E-Tourism: Context-Aware Points of Interest Finder and Trip Designer

FieldValue
dc.contributor.authorAlghamdi, Hamzah
dc.date.accessioned2017-01-05T20:03:48Z
dc.date.available2017-01-05T20:03:48Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10393/35676
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-633
dc.description.abstractMany countries depend heavily on tourism for their economic growth. The invention of the web has opened new opportunities for tourists to discover new places and live new adventures. However, the number of possible destinations has become huge and even an entire lifespan would not be enough to visit all of these places. Even for one city, there are a significant number of possible places to visit. Nowadays, searching online to find an interesting place to visit is harder than ever, not because there is a lack of information but rather due to the vast amount of information that can be found. Trip planning is a tedious task, especially when the tourist does not want to pick a preplanned itinerary from a traveling agency. That being said, even these preplanned itineraries need a lot of time and effort to be customized. Moreover, the set of itineraries that a tourist can select from is usually limited. In addition, there may be many places that tourists would enjoy visiting but that are not included in the itineraries. Thus, static planners do not always choose the right place at the right time. This is why the planning process should take into consideration many factors in order to give the tourist the best possible suggestions. In this Thesis, we propose an algorithm called the Balanced Orienteering Problem to design trips for tourists. This algorithm, combined with a context-aware recommender system for tourism suggestions, create the infrastructure of the mobile application for the augmented reality tourism guide that we developed. We cover the background knowledge of tour planning problems and tourism recommender systems and describe the existing techniques. Furthermore, a comparison between the existing systems and our algorithm is completed to illustrate that our proposed algorithm yields better results. We also discuss the workflow of our system implementation and how our mobile application is designed. Lastly, we address suggestions for future works and end with a conclusion.
dc.language.isoen
dc.publisherUniversité d'Ottawa / University of Ottawa
dc.subjectE-Tourism
dc.subjectMobile Application
dc.subjectTourism Recommender System;
dc.subjectTour Planning
dc.titleE-Tourism: Context-Aware Points of Interest Finder and Trip Designer
dc.typeThesis
dc.contributor.supervisorEl Saddik, Abdulmotaleb
thesis.degree.nameMASc
thesis.degree.levelMasters
thesis.degree.disciplineGénie / Engineering
uottawa.departmentScience informatique et génie électrique / Electrical Engineering and Computer Science
CollectionThèses, 2011 - // Theses, 2011 -

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