Bridging the Gap between Click and Relevance for Learning-to-Rank with Minimal Supervision.
Jae-woong LeeYoung-In SongDeokmin HaamSanghoon LeeWoo-Sik ChoiJongwuk LeePublished in: CIKM (2020)
Keyphrases
- learning to rank
- relevance judgments
- information retrieval
- learning to rank algorithms
- user clicks
- query dependent
- ranking functions
- behavioral targeting
- web search
- test collection
- ranking models
- loss function
- search engine
- ranking svm
- ranking list
- document retrieval
- evaluation metrics
- evaluation measures
- learn a ranking function
- direct optimization
- user feedback
- normalized discounted cumulative gain
- relevance feedback
- user behavior
- retrieval systems
- implicit feedback
- sponsored search
- relevance ranking
- collaborative filtering
- click data
- learning algorithm
- retrieval effectiveness
- information extraction
- supervised learning
- web search engines
- retrieved documents
- ranking algorithm
- relevant documents
- click logs
- relevance assessments
- online advertising
- query suggestion
- average precision