A Multi-Criteria Recommender System For Tourism Destination

Today, the transmission of information on tourism through internet has been implemented through several systems, among of them are e-Tourism, tourism virtual reality mapping, tourism reservation system, location-based tourism services and tourism recommender system. Of all those varied systems, tourism recommender system plays awfully vital roles because the system is able to provide any tourism information according to the interest and capability of the tourist. However, the development of the tourism recommender system, in fact, faces some problems, among of them are the complexity of the information contained in the tourism objects, and the difficult information extraction related to the existence of the tourism objects themselves. The information upon tourism objects holds many various aspects in relation to the services which the tourists to be will receive, such as completeness facilities of the tourism objects, easy access to the tourism objects, security guarantee, and so on and so forth. In this study, the methods of weighted sum model (WSM) are implemented to develop recommender system for tourism destination. From analysis result of WSM algorithm obtained characteristic of algorithm to generate tourism object recommendations

A MULTI-CRITERIA RECOMMENDER SYSTEM FOR TOURISM DESTINATION

Today, the transmission of information on tourism through internet has been implemented through several systems, among of them are e-Tourism, tourism virtual reality mapping, tourism reservation system, location-based tourism services and tourism recommender system. Of all those varied systems, tourism recommender system plays awfully vital roles because the system is able to provide any tourism information according to the interest and capability of the tourist. However, the development of the tourism recommender system, in fact, faces some problems, among of them are the complexity of the information contained in the tourism objects, and the difficult information extraction related to the existence of the tourism objects themselves. The information upon tourism objects holds many various aspects in relation to the services which the tourists to be will receive, such as completeness facilities of the tourism objects, easy access to the tourism objects, security guarantee, and so on and so forth. In this study, the methods of weighted sum model (WSM) are implemented to develop recommender system for tourism destination. From analysis result of WSM algorithm obtained characteristic of algorithm to generate tourism object recommendations

Destinations ratings based multi-criteria recommender system for Indonesian halal tourism game

Halal tourism is one of the tourism products that have the prospect of contributing to economic growth in Indonesia. Therefore, the government needs to increase promotions to increase tourist interest in halal tourism destinations in Indonesia. Game is one of the alternative promotional media that can also function as an educational medium for choosing halal tourism that is fun for potential tourists. This study proposes a recommendation system to support knowledge sources in the Indonesian halal tourism game. We use destinations ratings-based multi-criteria recommender system (MCRS) to generate recommendation rankings as a reference for visualizing halal travel for players as potential tourists. This method improves the ability of the conventional tourism recommendation system, which is generally based on a single criterion. In this study, we use eight destinations rating criteria as a reference for calculating the recommender system in the halal tourism game. Each of these criteria is a reference for tourists' assessment of halal tourist destinations in Indonesia. Next, we integrate the cosine-based similarity technique in MCRS to measure the level of similarity between players and previous tourist data sets. This research's testing phase uses the theme of halal tourism destinations in the Batu City area. The test results show that the number and composition of the tourism destinations item rating as input of the recommender system affect the accuracy, precision, recall, and F1 scores. Based on 40 experiments with different tourism destination item rating input configurations, it shows that the average value of accuracy = 0.60, precision = 0.67, recall = 0.64 and F1 score = 0.65

Destinations ratings based multi-criteria recommender system for Indonesian halal tourism game

Halal tourism is one of the tourism products that have the prospect of contributing to economic growth in Indonesia. Therefore, the government needs to increase promotions to increase tourist interest in halal tourism destinations in Indonesia. Game is one of the alternative promotional media that can also function as an educational medium for choosing halal tourism that is fun for potential tourists. This study proposes a recommendation system to support knowledge sources in the Indonesian halal tourism game. We use destinations ratings-based multi-criteria recommender system (MCRS) to generate recommendation rankings as a reference for visualizing halal travel for players as potential tourists. This method improves the ability of the conventional tourism recommendation system, which is generally based on a single criterion. In this study, we use eight destinations rating criteria as a reference for calculating the recommender system in the halal tourism game. Each of these criteria is a reference for tourists' assessment of halal tourist destinations in Indonesia. Next, we integrate the cosine-based similarity technique in MCRS to measure the level of similarity between players and previous tourist data sets. This research's testing phase uses the theme of halal tourism destinations in the Batu City area. The test results show that the number and composition of the tourism destinations item rating as input of the recommender system affect the accuracy, precision, recall, and F1 scores. Based on 40 experiments with different tourism destination item rating input configurations, it shows that the average value of accuracy = 0.60, precision = 0.67, recall = 0.64 and F1 score = 0.65

