[Corpora-List] (New Book) Learning to Rank for Information Retrieval and Natural Language Processing, 2nd ed.

Tue Dec 30 16:57:17 UTC 2014

I am pleased to announce the latest title in Morgan & Claypool's series on
Human Language Technologies:

Learning to Rank for Information Retrieval and Natural Language Processing

Second Edition 

Hang Li, Huawei Technologies

Paperback ISBN: 9781627055840, $40.00
eBook ISBN: 9781627055857
October 2014, 121 pages
http://dx.doi.org/10.2200/S00607ED2V01Y201410HLT026 

Abstract:

Learning to rank refers to machine learning techniques for training a 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 its problems recently, and
significant progress has been made. This lecture gives an introduction to
the area including the fundamental problems, major approaches, theories,
applications, and future work.

The author begins by showing that various ranking problems in information
retrieval and natural language processing can be formalized as two basic
ranking tasks, namely ranking creation (or simply ranking) and ranking
aggregation. In ranking creation, given a request, one wants to generate a
ranking list of offerings based on the features derived from the request and
the offerings. In ranking aggregation, given a request, as well as a number
of ranking lists of offerings, one wants to generate a new ranking list of
the offerings.

Ranking creation (or ranking) is the major problem in learning to rank. It
is usually formalized as a supervised learning task. The author gives
detailed explanations on learning for ranking creation and ranking
aggregation, including training and testing, evaluation, feature creation,
and major approaches. Many methods have been proposed for ranking creation.
The methods can be categorized as the pointwise, pairwise, and listwise
approaches according to the loss functions they employ. They can also be
categorized according to the techniques they employ, such as the SVM based,
Boosting based, and Neural Network based approaches.

The author also introduces some popular learning to rank methods in details.
These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet,
ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda
Count, Markov Chain, and CRanking.

The author explains several example applications of learning to rank
including web search, collaborative filtering, definition search, keyphrase
extraction, query dependent summarization, and re-ranking in machine
translation.

A formulation of learning for ranking creation is given in the statistical
learning framework. Ongoing and future research directions for learning to
rank are also discussed.

 <http://www.morganclaypool.com/doi/abs/10.2200/S00607ED2V01Y201410HLT026>
Read More

Series: Synthesis Series on Human Language Technologies

Series Editor: Graeme Hirst, University of Toronto 

http://www.morganclaypool.com/toc/hlt/1/1

Use of this book as a course text is encouraged, and the texts may be
downloaded without restriction by members of institutions that have licensed
accessed to the Synthesis Digital Library of Engineering and Computer
Science or after a one-time fee of $20.00 each by members of non-licensed
schools. To find out whether your institution is licensed, visit <
<http://www.morganclaypool.com/page/licensed>
http://www.morganclaypool.com/page/licensed> or follow the links above and
attempt to download the PDF. Additional information about Synthesis can be
found through the following links or by contacting me directly.

This book can also be purchased in print from Amazon and other booksellers
worldwide.

Amazon URL: http://amzn.to/11gRSzL 

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Synthesis are available for just $99.00 per year. This subscription will
provide individuals with unrestricted access to all Synthesis titles:
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Available titles and subject areas: 

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Information for librarians, including pricing and license: 

 <http://www.morganclaypool.com/page/librarian_info>
http://www.morganclaypool.com/page/librarian_info 

Please contact  <mailto:info at morganclaypool.com> info at morganclaypool.com to
request your desk copy

-- 
Shane Clyburn
Marketing Associate
 <http://www.morganclaypool.com/> Morgan & Claypool Publishers
E-mail:  <mailto:shane at morganclaypool.com> shane at morganclaypool.com
Fax: 415.785.2507

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