Text processing framework to analyse Natural Language by performing operations and tasks on corpus data. Hence, this approach focuses on the statistical/quantitative track of Natural Language Processing (NLP).
Website: http://nlptools.atrilla.net/
- Computational Linguistics (CL)
- Corpus Linguistics
- Information Retrieval
- Artificial Intelligence (AI), Machine Learning (ML) and Pattern Recognition
The differences among the aforementioned fields related to NLP are a matter of perspective and taste. Nonetheless, NLP is more frequently regarded to be an engineering-oriented approach while CL is rather more associated with theoretical aspects.
- Speech and Language Processing - An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, by Daniel Jurafsky and James H. Martin, 2009.
- Introduction to Information Retrieval, by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, 2008.
- Foundations of Statistical Natural Language Processing, by Christopher D. Manning and Hinrich Schütze, 1999.
- Artificial Intelligence: A Modern Approach, by Stuart Russell and Peter Norvig, 2010.
- Pattern recognition and machine learning, by Christopher M. Bishop,
- Pattern classification, by Richard O. Duda, Peter E. Hart and David G. Stork, 2001.
Coded in the PHP programming language for its suitability to process text on the web (i.e., Hypertext Preprocessor).
This README file provides a general description of the purpose of the NLP Toolkit.
For any comment or suggestion of any kind, please contact Alexandre Trilla.