Learning to rank for information retrieval and natural language processing [electronic resource] / Hang Li.
Saved in:
| Online Access: |
Full Text (via Morgan & Claypool) |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :
Morgan & Claypool,
©2011.
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| Series: | Synthesis lectures on human language technologies (Online) ;
# 12. |
| Subjects: |
| 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. |
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| Item Description: | Part of: Synthesis digital library of engineering and computer science. Series from website. |
| Physical Description: | 1 electronic text (ix, 101 pages) : illustrations, digital file. |
| Bibliography: | Includes bibliographical references (pages 89-100) |
| ISBN: | 9781608457083 (electronic bk.) |
| ISSN: | 1947-4059 ; |
| DOI: | 10.2200/S00348ED1V01Y201104HLT012 |