Empirical justification of the gain and discount function for nDCG

By Evangelos Kanoulas, J. Aslam. 2009

71 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Information Retrieval & Search, Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Tie-Yan Liu
2. Nick Craswell
3. Di He
4. Jimmy J. Lin
5. Ellen M. Voorhees
6. Tao Qin
7. C. Clarke
8. Xinyi Yan

In Information Systems

1. Nick Craswell
2. Ellen M. Voorhees
3. Cheng-hsin Luo
4. Liwei Wang
5. Di He
6. C. Clarke
7. Tie-Yan Liu
8. Xinyi Yan

In Information Retrieval & Search

1. Ellen M. Voorhees
2. C. Clarke
3. Nick Craswell
4. Jimmy J. Lin
5. Liwei Wang
6. Xinyi Yan
7. Cheng-hsin Luo
8. Di He

In Evaluation & Benchmarks

1. Nick Craswell
2. C. Clarke
3. Tie-Yan Liu
4. Xinyi Yan
5. Cheng-hsin Luo
6. Di He
7. Ellen M. Voorhees
8. Liwei Wang

Citations in the corpus

• Human Preferences as Dueling Bandits (2022, background): “Preferences also bypass the difficult problem of converting ordinal relevance grades into a ratio scale in order to compute NDCG and other standard evaluation measures [14, 18, 24, 28, 29].”
• A Theoretical Analysis of NDCG Type Ranking Measures (2013, background): “Given the importance and popularity of NDCG, there have been extensive studies on this measure, mainly in the field of Information Retrieval [13, 12, 14, 15, 16].”