CS
- TrustWalker: A Random Walk Model for Combining Trust-based and Item-based Recommendation '09 2013.04.20
- Item-Based Collaborative Filtering Recommendation Algorithms '01 2013.04.20
- Recommendation via Query Centered Random Walk on K-Partite Graph '07 2013.04.20
- Grocery Shopping Recommendations Based on Basket-Sensitive Random Walk '09 2013.04.20
- One-Class Collaborative Filtering '08 2013.04.20
- Tensor 2013.04.18
- Pearson correlation coefficient 2013.04.16
- Low-rank Approximation 2013.04.11
- Gram–Schmidt process 2013.04.11
- Eigendecomposition (Spectral Decomposition) 2013.04.10
- Linear Map (Linear Transformation) 2013.04.07
- FP Growth 2013.04.07
- Language Model 2013.04.05
- Performance of Recommender Algorithms on Top-N Recommendation Tasks '10 2013.04.01
- Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences '97 2013.04.01
- Google News Personalization: Scalable Online Collaborative Filtering '07 2013.04.01
- Collaborative Filtering, CF 2013.03.31
- Matrix Decomposition (Matrix Factorization) 2013.03.29
- Kalman Filtering 2013.03.28
- MinHash 2013.03.28
- Singular Value Decomposition, SVD 2013.03.28
- Recommender Systems Handbook [2011] 2013.03.27
- Recommender Systems 2013.03.27
- Erlang 2013.03.25
- A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models '98 2013.03.22
- Latent Semantic Indexing, LSI 2013.03.20
- AdaBoost 2013.03.15
- Hidden Markov Model, HMM 2013.03.15
- Independent Component Analysis, ICA 2013.03.15
- Principal Component Analysis, PCA 2013.03.15