Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking.
Tim BaumgärtnerLeonardo F. R. RibeiroNils ReimersIryna GurevychPublished in: EMNLP (2022)
Keyphrases
- information seeking
- relevance feedback
- information retrieval
- document retrieval
- document ranking
- information retrieval systems
- retrieved documents
- maximal marginal relevance
- relevant documents
- query expansion
- interactive information retrieval
- retrieval systems
- user feedback
- relevance assessments
- retrieval model
- learning to rank
- retrieval quality
- ranking functions
- retrieval strategies
- probabilistic retrieval model
- retrieved images
- retrieval process
- implicit feedback
- search tasks
- relevance model
- test collection
- document collections
- search sessions
- pseudo relevance feedback
- image retrieval
- ranked list
- retrieval framework
- retrieval effectiveness
- vector space model
- query terms
- language model
- information seeking activities
- active learning
- relevance judgments
- tf idf
- information seeking tasks
- relevance ranking
- information extraction
- initial query
- user queries
- relevance scores
- xml retrieval
- key frames
- information resources
- visual features
- web search
- evaluation measures
- average precision
- search engine