Otium: A web based planner for tourism and leisure

Authors:
Arturo Montejo-Ráez;José Manuel Perea-Ortega;Miguel Ángel García-Cumbreras;Fernando Martínez-Santiago
Affiliations:
Department of Computer Science, University of Jaén, Jaén 23071, Spain;Department of Computer Science, University of Jaén, Jaén 23071, Spain;Department of Computer Science, University of Jaén, Jaén 23071, Spain;Department of Computer Science, University of Jaén, Jaén 23071, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 9
Cited 2

A brief survey of web data extraction tools

ACM SIGMOD Record
Automatic information extraction from large websites

Journal of the ACM (JACM)
Agent-mediated architecture for reputation-based electronic tourism systems: a neural network approach

Information and Management
samap: An user-oriented adaptive system for planning tourist visits

Expert Systems with Applications: An International Journal
Opinion Mining and Sentiment Analysis

Foundations and Trends in Information Retrieval
A Product Recommendation System Using Vector Space Model and Association Rule

ICIT '08 Proceedings of the 2008 International Conference on Information Technology
Saying good-bye to DBMSs, designing effective interfaces

Communications of the ACM - The Status of the P versus NP Problem
Workshop on recommender systems and the social web

Proceedings of the third ACM conference on Recommender systems
Content-based recommendation systems

The adaptive web

GeOasis: A knowledge-based geo-referenced tourist assistant

Expert Systems with Applications: An International Journal
SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities

Engineering Applications of Artificial Intelligence

Quantified Score

Hi-index	12.06

Visualization

Abstract

This paper introduces the Otium planner system for scheduling of leisure tasks in tourism. This novel service allows users to create their own agenda of activities within specified dates. Activities are selected from a list of recommended events according to last selected events, user preferences and other parameters. The proposed restrictions on the recommendation procedure have been found to capture static and dynamic user context. The recommendation function is linear and shows low computational cost. The events are extracted from web sources with almost no human manipulation, so the recommender is always showing new and recent events. The Ajax-based web interface eases the creation of the final plan, offering an interactive experience to the user. We consider that the trade-off between interactivity and recommendation complexity exits, and that the second issue is preferable in this type of services. The details about the design and implementation of the system are described, along with the issues the system resolves and some guidelines for enhancement.