Sensor-Based, Context-Aware Recommender Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (15 May 2020) | Viewed by 3415
Special Issue Editors
Interests: recommender systems; affective computing; user modelling; human computer interaction; personalized interaction; human activity recognition
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; human computer interaction; user modelling; adaptive systems in education
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recommender systems use their intelligence to support users in decision-making processes. Their power can increase when information from the user and the context is sensed. The user information can be obtained from wearables so that the user’s emotions, actions performed, location, physical activity, etc., can be taken into account. The context information comes from context-aware sensors where intelligent features can be controlled. In this Special Issue we want to deepen the information that can be collected from sensors to enrich the recommendation process so that the context and the user are really taken into account. In particular, we are interested in comparing existing sensors and identifying if they provide the required information both from the user and the context, or whether new sensors need to be developed to make recommender systems more powerful. In doing so, there is an interplay between the sensor-based recommendation and the user reaction that opens many unresolved questions regarding when and how this should be managed and to what extent this impacts on the user’s decision-making process. In addition, we are also interested in techniques for processing the sensor data collected and the indicators obtained, including how to access them both from the user and the system viewpoints. Finally, new applications for recommender systems that take advantage of this contextual information are welcome.
- Recommendation possibilities with sensor data obtained from commercial wearables.
- Custom-made smart sensors and wearables for new recommendation opportunities.
- Context-aware sensors that can expand the features to be controlled in an ambient intelligent setting.
- Artificial intelligence techniques to process sensor data for recommender systems.
- Intelligent management of the interplay between sensor-based recommendations and the user.
- Goal and quality of indicators obtained from sensor data that can drive the recommendation process.
- Intelligent multimodal delivery of recommendations through diverse sensorial channels.
- User-friendly graphic tools to follow-up the sensor-based context-aware recommendations delivered.
- Application of sensor-based context-aware recommender systems (educational scenarios, affective support, physical activity training, etc.).
Prof. Dr. Olga C. Santos
Prof. Dr. Jesús G. Boticario
Guest Editors
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