Turist@: Agent-based personalised recommendation of tourist activities

Recommender systems in e-Tourism normally focus on helping tourists to select appropriate destinations. A related problem that has been less explored in the literature is how to provide personalised recommendations of cultural and leisure activities when the tourist has already arrived at the destination. This paper presents a novel recommendation system, [email protected], which addresses this issue. Its agent-based modular design permits to model different kinds of activities in a flexible way, and allows the implementation of a location-aware front-end in the mobile device of the user. Special care has been put in the recommendation engine, implemented via a specialised Recommender Agent. It incorporates a mixture of content-based and collaborative recommendation strategies, thus avoiding the drawbacks of each individual method, and is able to perform recommendations in heterogeneous scenarios. Recommendations take into account user profiles which are implicitly updated after the analysis of user actions (e.g., queries, evaluations). The system has been successfully deployed and tested in the World Heritage-listed city of Tarragona.

[1]  David Sánchez,et al.  Organizational structures supported by agent-oriented methodologies , 2011, J. Syst. Softw..

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

[3]  Pabitra Mitra,et al.  Feature weighting in content based recommendation system using social network analysis , 2008, WWW.

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

[5]  Gülçin Büyüközkan,et al.  Intelligent system applications in electronic tourism , 2011, Expert Syst. Appl..

[6]  David Sánchez,et al.  Provision of agent-based health care services , 2003, AI Commun..

[7]  Gülçin Büyüközkan,et al.  An integrated case-based reasoning and MCDM system for Web based tourism destination planning , 2011, Expert Syst. Appl..

[8]  Antonio Moreno,et al.  SigTur/E-Destination: A System for the Management of Complex Tourist Regions , 2011, ENTER.

[9]  Nick Antonopoulos,et al.  CinemaScreen recommender agent: combining collaborative and content-based filtering , 2006, IEEE Intelligent Systems.

[10]  Francesco Ricci,et al.  ITR: A Case-Based Travel Advisory System , 2002, ECCBR.

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

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

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

[14]  Vasile Palade,et al.  Building a Knowledge Base for Implementing a Web-Based Computerized Recommendation System , 2007, Int. J. Artif. Intell. Tools.

[15]  Francesco Ricci,et al.  DIETORECS: Travel Advisory for Multiple Decision Styles , 2003, ENTER.

[16]  Elaine Rich,et al.  User Modeling via Stereotypes , 1998, Cogn. Sci..

[17]  Alexandros G Moukas,et al.  Amalthaea--information filtering and discovery using a multiagent evolving system , 1997 .

[18]  Michael Wooldridge,et al.  Introduction to multiagent systems , 2001 .

[19]  Maria Ganzha,et al.  Introducing Collaborative Filtering into an Agent-Based Travel Support System , 2007, 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops.

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

[21]  B. Everitt,et al.  Cluster Analysis Ed. 5 , 2011 .

[22]  Jesus Boticario,et al.  samap: An user-oriented adaptive system for planning tourist visits , 2008, Expert Syst. Appl..

[23]  David Sánchez,et al.  A Multi-Criteria Decision Aid Agent Applied to the Selection of the Best Receiver in a Transplant , 2002, ICEIS.

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

[25]  David Sánchez,et al.  Agent-based execution of personalised home care treatments , 2011, Applied Intelligence.

[26]  Aïda Valls,et al.  Thesis: ClusDM: a Multiple Criteria Decision Method for heterogeneous data sets , 2003, AI Commun..

[27]  Alexandros Moukas Amalthaea Information Discovery and Filtering Using a Multiagent Evolving Ecosystem , 1997, Appl. Artif. Intell..

[28]  David Sánchez,et al.  Agent-based platform to support the execution of parallel tasks , 2011, Expert Syst. Appl..

[29]  Joaquin Delgado,et al.  Knowledge Bases and User Profiling in Travel and Hospitality Recommender Systems , 2002, ENTER.

[30]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

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

[32]  Montserrat Batet,et al.  Using expert's rules as background knowledge in the ClusDM methodology , 2009, Eur. J. Oper. Res..

[33]  Laura Sebastia,et al.  e-Tourism: A Tourist Recommendation and Planning Application , 2008, 2008 20th IEEE International Conference on Tools with Artificial Intelligence.

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

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

[36]  A. Valls CLUSDM: a multiple criteria decision making method for heterogeneous data sets , 2002 .

[37]  Liliana Ardissono,et al.  Intrigue: Personalized recommendation of tourist attractions for desktop and hand held devices , 2003, Appl. Artif. Intell..

[38]  Dirk Van Oudheusden,et al.  The City Trip Planner: An expert system for tourists , 2011, Expert Syst. Appl..