An Empirical Study of the Use of Multi-dimensional Contexts for Collaborative-Filtering-Based Service Recommendations in IoT Environments.
Joo-Sik SonHan-Gyu KoIn-Young KoPublished in: ICWE (2015)
Keyphrases
- multi dimensional
- collaborative filtering
- recommender systems
- making recommendations
- management system
- user preferences
- recommendation systems
- recommendation quality
- personalized recommendation
- collaborative filtering algorithms
- cold start
- matrix factorization
- online dating
- user ratings
- cold start problem
- context aware services
- content based filtering
- demographic information
- service providers
- recommendation algorithms
- ubiquitous computing environments
- latent factor models
- collaborative filtering recommendation
- item recommendation
- service oriented
- data sparsity
- hybrid recommendation
- user profiles
- end users
- service discovery
- real world
- information services
- dynamic environments
- high dimensional
- product recommendation
- service quality
- computing environments
- active user
- sensor web
- context aware
- information overload
- deal with information overload
- collaborative recommendation
- information filtering
- user feedback
- ambient intelligence
- web services