I'm developing a Neural training network with nntool in Matlab and I have as inputs 11250 text files with different lengths (from 10 to 500 words or let's say from 10 to 200 words if I eliminate redundant words ), I didn't find a good method to represent this input texts as a digital data to run my training algorithm. I thought about creating a vocabulary of words, but I've found that the vocabulary contains 16000 different words which is huge. There are some words in common between some text files.
Text representation for Neural training Network
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For quick sollution you should look for "bag of words" or "tfidf". If you don't know what is this, you should start here: https://en.wikipedia.org/wiki/Vector_space_model or https://en.wikipedia.org/wiki/Document_classification .
Have you read any book about NLP? Maybe this one may be valuable: http://www.nltk.org/book/ at the very begin.