Social Networks Based Framework for Recommending Touristic Locations

Tourists need tools that can help them to select locations in which they can spend their holidays. We have multiple social networks in which we find information about hotels and about users’ experiences. The problem is how tourists can use this information to build their proper opinion about a particular location to decide if they should go to that place or not. We try in this paper to present a design of a solution that can be used to achieve this task. In this paper, we propose a framework for a recommender system that bases on opinions of persons on the one hand and on of users’ preferences on the other hand to generate recommendations. Indeed, opinions of tourists are extracted from different sources and analyzed to finally extract how the hotels are perceived by their customers in terms of features and activities. The final step consists in matching between these opinions and the users’ preferences to generate the recommendations. A prototype was developed in order to show how this framework is really working.

[1]  Jinguo Liu,et al.  An Interactive Astronaut-Robot System with Gesture Control , 2016, Comput. Intell. Neurosci..

[2]  David Sánchez,et al.  Turist@: Agent-based personalised recommendation of tourist activities , 2012, Expert Syst. Appl..

[3]  Daniel Borrajo,et al.  Planning for tourism routes using social networks , 2017, Expert Syst. Appl..

[4]  Ping-Feng Pai,et al.  Tourism demand forecasting using novel hybrid system , 2014, Expert Syst. Appl..

[5]  Faiez Gargouri,et al.  A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism , 2015, DCAI 2015.

[6]  Antonio Moreno,et al.  Intelligent tourism recommender systems: A survey , 2014, Expert Syst. Appl..

[7]  Y. Blanco-Fernandez,et al.  TripFromTV+: Exploiting social networks to arrange cut-price touristic packages , 2011, 2011 IEEE International Conference on Consumer Electronics (ICCE).

[8]  Analía Amandi,et al.  Building an expert travel agent as a software agent , 2009, Expert Syst. Appl..

[9]  Wahidah Husain,et al.  A Framework of a Personalized Location-based Traveler Recommendation System in Mobile Application , 2012 .

[10]  Logesh Ravi,et al.  A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users , 2016, Comput. Intell. Neurosci..

[11]  Ma Ling,et al.  Personalized e-tourism attraction recommendation based on context , 2013, 2013 10th International Conference on Service Systems and Service Management.

[12]  Mehregan Mahdavi,et al.  DESIGNING A RECOMMENDER SYSTEM BASED ON SOCIAL NETWORKS AND LOCATION BASED SERVICES , 2012 .

[13]  Stanley Loh,et al.  A Tourism Recommender System Based on Collaboration and Text Analysis , 2003, J. Inf. Technol. Tour..

[14]  J González-Boticario.  SAMAP : An user-oriented adaptive system for planning tourist visits , 2017 .

[15]  Laura Sebastia,et al.  On the design of individual and group recommender systems for tourism , 2011, Expert Syst. Appl..

[16]  Ricardo Colomo Palacios,et al.  Sem-Fit: A semantic based expert system to provide recommendations in the tourism domain , 2011, Expert Syst. Appl..