Reducing the user labeling effort in effective high recall tasks by fine-tuning active learning.
Guilherme Dal BiancoDenio DuarteMarcos André GonçalvesPublished in: J. Intell. Inf. Syst. (2023)
Keyphrases
- fine tuning
- active learning
- high recall
- high precision
- labeling effort
- relevance feedback
- transfer learning
- fine tune
- user preferences
- random sampling
- learning strategies
- machine learning
- recommender systems
- user interface
- semi supervised learning
- labeled data
- collaborative filtering
- natural language
- user feedback
- human users
- object recognition
- batch mode
- information retrieval
- fine tuned
- feature selection
- precision and recall
- user queries
- unsupervised learning
- unlabeled data