User Tools

Site Tools


natural_language_processing

Natural Language Processing

Foundations

Common Knowledge

Pinyin

Word

Shallow Parsing

Deep Parsing

Information Extraction

Applications

Speech processing

Methods

Corpus

Evaluation

Tools

* Mallet * Natural Language Toolkit (NLTK) * Stanford CoreNLP : Fast and feature rich NLP library, written in JAVA. http://stanfordnlp.github.io/CoreNLP/ * Spacy : Another emerging NLP library in Python. Fast and state of the art. Tries to maintain an uniform API while implementing state of the art algorithms. https://spacy.io/ * Apache Tika : Offers an unified interface for extracting text data and meta data from many different file formats (PPT, PDF etc.) and analysis. https://tika.apache.org/

test processing

ngram

* google book ngrams Viewer: http://books.google.com/ngrams/

parser

All

* Clairlib: http://www.clairlib.org (Visual) The Clair library is a suite of open-source Perl modules intended to simplify a number of generic tasks in natural language processing (NLP), information retrieval (IR), and network analysis (NA). Its architecture also allows for external software to be plugged in with very little effort. * Whatswrong: http://code.google.com/p/whatswrong/ (Visual) A visualizer for Natural Language Processing problems * Tree Editor TrEd (Visual): http://ufal.mff.cuni.cz/~pajas/tred/ * markov thebeast: http://code.google.com/p/thebeast/ a Statistical Relational Learning software based on Markov Logic

Institutes

Books

  • Speech and Language Processing : Classic and Standard textbook in NLP. Pre publication draft of 3rd edition available here.
  • Natural Language Processing with Python : Application oriented book. Examples are in Python (NLTK). Free online version here.
  • Taming Text : Application oriented book. Examples are in JAVA.
  • Foundations of Statistical Natural Language Processing : Classic text on Statistical NLP. Goes deep into the implementation of parsers, taggers etc.
  • Handbook of Natural Language Processing : A complete treatment of NLP that starts from the historical roots and ends with the modern methods of NLP.
  • Statistical Machine Translation : Learn how to make a service like Google Translate
  • Introduction to Information Retrieval : Learn the nuts and bolts of services like Google Search and Google News (search, text classification, clustering etc.)
  • Prolog and Natural Language Analysis : Implement NLP algortihms in Prolog.

Courses

2017

2016

2007

resource

Dictionary

Benchmark

References

  • Manning C D. Computational Linguistics and Deep Learning. Computational Linguistics, 2015, 41(4): 701–707.
natural_language_processing.txt · Last modified: 2019/05/15 05:46 by x