Natural Language Processing with Python

Further Reading

Extra materials for this chapter are posted at http://www.nltk.org/, including links to freely available resources on the Web. Remember to consult the Python reference materials at http://docs.python.org/. (For example, this documentation covers “universal newline support,” explaining how to work with the different newline conventions used by various operating systems.)

For more examples of processing words with NLTK, see the tokenization, stemming, and corpus HOWTOs at http://www.nltk.org/howto. Chapters 2 and 3 of (Jurafsky & Martin, 2008) contain more advanced material on regular expressions and morphology. For more extensive discussion of text processing with Python, see (Mertz, 2003). For information about normalizing non-standard words, see (Sproat et al., 2001).

There are many references for regular expressions, both practical and theoretical. For an introductory tutorial to using regular expressions in Python, see Kuchling’s Regular Expression HOWTO, http://www.amk.ca/python/howto/regex/. For a comprehensive and detailed manual in using regular expressions, covering their syntax in most major programming languages, including Python, see (Friedl, 2002). Other presentations include Section 2.1 of (Jurafsky & Martin, 2008), and Chapter 3 of (Mertz, 2003).

There are many online resources for Unicode. Useful discussions of Python’s facilities for handling Unicode are:

• PEP-100 http://www.python.org/dev/peps/pep-0100/

• Jason Orendorff, Unicode for Programmers, http://www.jorendorff.com/articles/unicode/ ...