Need resources for Statistical Natural Language Processing?

A commonly cited "introductory" reference is Foundations of Statistical Natural Language Processing (1999) by Manning & Shutze. While comprehensive, relatively accessible and certainly a excellent reference, this may be overkill for a more casual introduction to the field.

A commonly cited "introductory" reference is Foundations of Statistical Natural Language Processing (1999) by Manning & Shutze. While comprehensive, relatively accessible and certainly a excellent reference, this may be overkill for a more casual introduction to the field. You can maybe find some online courses such as Short course on Statistical Methods in NLP And also, since you mentioned java, you can find a generic "toolbox" such as Weka Stanford Core NLP openNLP GATE and start getting hands-on exposure to specific areas of NLP such as, say, POS Tagging or Entity Extraction.

Also worthy of mention, 'though it is related to a the Python-based NLTK, the Natural Language Processing with Python online (and hardcopy) book constitutes a very practical guide into common NLP tasks. There is a bit of a catch-22 with getting one's feet wet with NLP: it is a rather extensive field of study and practice. It is rife with both scholarly research and time and industry tested practices and libraries.

Until one has a better grasp of the particular applications of NLP that are suitable for a given problem, one may waste a lot time poking technologies that are either immature or not well suited to the problems at hand.

1 Perfect answer. I'd highly recommend starting with NLTK (Python is super easy) so you can dip into a bunch of tools without needing to write a ton of code. When you step into the big java libraries (basically all the big stuff is written in java) there is a much more significant level of knowledge required.

Also, as said, know your problem and that narrows down what nlp tools you use to solve it! – nflacco Aug 24 at 14:58 +1 for NLTK. It is the easiest way to start with NLP.

– Skarab Aug 26 at 6:07.

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