Web Intelligence in Tourism: User Modeling and Recommender System
Bruno Coleho, Constantino Lopes Martins, Ana Almeida · 2010
This paper presents a successful attempt at evolving web intelligence in the tourism scenario, namely throughout two main areas: User Modeling and Recommender Systems. The first subject deals with the correct modeling of tourists’ profiles using a wide variety of techniques, such as stereotypes, keywords and psychological models. These techniques, besides presenting user interests with great coherence and completeness, allow for the reduction of several current problems such as the cold start issue, gray sheep individuals and overspecialization. The recommender system, by making use of all user models’ building blocks, brings an interesting, innovative and hybrid nature to the area, with benefits such as behavioral filtering, multi-technique resourcefulness and on-the-fly suggestions. The architecture was already tested in the scope of a prototype regarding the city of Porto, in Portugal.