Selecting tourism site using 6 as tourism destinations framework based multi-criteria recommender system

Batu City is a place with many types of tourism and had many tourists in 2019. However, there was an imbalance of tourist attractions visited from the total number. Tourists are only fixated on famous tourist spots. Therefore, a recommendation system is needed that can provide recommendations for tourists. In this study, we use the Multi-Criteria Recommender System (MCRS) method based on the rating value between users to obtain recommendations from the system regarding selecting tourist destinations. The authors use the 6 As Tourism Destinations (6AsTD) framework for user assessment criteria in this study. The framework consists of six indicators that assess the success of tourism destinations, including attractions, accessibility, amenities, support services, activities, and available packages. The six components are considered the key to the success of a tourist destination under the marketing approach. This study aimed to obtain a recommendation system for selecting tourist destinations using the multi-criteria concept based on the 6AsTD framework. Based on the experimental results, the proposed method has an accuracy rate of up to 72%

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

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

Travel route scheduling based on user’s preferences using simulated annealing

Nowadays, traveling has become a routine activity for many people, so that many researchers have developed studies in the tourism domain, especially for the determination of tourist routes. Based on prior work, the problem of determining travel route is analogous to finding the solution for travelling salesman problem (TSP). However, the majority of works only dealt with generating the travel route within one day and also did not take into account several user’s preference criteria. This paper proposes a model for generating a travel route schedule within a few days, and considers some user needs criteria, so that the determination of a travel route can be considered as a multi-criteria issue. The travel route is generated based on several constraints, such as travel time limits per day, opening/closing hours and the average length of visit for each tourist destination. We use simulated annealing method to generate the optimum travel route. Based on evaluation result, the optimality of the travel route generated by the system is not significantly different with ant colony result. However, our model is far more superior in running time compared to Ant Colony method

A multiple criteria route recommendation system

The work to be developed in this dissertation is part of a larger project called Sustainable Tourism Crowding (STC), which motivation is based on two negative impacts caused by the tourism overload that happens, particularly, in the historic neighborhoods of Lisbon. The goal of this dissertation is then to mitigate those problems: reduce the tourist burden of points of interest in a city that, in addition to the degradation of the tourist experience, causes sustainability problems in different aspects (environmental, social and local). Within the scope of this dissertation, the implementation of one component of a recommendation system is the proposed solution. It is based on a multi-criteria algorithm for recommending pedestrian routes that minimize the passage through more crowded places and maximizes the visit to sustainable points of interest. These routes will be personalized for each user, as they consider their explicit preferences (e.g. time, budget, physical effort) and several constraints taken from other microservices that are part of the global system architecture mentioned above (e.g. weather conditions, crowding levels, points of interest, sustainability). We conclude it is possible to develop a microservice that recommend personalized routes and communicate with other microservices that are part of the global system architecture mentioned above. The analysis of the experimental data from the recommendation system, allows us to conclude that it is possible to obtain a more balanced distribution of the tourist visit, by increasing the visit to more sustainable places of interest and avoiding crowded paths.O trabalho a desenvolver nesta dissertação insere-se num projeto de maior dimensão denominado Sustainable Tourism Crowding (STC), cuja motivação assenta, essencialmente, em dois impactos negativos provocados pela sobrecarga turística que se verifica, nomeadamente, nos bairros históricos de Lisboa. O objetivo desta dissertação é, então, mitigar esses problemas: reduzir a sobrecarga turística dos pontos de interesse mais visitados numa cidade que, além da degradação da experiência turística, causa problemas de sustentabilidade em diversos aspetos (ambiental, social e local). No âmbito desta dissertação, a implementação de um componente de um sistema de recomendação é a solução proposta. Baseia-se num algoritmo multicritério de recomendação de percursos pedonais que minimiza a passagem por locais mais apinhados e maximizam a visita a pontos de interesse mais sustentáveis. Essas rotas serão personalizadas para cada utilizador, pois consideram as suas preferências (por exemplo, tempo, orçamento, nível de esforço físico) e várias restrições retiradas de outros microsserviços que fazem parte da arquitetura do sistema global mencionado acima (por exemplo, condições meteorológicas, níveis de apinhamento, pontos de interesse, níveis de sustentabilidade). Concluímos que é possível desenvolver um microsserviço que recomenda rotas personalizadas e que comunica com outros microsserviços que fazem parte da arquitetura global do sistema mencionada acima. A análise dos dados experimentais do sistema de recomendação, permite-nos concluir que é possível obter uma distribuição mais equilibrada da visita turística, aumentando a visita a pontos de interesse mais sustentáveis e evitando percursos mais apinhados