About
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).
Related fields
- 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.
Recommended bibliography
NLP specific
- 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.
AI/ML specific
- Artificial Intelligence: A Modern Approach, by Stuart Russell and
Peter Norvig, 2010.
- Pattern recognition and machine learning, by Christopher M. Bishop,
2006.
- Pattern classification, by Richard O. Duda, Peter E. Hart and David
G. Stork, 2001.
Contact
For any comment or suggestion of any kind, please contact
Alexandre Trilla.