Optimum polynomial retrieval functions based on the probability ranking principle

@article{Fuhr1989OptimumPR,
  title={Optimum polynomial retrieval functions based on the probability ranking principle},
  author={N. Fuhr},
  journal={ACM Trans. Inf. Syst.},
  year={1989},
  volume={7},
  pages={183-204}
}
  • N. Fuhr
  • Published 1989
  • Computer Science
  • ACM Trans. Inf. Syst.
We show that any approach to developing optimum retrieval functions is based on two kinds of assumptions: first, a certain form of representation for documents and requests, and second, additional simplifying assumptions that predefine the type of the retrieval function. [...] Key Result On the other hand, this approach is not suited to log-linear probabilistic models and it needs large samples of relevance feedback data for its application.Expand
Learning to select for information retrieval
Learning to rank for information retrieval
Optimizing search engines using clickthrough data
Learning to Rank for Information Retrieval
  • Tie-Yan Liu
  • Computer Science
  • Found. Trends Inf. Retr.
  • 2009
...
1
2
3
4
5
...

References

Outline of a General Probabilistic Retrieval Model