Mastering Natural Language Processing with Python > PACKT 원서리스트

1: Working with Strings
Tokenization
Normalization
Substituting and correcting tokens
Applying Zipf's law to text
Similarity measures
Summary

2: Statistical Language Modeling
Understanding word frequency
Applying smoothing on the MLE model
Develop a back-off mechanism for MLE
Applying interpolation on data to get mix and match
Evaluate a language model through perplexity
Applying metropolis hastings in modeling languages
Applying Gibbs sampling in language processing
Summary

3: Morphology – Getting Our Feet Wet
Introducing morphology
Understanding stemmer
Understanding lemmatization
Developing a stemmer for non-English language
Morphological analyzer
Morphological generator
Search engine
Summary

4: Parts-of-Speech Tagging – Identifying Words
Introducing parts-of-speech tagging
Creating POS-tagged corpora
Selecting a machine learning algorithm
Statistical modeling involving the n-gram approach
Developing a chunker using pos-tagged corpora
Summary

5: Parsing – Analyzing Training Data
Introducing parsing
Treebank construction
Extracting Context Free Grammar (CFG) rules from Treebank
Creating a probabilistic Context Free Grammar from CFG
CYK chart parsing algorithm
Earley chart parsing algorithm
Summary

6: Semantic Analysis – Meaning Matters
Introducing semantic analysis
Generation of the synset id from Wordnet
Disambiguating senses using Wordnet
Summary

7: Sentiment Analysis – I Am Happy
Introducing sentiment analysis
Summary

8: Information Retrieval – Accessing Information
Introducing information retrieval
Vector space scoring and query operator interaction
Developing an IR system using latent semantic indexing
Text summarization
Question-answering system
Summary

9: Discourse Analysis – Knowing Is Believing
Introducing discourse analysis
Summary

10: Evaluation of NLP Systems – Analyzing Performance
The need for evaluation of NLP systems
Evaluation of IR system
Metrics for error identification
Metrics based on lexical matching
Metrics based on syntactic matching
Metrics using shallow semantic matching
Summary

Appendix A: Index