A Short Introduction to Learning to Rank

Hang LI  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E94-D   No.10   pp.1854-1862
Publication Date: 2011/10/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E94.D.1854
Print ISSN: 0916-8532
Type of Manuscript: INVITED PAPER (Special Section on Information-Based Induction Sciences and Machine Learning)
Category: 
Keyword: 
learning to rank,  information retrieval,  natural language processing,  SVM,  

Full Text: FreePDF(311KB)


Summary: 
Learning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in Information Retrieval, Natural Language Processing, and Data Mining. Intensive studies have been conducted on the problem and significant progress has been made [1],[2]. This short paper gives an introduction to learning to rank, and it specifically explains the fundamental problems, existing approaches, and future work of learning to rank. Several learning to rank methods using SVM techniques are described in details.