<NLP with python> notes: one

Preface

It is difficult to rely on clear rules to express natural language after generations of processing. Simple NLP: Compare different writing styles by comparing word frequency, complex NLP: Understanding human language and giving corresponding.

NLP applications: Handwritten character recognition, search engine, machine translation, etc.;

NLP in academia, also called computational linguistics;

The book Organization

Ch1-3:python Simple introduction of NLP treatment;

CH4: Structured to solidify the previous content, followed by subsequent labeling/sorting/information extraction;

CH5-7: Labeling/classification/information extraction;

CH8-10: Sentence parsing/recognition syntactic structure/structural semantic representation;

Ch11: How to effectively manage corpus data;

NLTK Common Modules

Corpus: Nltk.corpus;

Word, Root: Nltk.tokenize,nltk.stem

Fixed collocation: nltk.collocations

Callout: Nltk.tag

Category: Nltk.clasify,nltk.cluster

Chunk:nltk.chunk

Syntax parsing: nltk.parse

Evaluation: Nltk.metrics

Probability and Estimation: nltk.probablity

Application: Nltk.app,nltk.char

<NLP with python> notes: one