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Python自然語(yǔ)言處理(影印版)

Python自然語(yǔ)言處理(影印版)

定 價(jià):¥64.00

作 者: (英)伯德,(英)克萊因,(美)洛普 著
出版社: 東南大學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 程序設(shè)計(jì)

ISBN: 9787564122614 出版時(shí)間: 2010-06-01 包裝: 平裝
開(kāi)本: 16開(kāi) 頁(yè)數(shù): 479 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

  《Python自然語(yǔ)言處理(影印版)》提供了非常易學(xué)的自然語(yǔ)言處理入門介紹,該領(lǐng)域涵蓋從文本和電子郵件預(yù)測(cè)過(guò)濾,到自動(dòng)總結(jié)和翻譯等多種語(yǔ)言處理技術(shù)。在《Python自然語(yǔ)言處理(影印版)》中,你將學(xué)會(huì)編寫Python程序處理大量非結(jié)構(gòu)化文本。你還將通過(guò)使用綜合語(yǔ)言數(shù)據(jù)結(jié)構(gòu)訪問(wèn)含有豐富注釋的數(shù)據(jù)集,理解用于分析書面通信內(nèi)容和結(jié)構(gòu)的主要算法?!禤ython自然語(yǔ)言處理》準(zhǔn)備了充足的示例和練習(xí),可以幫助你:從非結(jié)構(gòu)化文本中抽取信息,甚至猜測(cè)主題或識(shí)別“命名實(shí)體”;分析文本語(yǔ)言結(jié)構(gòu),包括解析和語(yǔ)義分析;訪問(wèn)流行的語(yǔ)言學(xué)數(shù)據(jù)庫(kù),包括WordNet和樹(shù)庫(kù)(treebank);從多種語(yǔ)言學(xué)和人工智能領(lǐng)域中提取的整合技巧?!禤ython自然語(yǔ)言處理(影印版)》將幫助你學(xué)習(xí)運(yùn)用Python編程語(yǔ)言和自然語(yǔ)言工具包(NLTK)獲得實(shí)用的自然語(yǔ)言處理技能。如果對(duì)于開(kāi)發(fā)Web應(yīng)用、分析多語(yǔ)言新聞源或記錄瀕危語(yǔ)言感興趣——即便只是想從程序員視角觀察人類語(yǔ)言如何運(yùn)作,你將發(fā)現(xiàn)《Python自然語(yǔ)言處理》是一本令人著迷且極為有用的好書。

作者簡(jiǎn)介

  伯德(Steven Bird)是墨爾本大學(xué)計(jì)算機(jī)科學(xué)和軟件工程系副教授,以及賓夕法尼亞大學(xué)語(yǔ)言數(shù)據(jù)聯(lián)合會(huì)高級(jí)研究助理??巳R因(Ewan Klein)是愛(ài)丁堡大學(xué)信息學(xué)院語(yǔ)言技術(shù)教授。洛普(Edward Loper)最近從賓夕法尼亞大學(xué)獲得機(jī)器學(xué)習(xí)自然語(yǔ)言處理博士學(xué)位,目前是波士頓BBN Technologies公司的研究員。

圖書目錄

Preface
1.Language Processing and Python
1.1 Computing with Language: Texts and Words
1.2 A Closer Look at Python: Texts as Lists of Words
1.3 Computing with Language: Simple Statistics
1.4 Back to Python: Making Decisions and Taking Control
1.5 Automatic Natural Language Understanding
1.6 Summary
1.7 Further Reading
1.8 Exercises
2.Accessing Text Corpora and Lexical Resources
2.1 Accessing Text Corpora
2.2 Conditional Frequency Distributions
2.3 More Python: Reusing Code
2.4 Lexical Resources
2.5 WordNet
2.6 Summary
2.7 Further Reading
2.8 Exercises
3.Processing Raw Text
3.1 Accessing Text from the Web and from Disk
3.2 Strings: Text Processing at the Lowest Level
3.3 Text Processing with Unicode
3.4 Regular Expressions for Detecting Word Patterns
3.5 Useful Applications of Regular Expressions
3.6 Normalizing Text
3.7 Regular Expressions for Tokenizing Text
3.8 Segmentation
3.9 Formatting: From Lists to Strings
3.10 Summary
3.11 Further Reading
3.12 Exercises
4.Writing Structured Programs
4.1 Back to the Basics
4.2 Sequences
4.3 Questions of Style
4.4 Functions: The Foundation of Structured Programming
4.5 Doing More with Functions
4.6 Program Development
4.7 Algorithm Design
4.8 A Sample of Python Libraries
4.9 Summary
4.10 Further Reading
4.11 Exercises
5.Categorizing andTagging Words
5.1 Using a Tagger
5.2 Tagged Corpora
5.3 Mapping Words to Properties Using Python Dictionaries
5.4 Automatic Tagging
5.5 N-Gram Tagging
5.6 Transformation-Based Tagging
5.7 How to Determine the Category of a Word
5.8 Summary
5.9 Further Reading
5.10 Exercises
6.Learning to Classify Text
6.1 Supervised Classification
6.2 Further Examples of Supervised Classification
6.3 Evaluation
6.4 Decision Trees
6.5 Naive Bayes Classifiers
6.6 Maximum Entropy Classifiers
6.7 Modeling Linguistic Patterns
6.8 Summary
6.9 Further Reading
6.10 Exercises
7.Extracting Information from Text
7.1 Information Extraction
7.2 Chunking
7.3 Developing and Evaluating Chunkers
7.4 Recursion in Linguistic Structure
7.5 Named Entity Recognition
7.6 Relation Extraction
7.7 Summary
7.8 Further Reading
7.9 Exercises
8.Analyzing Sentence Structure
8.1 Some Grammatical Dilemmas
8.2 What's the Use of Syntax?
8.3 Context-Free Grammar
8.4 Parsing with Context-Free Grammar
8.5 Dependencies and Dependency Grammar
8.6 Grammar Development
8.7 Summary
8.8 Further Reading
8.9 Exercises
9.Building Feature-Based Grammars
9.1 Grammatical Features
9.2 Processing Feature Structures
9.3 Extending a Feature-Based Grammar
9.4 Summary
9.5 Further Reading
9.6 Exercises
10.Analyzing the Meaning of Sentences
10.1 Natural Language Understanding
10.2 Propositional Logic
10.3 First-Order Logic
10.4 The Semantics of English Sentences
10.5 Discourse Semantics
10.6 Summary
10.7 Further Reading
10.8 Exercises
11.Managing Linguistic Data
11.1 Corpus Structure: A Case Study
11.2 The Life Cycle of a Corpus
11.3 Acquiring Data
11.4 Working with XML
11.5 Working with Toolbox Data
11.6 Describing Language Resources Using OLAC Metadata
11.7 Summary
11.8 Further Reading
11.9 Exercises
Afterword: The Language Challenge
Bibliography
NLTK Index
General Index

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