Parallel rule-based selective sampling and on-demand learning to rank.
Mateus Ferreira e FreitasDaniel Xavier de SousaWellington S. MartinsThierson Couto RosaRodrigo M. SilvaMarcos André GonçalvesPublished in: Concurr. Comput. Pract. Exp. (2019)
Keyphrases
- learning to rank
- selective sampling
- active sampling
- active learning
- random sampling
- ranking functions
- information retrieval
- loss function
- document retrieval
- test collection
- feature selection
- ranking svm
- support vector machine
- supervised learning
- collaborative filtering
- machine learning
- learning to rank algorithms
- retrieval systems
- structured data
- web search engines
- feature vectors
- training set
- support vector