I was looking to do some things using NLTK and found code.google.com/p/nltk-gae/ which looks promising, but the code on the site has quite a few errors (most of which I worked through) but has a LOT to be implemented (and relies on MemCache never being flushed to work)
Does anyone know of a better NLTK for GAE implementation? Or do we have an ETA on NLTK being supported on GAE?
-Brandon
Kind of sort of, not really.
Prediction doesn’t give you back any of the NLP, so you can’t say “What is this sentence about”, or what was user trying to search for.
But also it is SOOOO VERYYYYYY Expensive. Loading the training data for 10k users to build something like a content recommendation system and then loading all of the data to make recommendations from was going to be in the neighborhood of $20k before I got to the point that I could even evaluate if the system was going to work.
I have played with the prediction API for looking at traffic data to say “Hey you are always ‘UP’ in October” but that was hardly rocket science.
What I specifically need in this case is the ability to boil content down to the important bits.
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Wasn’t my number. That was the price quoted me by the Predictions team, given the data set were attempting to load.
And using NLTK in combination with a library I built I get very high accuracy on sentence context. Not Meaning, just subject matter.
My high confidence comes from this being one of the last places I go to ask questions. If I end up asking here it is usually because it is 3am and everyone else is sleeping. Or because I exhausted everything else and am hoping some crazy person here knows about some guy in Korea who did a port but the documentation is in a funny language.
I ended up writing my own Word and Sentence Tokenizer and am starting on a Stemmer. They are much faster than the NLKT version, but not having tested them with 10 billion words I always worry that I will have screwed something up.
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> Have you looked at using the 'real' NLTK on Python 2.7? As far as I can tell, the only hard dependency is NumPy, which we have.
It times out doing imports,
Nick, made a few comments on the issues, and I decided if he couldn’t get it to work I wasn’t going to try J
I may revisit as I start to hit the limits of what the stuff I built in a day can do.
> Have you looked at using the 'real' NLTK on Python 2.7? As far as I can tell, the only hard dependency is NumPy, which we have.
It times out doing imports,
Nick, made a few comments on the issues, and I decided if he couldn’t get it to work I wasn’t going to try J
I may revisit as I start to hit the limits of what the stuff I built in a day can do.
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I lurk here from time to time J
http://stackoverflow.com/questions/1286301/using-the-python-nltk-2-0b5-on-the-google-app-engine