Norwell, MA Now Publishers 2009 Trade paperback New. Trade paperback (US). Glued binding. 122 p. Foundations and Trends(r) in Information Retrieval, 9.

Now Publishers 7/30/2009 12: 00: 00 AM Softcover New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.

Now Publishers 7/30/2009 12: 00: 00 AM Softcover PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.

Paperback / softback. New. Provides an introduction to the field of learning to rank, a hot research topic in information retrieval and machine learning. Learning to Rank for Information Retrieval is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners. ISBN 1601982445 9781601982445 [GB]

ISBN10: 1601982445, ISBN13: 9781601982445, [publisher: Now Publishers Inc] Softcover nach der Bestellung gedruckt Neuware - Printed after ordering - Learning to Rank for Information Retrieval is an introduction to the field of learning to rank, a hot research topic in information retrieval and machine learning. It categorizes the state-of-the-art learning-to-rank algorithms into three approaches from a unified machine learning perspective, describes the loss functions and learning mechanisms in different approaches, reveals their relationships and differences, shows their empirical performances on real IR applications, and discusses their theoretical properties such as generalization ability. As a tutorial, Learning to Rank for Information Retrieval helps people find the answers to the following critical questions: To what respect are learning-to-rank algorithms similar and in which aspects do they differ What are the strengths and weaknesses of each algorithm Which learning-to-rank algorithm empirically performs the best Is ranking a new machine learning problem What are the unique theoretical issues for ranking as compared to classification and regression Learning to Rank for Information Retrieval is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners.
[Einbeck, Germany] [Publication Year: 2009] ...
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ISBN10: 1601982445, ISBN13: 9781601982445, [publisher: Now Publishers] Softcover pp. 122
[New York, NY, U.S.A.] [Publication Year: 2009]