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Learning to rank for information retrieval and natural language processing /

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Bibliographic Details
Main Author: Li, Hang, 1965-
Format: eBook
Language:English
Published: [San Rafael, Calif.] : Morgan & Claypool Publishers, [2011]
Series:Synthesis lectures on human language technologies ; lecture #12.
Subjects:
Supervised learning (Machine learning)
Ranking and selection (Statistics)
Information retrieval.
Natural language processing (Computer science)
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Abstract: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 recently and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, existing approaches, theories, applications, and future work.
Item Description:Title from PDF title page (Morgan & Claypool, viewed May 3, 2011).
Electronic resource.
Physical Description:1 online resource.
Bibliography:Includes bibliographical references (pages 89-100).
ISBN:9781608457083 (ebook)
1608457087 (ebook)
ISSN:1947-4059 ;