Learning to rank relevant and novel documents through user feedback.
Abhimanyu LadYiming YangPublished in: CIKM (2010)
Keyphrases
- user feedback
- learning to rank
- relevance judgments
- information retrieval
- document retrieval
- ranking functions
- retrieval process
- relevant documents
- retrieval systems
- ranking models
- document collections
- relevance assessments
- loss function
- test collection
- evaluation measures
- evaluation metrics
- relevance feedback
- information retrieval systems
- implicit feedback
- ranking svm
- user interaction
- query dependent
- collaborative filtering
- supervised learning
- language model
- document clustering
- expert search
- xml documents
- web documents
- clickthrough data
- web search
- keywords
- vector space model
- ranked list
- retrieval model
- metadata
- digital libraries
- query processing
- data sets
- query expansion