A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

Tunisia is well placed in terms of medical tourism and has highly qualified and specialized medical and surgical teams. Integrating social networks in Tunisian medical tourism recommender systems can result in much more accurate recommendations. That is to say, information, interests, and recommendations retrieved from social networks can improve the prediction accuracy. This paper aims to improve traditional recommender systems by incorporating information in social network; including user preferences and influences from social friends. Accordingly, a user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a semantic social recommender system employing a user interest ontology and a Tunisian Medical Tourism ontology. Our system can improve the quality of recommendation for Tunisian tourism domain. Finally, our social recommendation algorithm is implemented in order to be used in a Tunisia tourism Website to assist users interested in visiting Tunisia for medical purposes.

[1]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[2]  Greg M. Allenby,et al.  Modeling Interdependent Consumer Preferences , 2003 .

[3]  Faiez Gargouri,et al.  Toward a User Interest Ontology to Improve Social Network-Based Recommender System , 2014 .

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

[5]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[6]  Giuseppe Lo Re,et al.  Designing Ontology-Driven Recommender Systems for Tourism , 2014, Advances onto the Internet of Things.

[7]  Dalia Sulieman.  Towards Semantic-Social Recommender Systems , 2014 .

[8]  Abdelfattah Triki,et al.  Medical Tourism in Tunisia: Building Relational Loyalty , 2015 .

[9]  Chang-Shing Lee,et al.  Ontological recommendation multi-agent for Tainan City travel , 2009, Expert Syst. Appl..

[10]  Stuart E. Middleton,et al.  Ontology-based Recommender Systems , 2004, Handbook on Ontologies.

[11]  Wesley W. Chu,et al.  A Social Network-Based Recommender System (SNRS) , 2010, Data Mining for Social Network Data.

[12]  Yuefeng Li,et al.  The state-of-the-art in personalized recommender systems for social networking , 2012, Artificial Intelligence Review.

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

[14]  Antonio Moreno,et al.  SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities , 2013, Eng. Appl. Artif. Intell..

[15]  Mohand Boughanem,et al.  Time-Sensitive User Profile for Optimizing Search Personlization , 2014, UMAP.

[16]  Kwan-Liu Ma,et al.  Visualizing Social Networks , 2011, Social Network Data Analytics.

[17]  Robin Burke,et al.  Knowledge-based recommender systems , 2000 .

[18]  Alessandro Micarelli,et al.  User Profiles for Personalized Information Access , 2007, The Adaptive Web.

[19]  Leanne White,et al.  Facebook, friends and photos: a snapshot into social networking for generating travel ideas , 2010 .

[20]  B. Pröll,et al.  Covering the semantic space of tourism: an approach based on modularized ontologies , 2009, CIAO '09.

[21]  R. Chanda,et al.  Trade in health services. , 2002, Bulletin of the World Health Organization.

[22]  Francesco Ricci,et al.  Harmonise: A Solution for Data Interoperability , 2002, I3E.

[23]  Josep Lluís de la Rosa i Esteva,et al.  A Taxonomy of Recommender Agents on the Internet , 2003, Artificial Intelligence Review.

[24]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[25]  Constantin Orasan,et al.  Development and Alignment of a Domain-Specific Ontology for Question Answering , 2008, LREC.

[26]  ChengXiang Zhai,et al.  Positional language models for information retrieval , 2009, SIGIR.

[27]  Azadeh Shakery,et al.  Alleviating the cold-start problem of recommender systems using a new hybrid approach , 2010, 2010 5th International Symposium on Telecommunications.

[28]  Alexander Pretschner,et al.  Ontology based personalized search , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[29]  Jorge S. Cardoso.  Developing An Owl Ontology For e-Tourism , 2006, Semantic Web Services, Processes and Applications.

[30]  Martin Hepp,et al.  Towards the semantic web in e-tourism: can annotation do the trick? , 2006, ECIS.

[31]  Fellah Aissa.  Alignement des ontologies : Utilisation de WordNet et une nouvelle mesure structurelle , 2008, CORIA.

[32]  José M. Molina López,et al.  A Multi-Agent architecture for intelligent gathering systems , 2005, AI Communications.

[33]  Thomas R. Gruber,et al.  A Translation Approach to Portable Ontologies , 1993 .

[34]  Stuart E. Middleton,et al.  Ontological user profiling in recommender systems , 2004, TOIS.

[35]  Ling Bian,et al.  A Bayesian network and analytic hierarchy process based personalized recommendations for tourist attractions over the Internet , 2009, Expert Syst. Appl..

[36]  Jean Oh,et al.  Getting from here to there: interactive planning and agent execution for optimizing travel , 2002, AAAI/IAAI.

[37]  Andreas Stafylopatis,et al.  A hybrid movie recommender system based on neural networks , 2005, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05).

[38]  Ying Ding,et al.  TOURISM ONTOLOGY AND SEMANTIC MANAGEMENT SYSTEM: STATE-OF-THE-ARTS ANALYSIS , 2007 .

[39]  Juana María Ruiz-Martínez,et al.  ONTOLOGY POPULATION : AN APPLICATION FOR THE E-TOURISM DOMAIN , 2011 .

[40]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[41]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[42]  Ah-Hwee Tan,et al.  OntoSearch: A Full-Text Search Engine for the Semantic Web , 2006, AAAI.

[43]  Balaji Rajagopalan,et al.  Knowledge-sharing and influence in online social networks via viral marketing , 2003, CACM.

[44]  Faïez Gargouri,et al.  Designing a User Interest Ontology-Driven Social Recommender System: Application for Tunisian Tourism , 2015, PAAMS.

[45]  Marc Lautier,et al.  Export of health services from developing countries: the case of Tunisia. , 2008, Social science & medicine.

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

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

[48]  Ah-Hwee Tan,et al.  Learning user profiles for personalized information dissemination , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

[49]  Bamshad Mobasher,et al.  Ontology-Based Collaborative Recommendation , 2010, ITWP@UMAP.

[50]  Fabio Crestani,et al.  Proximity-based opinion retrieval , 2010, SIGIR '10.