Learning to Rank for Information Retrieval

Douban
Learning to Rank for Information Retrieval

Entre ou cadastre-se para escrever uma análise ou adicionar este item à sua coleção.

ISBN: 9781601982445
autor: Tie-Yan Liu
casa editorial: Now Publishers Inc
data de publicação: 2009 -6
séries: Foundations and Trends(R) in Theoretical Computer Science
preço: USD 85.00
número de páginas: 120

/ 10

1 avaliações

Avaliações insuficientes
Emprestar ou Comprar

Tie-Yan Liu   

visão geral

nada até agora.

conteúdo

1 Introduction
1.1 Ranking in IR
1.2 Learning to Rank
1.3 About this Tutorial
2 The Pointwise Approach
2.1 Regression based Algorithms
2.2 Classification based Algorithms
2.3 Ordinal Regression based Algorithms
2.4 Discussions
3 The Pairwise Approach
3.1 Example Algorithms
3.2 Discussions
4 The Listwise Approach
4.1 Direct Optimization of IR Evaluation Measures
4.2 Minimization of Listwise Ranking Losses
4.3 Discussions
5 Analysis of the Approaches
5.1 The Pointwise Approach
5.2 The Pairwise Approach
5.3 The Listwise Approach
5.4 Discussions
6 Benchmarking Learning-to-Rank Algorithms
6.1 The LETOR Collection
6.2 Experimental Results on LETOR
7 Statistical Ranking Theory
7.1 Conventional Generalization Analyses on Ranking
7.2 A Query-level Ranking Framework
7.3 Query-level Generalization Analysis
7.4 Discussions
8 Summary and Outlook
Acknowledgments References

comentários
Análises
notas