Paper Info
Title
Modeling A Mobile Group Recommender System For Tourism With Intelligent Agents And Gamification
Abstract
To provide recommendations to groups of people is a complex task, especially due to the group's heterogeneity and conflicting preferences and personalities. This heterogeneity is even deeper in occasional groups formed for predefined tour packages in tourism. Group Recommender Systems (GRS) are being designed for helping in situations like those. However, many limitations can still be found, either on their time-consuming configurations and excessive intrusiveness to build the tourists' profile, or in their lack of concern for the tourists' interests during the planning and tours, like feeling a greater liberty, diminish the sense of fear/being lost, increase their sense of companionship, and promote the social interaction among them without losing a personalized experience. In this paper, we propose a conceptual model that intends to enhance GRS for tourism by using gamification techniques, intelligent agents modeled with the tourists' context and profile, such as psychological and socio-cultural aspects, and dialogue games between the agents for the post-recommendation process. Some important aspects of a GRS for tourism are also discussed, opening the way for the proposed conceptual model, which we believe will help to solve the identified limitations.
Year
DOI
Venue
2019
10.1007/978-3-030-29859-3_49
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2019
Keywords
Field
DocType
Group Recommender Systems, Mobile tourism, Context-awareness, Gamification, Multi-agent systems
Recommender system,Intelligent agent,Computer science,Tourism,Human–computer interaction,Artificial intelligence,Machine learning
Conference
Volume
ISSN
Citations 
11734
0302-9743
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Patrícia Alves112.03
João Carneiro200.34
Goreti Marreiros314239.40
Paulo Novais4883171.45