Iterative learning to rank from explicit relevance feedback.
Mateus PereiraElham EtemadFernando V. PaulovichPublished in: SAC (2020)
Keyphrases
- learning to rank
- relevance feedback
- document retrieval
- information retrieval
- ranking functions
- user feedback
- relevance judgments
- information retrieval systems
- loss function
- evaluation measures
- ranking svm
- retrieval model
- direct optimization
- evaluation metrics
- relevant documents
- image retrieval
- document collections
- pseudo relevance feedback
- query dependent
- retrieval effectiveness
- low level features
- learning to rank algorithms
- directly optimize
- machine learning
- collaborative filtering
- active learning
- supervised learning
- query suggestion
- retrieved documents
- information extraction
- ranking list
- support vector
- learning algorithm
- data sets
- exploration exploitation dilemma