统计自然语言处理基础

Name: 统计自然语言处理基础
ISBN: 0262133601

Foundations of Statistical Natural Language Processing

Christopher Manning、Hinrich Schütze · 初版 1999 年

15人推荐

16位读者提及

19次提及

为什么值得读

涵盖从分词到鲁棒句法分析等完整核心技术体系
讲解温和且透彻，适合建立扎实的语言建模基础
被学术界广泛视为统计NLP领域的标准案头参考书

Hacker News 上怎么说

prakash · 2009 年
《Introduction to Information Retrieval》（信息检索导论）：http://www.amazon.com/dp/0521865719/；《Convex Optimization》（凸优化）：http://www.amazon.com/dp/0521833787/；《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）：http://www.amazon.com/dp/0262133601/。读读 Peter Norvig 对《Foundations of ...》的书评：http://www.amazon.com/review/R3GSYXSKRU8V17/。这些书我都还没读过，不过都是被一些人吹爆的……
Introduction to Information Retrieval: http://www.amazon.com/dp/0521865719/ Convex Optimization: http://www.amazon.com/dp/0521833787/ Foundations of Statistical Natural Language Processing: http://www.amazon.com/dp/0262133601/ Read Peter Norvig's review for Foundations of ....http://www.amazon.com/review/R3GSYXSKRU8V17/ I haven't read any of these books, yet, highly recommended by some…
danieldk · 2010 年
强烈推荐这两本书：- Jurafsky 和 Martin 的《Speech and Language Processing》（语音与语言处理）；- Chris Manning 和 Hinrich Schütze 的《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）。它们合在一起构成了该领域极好的全景概览，从分词（tokenization）到鲁棒句法分析（robust parsing）应有尽有。具体的库我倒不好推荐某一个。过去两年里，我一直在……
These two books are really recommended: - Speech and Language Processing, Jurafsky and Martin - Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze Together they provide a very good overview of the field, from tokenization to robust parsing. I cannot really recommend one library. The last two years, I have been…
arnsholt · 2016 年
在 NLP 领域，除学位论文外，其实不太流行专题学术专著。不过大多数人都会参考那么两本工具书：* Manning 和 Schütze 的《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）；* Jurafsky 和 Martin 的《Speech and Language Processing》（语音与语言处理，目前正在修订第三版，可以在这里看：https://web.stanford.edu/~jurafsky/slp3/）。除此之外……
Monographs aren't really a thing in NLP, beyond theses. There are a couple of reference books most people lean on, though: * Foundations of Statistical Natural Language Processing by Manning and Schütze * Speech and Language Processing by Jurafsky and Martin (which is being revised for a third edition, which you can look at: https://web.stanford.edu/~jurafsky/slp3/ ) Beyond that,…
YeGoblynQueenne · 2023 年
……对于那些好奇语言模型是否有能力对文本以外的事物进行建模的人，有助于深入理解语言模型的工作原理。想要入门统计语言模型，一本很好的教材是 Manning 和 Schütze 写的《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）：https://nlp.stanford.edu/fsnlp/。或者同样优秀的、Jurafsky 和 Martin 写的《Speech and Language Processing》（语音与语言处理）：https://web.stanford.edu/~jurafsky/slp3/。或者如果你没有……
…understanding in how language modelling works, for those who are curious about questions regarding their ability to model something beyond text. A good textbook to begin with statistical language modelling is "Foundations of Statistical Natural Language Processing" by Manning and Schűtze: https://nlp.stanford.edu/fsnlp/ Or, just as good, "Speech and Language Processing" by Jurafsky and Martin: https://web.stanford.edu/~jurafsky/slp3/ Or, if you don't have the…
nathell · 2012 年
如果你还没读过并且对这类内容感兴趣，我强烈推荐 Manning 和 Schütze 的《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）。如果你想通俗易懂却又全面系统地入门统计 NLP，看这本“圣经”就对了。
If you haven't, and are interested in this kind of thing, I strongly recommend Manning and Schütze's "Foundations of Statistical Natural Language Processing". This is _the_ book if you want a gentle yet thorough introduction to statistical NLP.
xigency · 2015 年
……使用类似这种技术，否则我可能会花多得多的时间去研究自然语言处理。相反，我做了一个基于语言处理的搜索小项目，只读了《Foundations of Statistical Natural Language Processing》（统计自然语言处理基础）[1]（读起来不算太难），以及《Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition》（语音与语言处理导论）[2]（这本书啃起来挺费劲的……
…using techniques like this, otherwise I would probably spend much more time researching natural language processing. Instead, I did a simple project on searching using language processing and just read Foundations of Statistical Natural Language Processing [1], which is not too difficult, and Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition [2], which is a pretty heavy read…

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