system, and it was also connected with external SNS (Social Networking Services: Twitter and Facebook). Additionally, the system was operated for four weeks in the central part of Yokohama City in Kanagawa Prefecture, Japan, and the total number of users was 52. Based on the results of the web questionnaire survey, the usefulness of the system when sightseeing was high, and the recommendation function of sightseeing spots, which is an original function, has received mainly good ratings. From the results of the access analysis of users' log data, it is evident that the system has been used by different types of devices, just as it was designed for, and that the system has been used according to the purpose of the present study, which is to support the sightseeing activities of users.

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“…Following the experimental protocol suggested by Gunawardana and Shani in [26] a case study is carried out to evaluate the effects of the previous proposal over Movielens, which is a well-known dataset containing 100,000 movie ratings on 943 users and 1,682 items where each rating is discrete and is given in the range [1,5].…”

Section: Case Studymentioning

confidence: 99%

“…Recommender systems (RSs) are the most successful tool for supporting personalized recommendations [1,2]. RSs have been broadly used in different scenarios like e-commerce [3], e-learning [4], tourism [5], and so on.…”

Section: Introductionmentioning

confidence: 99%

Managing Natural Noise in Recommender Systems

Martínez

Castro

Toledo

2016

Theory and Practice of Natural Computing

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Abstract. E-commerce customers demand quick and easy access to suitable products in large purchase spaces. To support and facilitate this purchasing process to users, recommender systems (RSs) help them to find out the information that best fits their preferences and needs in an overloaded search space. These systems require the elicitation of customers' preferences. However, this elicitation process is not always precise either correct because of external factors such as human errors, uncertainty, human beings inherent inconsistency and so on. Such a problem in RSs is known as natural noise (NN) and can negatively bias recommendations, which leads to poor user's experience. Different proposals have been presented to deal with natural noise in RSs. Several of them require additional interaction with customers. Others just remove noisy information. Recently, new NN approaches dealing with the ratings stored in the user/item rating matrix have raised to deal with NN in a better and simpler way. This contribution is devoted to provide a brief review of the latter approaches revising crisp and fuzzy approaches for dealing with NN in RSs. Eventually it points out as a future research the management of NN in other recommendation scenarios as group RSs.

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A mobile 3D-GIS hybrid recommender system for tourism

Cited by 204 publications

References 63 publications

Aceitação e uso da tecnologia para escolha de destinos turísticos por pessoas da terceira idade: um estudo usando a UTAUT2

Aceitação e uso da tecnologia para escolha de destinos turísticos por pessoas da terceira idade: um estudo usando a UTAUT2

A Sightseeing Spot Recommendation System That Takes into Account the Change in Circumstances of Users

Managing Natural Noise in Recommender Systems

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