Imputation-boosted collaborative filtering using machine learning classifiers.
Xiaoyuan SuTaghi M. KhoshgoftaarXingquan ZhuRussell GreinerPublished in: SAC (2008)
Keyphrases
- collaborative filtering
- machine learning
- machine learning algorithms
- machine learning methods
- decision trees
- machine learning approaches
- feature selection
- supervised classification
- random forests
- matrix factorization
- missing values
- pattern recognition
- data mining
- boosted classifiers
- missing data
- user preferences
- training data
- support vector
- text classification
- learning algorithm
- multiple classifier systems
- recommender systems
- maximum margin matrix factorization
- feature set
- learning problems
- transfer learning
- learning tasks
- text mining
- decision stumps
- learning classifier systems
- linear classifiers
- ensemble learning
- training set
- information extraction
- training examples
- deal with information overload
- supervised learning
- making recommendations
- training samples
- naive bayes
- data sparsity
- active learning
- inductive logic programming
- computer vision
- ensemble classifier
- classifier combination
- feature extraction
- support vector machine
- test set
- semi supervised learning
- svm classifier