Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2012/poster/132> ?p ?o. }
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- 132 creator lidia-grauer.
- 132 creator pavel-serdyukov.
- 132 creator yury-logachev.
- 132 type InProceedings.
- 132 label "Tuning parameters of the Expected Reciprocal Rank".
- 132 sameAs 132.
- 132 abstract "There are several popular IR metrics based on an underlying user model. Most of them are parameterized. Usually parameters of these metrics are chosen on the basis of general considerations and not validated by experiments with real users. Particularly, the parameters of the Expected Reciprocal Rank measure are the normalized parameters of the DCG metric, and the latter are chosen in an ad-hoc manner.We suggest two approaches for adjusting parameters of the ERR model by analyzing real users behaviour: one based on a controlled experiment and another relying on search log analysis. We show that our approaches generate parameters that are largely dierent from the commonly used parameters of the ERR model.".
- 132 hasAuthorList authorList.
- 132 isPartOf proceedings.
- 132 isPartOf proceedings.
- 132 keyword "evaluation".
- 132 keyword "expected reciprocal rank".
- 132 keyword "information retrieval measures".
- 132 keyword "user models".
- 132 title "Tuning parameters of the Expected Reciprocal Rank".