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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='font-size:12.0pt'>I am pleased to announce the latest title in Morgan & Claypool’s series on Human Language Technologies</span><span style='font-size:12.0pt'>:<o:p></o:p></span></p><p class=MsoNormal><b><span style='font-size:12.0pt'><o:p> </o:p></span></b></p><p class=MsoNormal><b><span style='font-size:12.0pt'>Learning to Rank for Information Retrieval and Natural Language Processing<o:p></o:p></span></b></p><p class=MsoNormal><b><span style='font-size:12.0pt'>Second Edition<span class=name> </span></span></b><span class=name><o:p></o:p></span></p><p class=MsoNormal><span class=name>Hang Li, <i>Huawei Technologies<o:p></o:p></i></span></p><p class=MsoNormal><span class=name>Paperback ISBN: </span>9781627055840, $40.00<br>eBook ISBN: 9781627055857<span class=name><i><br></i>October 2014, 121 pages</span><i><br></i><a href="http://dx.doi.org/10.2200/S00607ED2V01Y201410HLT026">http://dx.doi.org/10.2200/S00607ED2V01Y201410HLT026</a> <o:p></o:p></p><p class=summary-title style='margin:0in;margin-bottom:.0001pt'><b><span style='font-family:"Calibri","sans-serif"'><o:p> </o:p></span></b></p><p class=summary-title style='margin:0in;margin-bottom:.0001pt'><b><span style='font-family:"Calibri","sans-serif"'>Abstract:<o:p></o:p></span></b></p><p style='mso-margin-top-alt:5.0pt;margin-right:.25in;margin-bottom:5.0pt;margin-left:27.0pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:5.0pt;margin-right:.25in;margin-bottom:5.0pt;margin-left:27.0pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:5.0pt;margin-right:.25in;margin-bottom:5.0pt;margin-left:27.0pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:5.0pt;margin-right:.25in;margin-bottom:5.0pt;margin-left:27.0pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:5.0pt;margin-right:.25in;margin-bottom:5.0pt;margin-left:27.0pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:0in;margin-right:.25in;margin-bottom:0in;margin-left:27.0pt;margin-bottom:.0001pt;text-align:justify'><span style='font-family:"Calibri","sans-serif"'>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.<o:p></o:p></span></p><p style='mso-margin-top-alt:0in;margin-right:.25in;margin-bottom:0in;margin-left:27.0pt;margin-bottom:.0001pt;text-align:justify'><a href="http://www.morganclaypool.com/doi/abs/10.2200/S00607ED2V01Y201410HLT026"><span style='font-family:"Calibri","sans-serif"'>Read More</span></a><span style='font-family:"Calibri","sans-serif"'><o:p></o:p></span></p><div style='mso-element:para-border-div;border:none;border-bottom:solid windowtext 1.0pt;padding:0in 0in 0in 0in'><p class=MsoNormal style='border:none;padding:0in'><span style='font-size:12.0pt'><o:p> </o:p></span></p></div><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:12.0pt'>Series: Synthesis Series on Human Language Technologies<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:12.0pt'>Series Editor: Graeme Hirst, University of Toronto <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><a href="http://www.morganclaypool.com/toc/hlt/1/1">http://www.morganclaypool.com/toc/hlt/1/1</a><o:p></o:p></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'>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 <</span><a href="http://www.morganclaypool.com/page/licensed"><span style='font-size:12.0pt'>http://www.morganclaypool.com/page/licensed</span></a><span style='font-size:12.0pt'>> 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.<o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'>This book can also be purchased in print from Amazon and other booksellers worldwide.<o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:12.0pt'>Amazon URL: </span><a href="http://amzn.to/11gRSzL">http://amzn.to/11gRSzL</a> <o:p></o:p></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormalCxSpMiddle><a href="http://www.morganclaypool.com/page/subscribe"><span style='font-size:12.0pt'>Individual subscriptions</span></a><span style='font-size:12.0pt'> to Synthesis are available for just $99.00 per year. This subscription will provide individuals with unrestricted access to all Synthesis titles: </span><a href="http://www.morganclaypool.com/page/subscribe"><span style='font-size:12.0pt'>http://www.morganclaypool.com/page/subscribe</span></a><span style='font-size:12.0pt'> <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'>Available titles and subject areas: <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><a href="http://www.morganclaypool.com/page/browseLbS.jsp"><span style='font-size:12.0pt'>http://www.morganclaypool.com/page/browseLbS.jsp</span></a><span style='font-size:12.0pt'> <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'>Information for librarians, including pricing and license: <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><a href="http://www.morganclaypool.com/page/librarian_info"><span style='font-size:12.0pt'>http://www.morganclaypool.com/page/librarian_info</span></a><span style='font-size:12.0pt'> <o:p></o:p></span></p><p class=MsoNormalCxSpMiddle><span style='font-size:12.0pt'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:12.0pt'>Please contact </span><a href="mailto:info@morganclaypool.com"><span style='font-size:12.0pt'>info@morganclaypool.com</span></a><span style='font-size:12.0pt'> to request your desk copy</span><o:p></o:p></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:#888888'>-- <br>Shane Clyburn<br>Marketing Associate<br></span><span style='color:#1F497D'><a href="http://www.morganclaypool.com/"><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:blue'>Morgan & Claypool Publishers</span></a></span><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:#888888'><br>E-mail: </span><span style='color:#1F497D'><a href="mailto:shane@morganclaypool.com" target="_blank"><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:blue'>shane@morganclaypool.com</span></a></span><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:#888888'><br>Fax: 415.785.2507<o:p></o:p></span></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:#888888'><a href="https://twitter.com/MorganClaypool"><span style='color:blue'>Follow us on Twitter</span></a><o:p></o:p></span></p><p class=MsoNormal style='mso-margin-top-alt:auto;mso-margin-bottom-alt:auto'><span style='font-size:12.0pt;font-family:"Times New Roman","serif";color:#888888'><a href="http://www.facebook.com/pages/Morgan-Claypool-Publishers/232568823106"><span style='color:blue'>Like us on Facebook</span></a></span><span style='color:#1F497D'><o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p></div>
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