{"product_id":"natural-language-annotation-for-machine-learning-a-guide-to-corpus-building-for-applications-9781449306663","title":"Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications","description":"\u003cp\u003eCreate your own natural language training corpus for machine learning. Whether you're working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle--the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don't need any programming or linguistics experience to get started.\u003c\/p\u003e\u003cp\u003eUsing detailed examples at every step, you'll learn how the \u003ci\u003eMATTER Annotation Development Process\u003c\/i\u003e helps you \u003cb\u003eM\u003c\/b\u003eodel, \u003cb\u003eA\u003c\/b\u003ennotate, \u003cb\u003eT\u003c\/b\u003erain, \u003cb\u003eT\u003c\/b\u003eest, \u003cb\u003eE\u003c\/b\u003evaluate, and \u003cb\u003eR\u003c\/b\u003eevise your training corpus. You also get a complete walkthrough of a real-world annotation project.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eDefine a clear annotation goal before collecting your dataset (corpus)\u003c\/li\u003e\n\u003cli\u003eLearn tools for analyzing the linguistic content of your corpus\u003c\/li\u003e\n\u003cli\u003eBuild a model and specification for your annotation project\u003c\/li\u003e\n\u003cli\u003eExamine the different annotation formats, from basic XML to the Linguistic Annotation Framework\u003c\/li\u003e\n\u003cli\u003eCreate a gold standard corpus that can be used to train and test ML algorithms\u003c\/li\u003e\n\u003cli\u003eSelect the ML algorithms that will process your annotated data\u003c\/li\u003e\n\u003cli\u003eEvaluate the test results and revise your annotation task\u003c\/li\u003e\n\u003cli\u003eLearn how to use lightweight software for annotating texts and adjudicating the annotations\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis book is a perfect companion to O'Reilly's \u003ci\u003eNatural Language Processing with Python\u003c\/i\u003e.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-276623\"\u003eJames Pustejovsky\u003c\/a\u003e, \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-6578096\"\u003eAmber Stubbs\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e O'Reilly Media\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 11\/20\/2012\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 342\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.21lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.01h x 7.07w x 0.73d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9781449306663\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 1449306667\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM062000\"\u003eData Science | Data Modeling \u0026amp; Design\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/correctionsbookstore.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM042000\"\u003eArtificial Intelligence | Natural Language Processing\u003c\/a\u003e\u003cbr\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eJames Pustejovsky teaches and does research in Artificial Intelligence and Computational Linguistics in the Computer Science Department at Brandeis University. His main areas of interest include: lexical meaning, computational semantics, temporal and spatial reasoning, and corpus linguistics. He is active in the development of standards for interoperability between language processing applications, and lead the creation of the recently adopted ISO standard for time annotation, ISO-TimeML. He is currently heading the development of a standard for annotating spatial information in language. More information on publications and research activities can be found at his webpage: pusto.com.\u003c\/p\u003e\u003cp\u003eAmber Stubbs recently completed her Ph.D. in Computer Science at Brandeis University, and is currently a Postdoctoral Associate at SUNY Albany. Her dissertation focused on creating an annotation methodology to aid in extracting high-level information from natural language files, particularly biomedical texts. Her website can be found at http: \/\/pages.cs.brandeis.edu\/ astubbs\/\u003c\/p\u003e","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":45876730921135,"sku":"9781449306663","price":56.65,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0651\/9255\/8767\/files\/img_baaaab4a-d217-48d2-9d33-5cbf6bb293c9.jpg?v=1757694706","url":"https:\/\/www.correctionsbookstore.com\/es\/products\/natural-language-annotation-for-machine-learning-a-guide-to-corpus-building-for-applications-9781449306663","provider":"Corrections Bookstore ","version":"1.0","type":"link"}