Natural Language Annotation for Machine Learning 在线电子书 图书标签: NLP 机器学习 O'Reilly 语言学 计算语言学 语料库语言学 ML 计算机科学
发表于2024-11-08
Natural Language Annotation for Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024
这本书的精华是附录A里面的语料库资源
评分传统语言学家进入现代计算语言学的必经之路,可能不是唯一,但之一是没有问题的。
评分上一次见这个封皮是干什么来着
评分精读了chapter1,2,3,7,如果目的不是text annotation, 这本书可能不是很适合。
评分传统语言学家进入现代计算语言学的必经之路,可能不是唯一,但之一是没有问题的。
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 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024