Liu, Tie-Yan
Learning to Rank for Information Retrieval
1. Introduction
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2. The Pointwise Approach
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3. The Pairwise Approach
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4. The Listwise Approach
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5. Analysis of the Approaches
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6. Relational Ranking
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7. Query-Dependent Ranking
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8. Semi-supervised Ranking
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9. Transfer Ranking
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10. The LETOR Datasets
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11. Experimental Results on LETOR
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12. Other Datasets
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13. Data Preprocessing for Learning to Rank
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14. Applications of Learning to Rank
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15. Statistical Learning Theory for Ranking
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16. Statistical Ranking Framework
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17. Generalization Analysis for Ranking
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18. Statistical Consistency for Ranking
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19. Summary
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20. Future Work
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21. Mathematical Background
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22. Machine Learning
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Keywords: Computer Science, Information Storage and Retrieval, Artificial Intelligence (incl. Robotics), Probability and Statistics in Computer Science, Pattern Recognition
- Author(s)
- Liu, Tie-Yan
- Publisher
- Springer
- Publication year
- 2011
- Language
- en
- Edition
- 1
- Page amount
- 17 pages
- Category
- Information Technology, Telecommunications
- Format
- Ebook
- eISBN (PDF)
- 9783642142673