e-Tourism: A Tourist Recommendation and Planning Application

e-Tourism is a tourist recommendation and planning application to assist users on the organization of a leisure and tourist agenda. First, a recommender system offers the user a list of the city places that are likely of interest to the user. This list takes into account the user demographic classification, the user likes in former trips and the preferences for the current visit. Second, a planning module schedules the list of recommended places according to their temporal characteristics as well as the user restrictions; that is the planning system determines how and when to perform the recommended activities. This is a very relevant feature that most recommender systems lack as it allows the user to have the list of recommended activities organized as an agenda, i.e. to have a totally executable plan.

[1]  David E. Smith Choosing Objectives in Over-Subscription Planning , 2004, ICAPS.

[2]  Paolo Traverso,et al.  Automated planning - theory and practice , 2004 .

[3]  Alfred Kobsa,et al.  User Modeling for Personalized City Tours , 2002, Artificial Intelligence Review.

[4]  Hannes Werthner,et al.  Intelligent Systems in Travel and Tourism , 2003, IJCAI.

[5]  Anna Goy,et al.  Dynamic Configuration of a Personalized Tourist Agenda , 2004, ICWI.

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

[7]  Keith Cheverst,et al.  The role of adaptive hypermedia in a context-aware tourist GUIDE , 2002, CACM.

[8]  Francesco Ricci,et al.  Integrating Travel Planning and On-Tour Support in a Case-Based Recommender System , 2002 .

[9]  Michael J. Pazzani,et al.  A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.

[10]  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.

[11]  A. Gerevini,et al.  Plan Constraints and Preferences in PDDL 3 The Language of the Fifth International Planning Competition , 2005 .

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

[13]  A. Felfernig,et al.  A Short Survey of Recommendation Technologies in Travel and Tourism , 2006 .

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

[15]  Brendon Towle,et al.  Knowledge Based Recommender Systems Using Explicit User Models , 2000 .

[16]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[17]  Dietmar Jannach,et al.  Developing a Conversational Travel Advisor with ADVISOR SUITE , 2007, ENTER.

[18]  Peretz Shoval,et al.  Information Filtering: Overview of Issues, Research and Systems , 2001, User Modeling and User-Adapted Interaction.

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

[20]  R. Malaka,et al.  CRUMPET: creation of user-friendly mobile services personalised for tourism , 2001 .

[21]  J PazzaniMichael A Framework for Collaborative, Content-Based and Demographic Filtering , 1999 .

[22]  Subbarao Kambhampati,et al.  Over-Subscription Planning with Numeric Goals , 2005, IJCAI.

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