Generation of recommendations in an Augmented Reality system applied to tourism based on the context
DOI:
https://doi.org/10.25145/j.pasos.2015.13.045Keywords:
Augmented reality, Recommender system, Filtering system, Context‑aware system, Human‑Computer interaction, PersonalizationAbstract
There are many tourist applications using augmented reality, but it’s necessary have models with open architecture to integrate different recommendation techniques. This paper describes RAMCAT, an adaptive tourist guide which recommended points of interest (POIs). Factors such as personal interests and context-related attributes are important. We present the components of the proposed architecture and its characteristics, emphasizing the integration of different recommender systems, allowing adding new recommendation engine. The article describes with detail, the recommender system based on preferences of tourists. Other characteristic of the system is the feedback through qualifications of tourists and their traceability.
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