Natural Language Annotation for Machine Learning 在線電子書 圖書標籤: NLP 機器學習 O'Reilly 語言學 計算語言學 語料庫語言學 ML 計算機科學
發表於2024-12-23
Natural Language Annotation for Machine Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024
精讀瞭chapter1,2,3,7,如果目的不是text annotation, 這本書可能不是很適閤。
評分傳統語言學傢進入現代計算語言學的必經之路,可能不是唯一,但之一是沒有問題的。
評分乾貨不多。
評分傳統語言學傢進入現代計算語言學的必經之路,可能不是唯一,但之一是沒有問題的。
評分上一次見這個封皮是乾什麼來著
James Pustejovsky
James 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.
Amber Stubbs
Amber Stubbs is a Ph.D. candidate in Computer Science at Brandeis University in the Laboratory for Linguistics and Computation. Her dissertation is focused on creating an annotation methodology to aid in extracting high-level information from natural language files, particularly biomedical texts. Information about her publications and other projects can be found on her website: http://pages.cs.brandeis.edu/~astubbs/.
Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process.
Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You’ll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations.
This book is a perfect companion to O'Reilly’s Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
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Natural Language Annotation for Machine Learning 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024