Image-based Travel Recommender System for small tourist destinations
Published 1 January 2011
María Teresa Linaza, Amaia Agirregoikoa, Ander García, José Ignacio Castro Torres, Kepa Aranburu
Citations11
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This paper describes an approach that allows tourists specify their interests through a set of images, from which the system inferences their profile, and calculates a list of resources that match the profile with the destination tourist resources.
Abstract
Most tour planning systems have similar three-step structures: definition of the tourist profile, evaluation of the Points of Interest (PoI), and route optimization. Having in mind that a picture paints a thousand words, this paper describes an approach that allows tourists specify their interests through a set of images, from which the system inferences their profile. Taken into account the choices made by the visitor, the system infers a dynamic profile. Furthermore, the system calculates a list of resources that match the profile with the destination tourist resources. Each resource is associated with a weight which indicates the utility of that resource to the profile of the visitor. Thus, visitors obtain personalized tourism recommendations based on their preferences as a result.
Keywords
Computer Science
IEEE Transactions on Knowledge and Data EngineeringToward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
10,115 Citations2005Gediminas Adomavičius, Alexander Tuzhilin
This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches.
Communications of the ACMRecommender systems
3,685 Citations1997Paul Resnick, Hal R. Varian
This special section includes descriptions of five recommender systems, which provide recommendations as inputs, which the system then aggregates and directs to appropriate recipients, and which combine evaluations with content analysis.
Artificial Intelligence ReviewA Framework for Collaborative, Content-Based and Demographic Filtering
1,307 Citations1999Michael J. Pazzani
The types of information available to determine whether to recommend a particular page to a particular user are described and how each type of information may be used individually and an approach to combining recommendations from multiple sources are discussed.
Artificial Intelligence ReviewA Taxonomy of Recommender Agents on the Internet
637 Citations2003Miquel Montaner, Beatriz López +1 more
A state-of-the-art taxonomy of intelligent recommender agents on the Internet and a cross-dimensional analysis with the aim of providing a starting point for researchers to construct their own recommender system.
User Modeling and User-Adapted InteractionGeneric User Modeling Systems
596 Citations2001Alfred Kobsa
The paper reviews the development of generic user modeling systems over the past twenty years and discusses the architectures that have been explored so far, namely shell systems that form part of the application, central server systems that communicate with several applications, and possible future user modeling agents that physically follow the user.
Lecture notes in computer scienceAdaptive Hypermedia and Adaptive Web-Based Systems
574 Citations2008Shlomo Berkovsky, Francesca Carmagnola +3 more
It sounds good when knowing the adaptive hypermedia and adaptive web based systems in this website, this famous book will serve something that will let you get the best time and moment to spend for reading the book.
User Modeling and User-Adapted InteractionUser Modeling for Adaptive News Access
480 Citations2000Daniel Billsus, Michael J. Pazzani
The induction of hybrid user models that consist of separate models for short-term and long-term interests are proposed, and it is suggested that effective personalization can be achieved without requiring any extra effort from the user.
User Modeling and User-Adapted InteractionInformation Filtering: Overview of Issues, Research and Systems
362 Citations2001Uri Hanani, Bracha Shapira +1 more
Research issues in the Information Filtering research arena are presented, such as user modeling, evaluation standardization and integration with digital libraries and Web repositories, and the framework to classify IF systems according to several parameters is defined.
Computers & Operations ResearchIterated local search for the team orienteering problem with time windows
342 Citations2009Pieter Vansteenwegen, Wouter Souffriau +2 more
A simple, fast and effective iterated local search meta-heuristic to solve the TOPTW and an insert step is combined with a shake step to escape from local optima, produces a heuristic that performs very well on a large and diverse set of instances.
IEEE Intelligent SystemsIntelligent systems for tourism
162 Citations2002Sally D. Stabb, H. Werther +6 more
The authors discuss travel recommender systems, adaptive context aware mobility support for tourists, tourism information systems, information delivery and travel planning information gathering agents.
CABI eBooksDestination recommendation systems: behavioural foundations and applications
142 Citations2006
This chapter discusses travel recommendation systems for the Internet using a case study of DIETORECS, a Case-Based Travel Advisory System for On-the-move Travelers, and the design of Destination Recommendation Systems.
Expert Systems with Applicationssamap: An user-oriented adaptive system for planning tourist visits
124 Citations2006Luis Castillo, Eva Sanchez Armengol +7 more
This tool integrates modules that dynamically capture user models, determine lists of activities that can provide more utility to a user given the past experience of the system with similar users, and generates plans that can be executed by the user.
Information Technology & TourismCase Base Querying for Travel Planning Recommendation
122 Citations2001Francesco Ricci⋆, Hannes Werthner
The general architecture and function of an intelligent recommendation system aimed at supporting a leisure traveller in the task of selecting a tourist destination, bundling a set of products and composing a plan for the travel is described.
DIETORECS: Travel Advisory for Multiple Decision Styles
80 Citations2003Daniel R. Fesenmaier, Francesco Ricci⋆ +3 more
Dietorecs supports decision styles by means of an adaptive behavior which is learned exploiting a case base of recommendation sessions that are stored by the systems.
Tourism Informatics: Visual Travel Recommender Systems, Social Communities, and User Interface Design
39 Citations2009Nalin Sharda
A defining body of research, this innovative collection of cutting-edge e-tourism systems and directions provides academicians, researchers, and practitioners with a better understanding of this expanding industry.
Intelligent Routing System for a Personalised Electronic Tourist Guide
34 Citations2009Ander García, María Teresa Linaza +2 more
An intelligent routing system for a Personalised Electronic Tourist Guide to fulfil the same task and improves the automatic route creation functionality of existing PETs to solve better the needs of tourists.
Quo Vadis Homo Turisticus? Towards a Picture-based Tourist Profiler
12 Citations2007Helmut Berger, Michaela Denk +3 more
An online survey shows a significant relationship between different tourist types and the preference for particular visual impressions conveyed by photographs, indicating that tourist types can be determined by representative photos without necessarily requesting users to provide additional information.
Lecture notes in computer sciencePhoto-Based User Profiling for Tourism Recommender Systems
11 Citations2007Helmut Berger, Michaela Denk +3 more
An online survey revealing significant dependencies between tourism-related photographs and tourist types is conducted, revealing it is now possible to generate a user profile in an enjoyable way by simply selecting photos without enduring lengthy form-based self assessments.
Developing a Visualisation Tool for Tour Planning
4 Citations2007Jayden Kimber, Mladen Georgievski +1 more
This work builds on the SCORM standard to development a Tour Recommendation using Image-based Planning (TRIP) system model that can provide tourists with a visual experience of their proposed travel itinerary.
Lecture notes in computer scienceVUMA: A Visual User Modelling Approach for the Personalisation of Adaptive Systems
2 Citations2008Melanie B. Späth, Owen Conlan
A visual approach to user modelling resulting in the VUMA (Visual User Modelling Approach) tool that can be used in a playful and dynamic manner repeatedly during a user's engagement with a personalisation system.
IGI Global eBooksDeveloping Visual Tourism Recommender Systems
1 Citations2007Mohan Ponnada, Roopa Jakkilinki +1 more
Way of developing visual travel recommender systems (V-TRS) should aim to improve user interaction and provide more control functions within a V- TRS to make tour-planning simple, fun and more interactive.