CRUC: Cold-start Recommendations Using Collaborative Filtering in Internet of Things
This addresses the cold-start problem for IoT systems, but it appears incremental as it applies collaborative filtering to a specific domain.
The paper tackles the cold-start problem in IoT, where few users are interconnected initially, by proposing the CRUC scheme using collaborative filtering, and experimental results show it efficiently solves the issue.
The Internet of Things (IoT) aims at interconnecting everyday objects (including both things and users) and then using this connection information to provide customized user services. However, IoT does not work in its initial stages without adequate acquisition of user preferences. This is caused by cold-start problem that is a situation where only few users are interconnected. To this end, we propose CRUC scheme - Cold-start Recommendations Using Collaborative Filtering in IoT, involving formulation, filtering and prediction steps. Extensive experiments over real cases and simulation have been performed to evaluate the performance of CRUC scheme. Experimental results show that CRUC efficiently solves the cold-start problem in IoT.