Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/885
Title: myVisitPlannerGR: Personalized Itinerary Planning System for Tourism
Authors: Refanidis, Ioannis
Emmanouilidis, Christos
Sakellariou, Ilias
Alexiadis, Anastasios
Koutsiamanis, Remous-Aris
Agnantis, Konstantinos
Tasidou, Aimilia
Kokkoras, Fotios
Efraimidis, Pavlos S.
Editors: Likas, A.
Blekas, K.
Kalles, D.
Type: Conference Paper
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Activity Type
User Profile
Cultural Event
Extraction Rule
Meeting Schedule
Issue Date: May-2014
Publisher: Springer International Publishing
Volume: 8445
First Page: 615
Last Page: 629
Volume Title: Artificial Intelligence: Methods and Applications. SETN 2014
Part of Series: Lecture Notes on Computer Science
Part of Series: Lecture Notes on Computer Science
Abstract: This application paper presents MYVISITPLANNERGR, an intelligent web-based system aiming at mak-ing recommendations that help visitors and residents of the region of Northern Greece to plan their leisure, cultural and other activities during their stay in this area. The system encompasses a rich on-tology of activities, categorized across dimensions such as activity type, historical era, user profile and age group. Each activity is characterized by attributes describing its location, cost, availability and duration range. The system makes activity recommendations based on user-selected criteria, such as visit duration and timing, geographical areas of interest and visit profiling. The user edits the pro-posed list and the system creates a plan, taking into account temporal and geographical constraints imposed by the selected activities, as well as by other events in the user’s calendar. The user may edit the proposed plan or request alternative plans. A recommendation engine employs non-intrusive ma-chine learning techniques to dynamically infer and update the user’s profile, concerning his prefer-ences for both activities and resulting plans, while taking privacy concerns into account. The system is coupled with a module to semi-automatically feed its database with new activities in the area.
URI: https://doi.org/10.1007/978-3-319-07064-3_53
https://ruomo.lib.uom.gr/handle/7000/885
ISBN: 978-3-319-07063-6
Electronic ISBN: 978-3-319-07064-3
Other Identifiers: 10.1007/978-3-319-07064-3_53
Appears in Collections:Department of Applied Informatics

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