RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search.
Jianghong ZhouEugene AgichteinPublished in: WWW (2020)
Keyphrases
- learning to rank
- reinforcement learning
- ranking functions
- query dependent
- exploration exploitation dilemma
- information retrieval
- loss function
- balancing exploration and exploitation
- query suggestion
- document retrieval
- evaluation metrics
- direct optimization
- supervised learning
- ranking models
- learning to rank algorithms
- ranking svm
- evaluation measures
- user feedback
- search queries
- ranking algorithm
- retrieval systems
- user queries
- feature vectors
- search engine