A trust-aware latent space mapping approach for cross-domain recommendation.
Guofang MaYuexuan WangXiaolin ZhengXiaoye MiaoQianqiao LiangPublished in: Neurocomputing (2021)
Keyphrases
- trust aware
- cross domain
- latent space
- transfer learning
- recommender systems
- collaborative filtering
- matrix factorization
- trust model
- knowledge transfer
- latent variables
- reinforcement learning
- learning tasks
- gaussian process
- low dimensional
- sentiment classification
- labeled data
- lower dimensional
- target domain
- feature space
- text categorization
- parameter space
- manifold learning
- generative model
- active learning
- gaussian processes
- dimensionality reduction
- semi supervised learning
- multi task
- distance metric
- high dimensional
- machine learning
- machine learning algorithms
- gaussian process latent variable models
- learning algorithm
- knn
- high dimensional data
- text classification
- e government
- unlabeled data
- probabilistic latent semantic analysis
- rating prediction