e-Turist: An Intelligent Personalised Trip Guide (original) (raw)

myVisitPlannerGR: Personalized Itinerary Planning System for Tourism

This application paper presents MYVISITPLANNERGR, an intelligent web-based system aiming at making 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 ontology 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 proposed 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 machine learning techniques to dynamically infer and update the user’s profile, concerning his preferences 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.

e-Turist: Electronic Mobile Tourist Guide

Contemporary Trends in Tourism and Hospitality 2013, Novi Sad, 2013

In the e-Turist project we developed a mobile application that provide experience comparable to that offered by a professional tour guide, but tailored to each individual tourist. The tourist can enter his interests (entertainment, active tourism, gastronomy, cultural and natural heritage), the available time and any special requirements he/she may have. Based on these and other data such as opening time, the application prepares a personalized sightseeing program. To this end, it uses a recommender system that combines the extensive knowledge on tourism provided by Turistica with state-of-the art intelligent computer methods developed at Jožef Stefan Institute. Afterwards, the application guides the tourist using the GPS, providing a multilingual written and voice description accompanied by photos. The tourist may comment and rate each sight, which is then used by the recommender system and tourism services providers to improve their services.

Information Management for Travelers: Towards Better Route and Leisure Suggestion

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016

Contemporary travel information services are connected to huge amount of travel related data used for improving personalized suggestions. Such suggestions include finding better routes, access to amusement and educational amenities implemented as digital services, as well as the features for people collaboration, and for planning leisure time with respect to existing attractiveness evaluation algorithms under time-budget constraints. Much effort is required for supporting personalized itineraries construction in such a way which would leverage existing cultural and technological user experience. In this paper we analyze the underlying algorithms and major components being an implementation of the proposed model investigated with particular attention to annotated leisure walk route construction, traveler collaboration and travel meeting management. In sum, we make an effort to address a number of complex issues in the area of developing models, interfaces and algorithms required by modern travel services considered as an essential application of a human-centric computing multidisciplinary paradigm.

Personalized Tourist Route Generation

Lecture Notes in Computer Science, 2010

When tourists are at a destination, they typically search for information in the Local Tourist Organizations. There, the staff determines the profile of the tourists and their restrictions. Combining this information with their up-to-date knowledge about the local attractions and public transportation, they suggest a personalized route for the tourist agenda. Finally, they fine tune up this route to better fit tourists' needs. We present an intelligent routing system to fulfil the same task. We divide this process in three steps: recommendation, route generation and route customization. We focus on the last two steps and analyze them. We model the tourist planning problem, integrating public transportation, as the Time Dependent Team Orienteering Problem with Time Windows (TDTOPTW) and we present an heuristic able to solve it on real-time. Finally, we show the prototype which generates and customizes routes in real-time.

A Web Application for Recommending Personalized Mobile Tourist Routes

IET Software, 2012

This study deals with the problem of deriving personalised recommendations for daily sightseeing itineraries for tourists visiting any destination. The authors' approach considers selected places of interest that a traveller would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. The authors' method enables the planning of customised daily personalised tourist itineraries considering user preferences, time available for visiting sights on a daily basis, opening days of sights and average visiting times for these sights. Herein, the authors propose a heuristic solution to this problem addressed to both web and mobile web users. Evaluation and simulation results verify the competence of the authors' approach against an alternative method.

An Efficient Algorithm for Recommending Personalized Mobile Tourist Routes

This article deals with the problem of deriving personalized recommendations for daily sightseeing itineraries for tourists visiting any destination. Our approach considers selected places of interest that a traveller would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. Our method enables the planning of customised daily personalised tourist itineraries considering user preferences, time available for visiting ...

PersTour: A Personalized Tour Recommendation and Planning System

Extended Proceedings of the 27th ACM Conference on Hypertext and Social Media (HT'16), 2016

Touring is a popular but time-consuming activity, due to the need to identify interesting attractions or Places-of-Interest (POIs) and structure these POIs in the form of a time-constrained tour itinerary. To solve this challenge, we propose the Personalized Tour Recommendation and Planning (PersTour) system. The PersTour system is able to plan for a customized tour itinerary where the recommended POIs and visit durations are personalized based on the tourist's interest preferences. In addition, tourists have the option to indicate their trip constraints (e.g., a preferred start-ing/ending location and a specific tour duration) to further customize their tour itinerary.

Personalized routes for mobile tourism

2011 IEEE 7th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2011

Τhis paper deals with the problem of deriving personalized recommendations for daily sightseeing itineraries for tourists visiting any destination. Our approach considers selected places of interest that a traveler would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. Our method enables the planning of customized daily personalized tourist itineraries considering user preferences, time available for visiting sights in daily basis, opening days of sights and average visiting times for these sights. Herein, we propose a heuristic solution to this problem and discuss its implementation aspects.

Web application for recommending personalised mobile tourist routes

This study deals with the problem of deriving personalised recommendations for daily sightseeing itineraries for tourists visiting any destination. The authors' approach considers selected places of interest that a traveller would potentially wish to visit and derives a near-optimal itinerary for each day of visit; the places of potential interest are selected based on stated or implied user preferences. The authors' method enables the planning of customised daily personalised tourist itineraries considering user preferences, time available for visiting sights on a daily basis, opening days of sights and average visiting times for these sights. Herein, the authors propose a heuristic solution to this problem addressed to both web and mobile web users. Evaluation and simulation results verify the competence of the authors' approach against an alternative method.

RecTour: A Recommender System for Tourists

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2012

This paper presents a recommender system that provides personalized information about locations of potential interest to a tourist. The system generates suggestions, consisting of touristic places, according to the current position and history data describing the tourist movements. For the selection of tourist sites, the system uses a set of points of interest a priori identified. We evaluate our system on two datasets: a real and a synthetic one, both storing trajectories describing previous movements of tourists. The proposed solution has high applicability and the results show that the solution is both efficient and viable.