Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundation...
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
目录
· · · · · ·
Introduction
Mathematical Foundations
Linguistic Essentials
Corpus-Based Work
Collocations
Statistical Inference: n-gram Models over Sparse Data
· · · · · ·
(更多)
Introduction
Mathematical Foundations
Linguistic Essentials
Corpus-Based Work
Collocations
Statistical Inference: n-gram Models over Sparse Data
Word Sense Disambiguation
Lexical Acquisition
Markov Models
Part-of-Speech Tagging
Probabilistic Context Free Grammars
Probabilistic Parsing
Statistical Alignment and Machine Translation
Clustering
Topics in Information Retrieval
Text Categorization
· · · · · · (收起)
We suspect that speech recognition people prefer to report the larger
non-logarithmic numbers given by perplexity mainly because it is much
easier to
impress funding bodies
by saying that “we’ve managed to reduce perplexity from 950 to only 540” than by saying that “we’ve reduced
cross entropy from 9.9 to 9.1 bits.” (查看原文)
This book published 20 years ago, but the content still new to me. Statistical NLP is the most interdisciplinary in my view, it involves Linguistics, Computer Science, Statistics, Information Theory, ...This book published 20 years ago, but the content still new to me. Statistical NLP is the most interdisciplinary in my view, it involves Linguistics, Computer Science, Statistics, Information Theory, even Philosophy and Neurosciences if you want to know more about NLP(展开)
苏格拉底大王
电子工业出版社2005版
realplayer-z
电子工业出版社2005版
0 有用 Victor 2023-10-02 22:21:14 美国
part of course material
0 有用 诸葛二牛 2011-08-30 19:51:36
国外经典教材，读得不多，略读过了。
0 有用 红茶渣 2012-01-15 00:09:17
入门书 涉猎面比SMT广 NLP都有涉及
0 有用 李白 2022-10-18 20:57:56 广东
上学的时候读过，全忘了
0 有用 王亮 2015-11-22 15:28:39
书写的挺好，就是比较过时了。。。
0 有用 Victor 2023-10-02 22:21:14 美国
part of course material
0 有用 李白 2022-10-18 20:57:56 广东
上学的时候读过，全忘了
0 有用 最上川 2020-02-28 12:39:43
看完了（心虚
0 有用 马文 2018-08-28 02:15:15
This book published 20 years ago, but the content still new to me. Statistical NLP is the most interdisciplinary in my view, it involves Linguistics, Computer Science, Statistics, Information Theory, ... This book published 20 years ago, but the content still new to me. Statistical NLP is the most interdisciplinary in my view, it involves Linguistics, Computer Science, Statistics, Information Theory, even Philosophy and Neurosciences if you want to know more about NLP (展开)
1 有用 Luke 2017-11-28 14:58:21
经典