Information Retrieval Meets Game Theory: The Ranking Competition Between Documents? Authors.
Nimrod RaiferFiana RaiberMoshe TennenholtzOren KurlandPublished in: SIGIR (2017)
Keyphrases
- game theory
- information retrieval
- maximal marginal relevance
- learning to rank
- document ranking
- game theoretic
- information retrieval systems
- document collections
- document relevance
- relevant documents
- document retrieval
- ranking models
- expert finding
- cooperative
- relevance ranking
- expert search
- nash equilibrium
- retrieval systems
- resource allocation
- search engine
- retrieval strategies
- ranked list
- vector space model
- retrieved documents
- multi agent systems
- effective retrieval
- multi agent learning
- web search
- statistical physics
- ranking functions
- mechanism design
- test collection
- term weights
- fictitious play
- ranking algorithm
- query expansion
- text mining
- related documents
- keywords
- query terms
- language model
- term weighting
- decision theory
- information extraction
- cooperative game theory
- nash equilibria
- retrieval effectiveness
- evolutionary game theory
- financial crisis
- imperfect information
- solution concepts
- retrieval model
- bayesian networks
- machine learning