Learning to Rank for Information Retrieval

1. Introduction
Tie-Yan Liu

2. The Pointwise Approach
Tie-Yan Liu

3. The Pairwise Approach
Tie-Yan Liu

4. The Listwise Approach
Tie-Yan Liu

5. Analysis of the Approaches
Tie-Yan Liu

6. Relational Ranking
Tie-Yan Liu

7. Query-Dependent Ranking
Tie-Yan Liu

8. Semi-supervised Ranking
Tie-Yan Liu

9. Transfer Ranking
Tie-Yan Liu

10. The LETOR Datasets
Tie-Yan Liu

11. Experimental Results on LETOR
Tie-Yan Liu

12. Other Datasets
Tie-Yan Liu

13. Data Preprocessing for Learning to Rank
Tie-Yan Liu

14. Applications of Learning to Rank
Tie-Yan Liu

15. Statistical Learning Theory for Ranking
Tie-Yan Liu

16. Statistical Ranking Framework
Tie-Yan Liu

17. Generalization Analysis for Ranking
Tie-Yan Liu

18. Statistical Consistency for Ranking
Tie-Yan Liu

19. Summary
Tie-Yan Liu

20. Future Work
Tie-Yan Liu

21. Mathematical Background
Tie-Yan Liu

22. Machine Learning
Tie-Yan Liu

Nyckelord: Computer Science, Information Storage and Retrieval, Artificial Intelligence (incl. Robotics), Probability and Statistics in Computer Science, Pattern Recognition