31–38 of 38 posts
Nice parser collection. But there a more powerful NLP libraries out there for JS: https://github.com/spencermountain/nlp_compromise
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dd/mm/yyyy and yyyy/mm/dd are as valid as each other, since it proceeds in either increasing or decreasing unit size. Having dates as mm/dd/yyyy makes about as much logical sense as writing: 10492 as 49210.
It doesn't make sense mathematically because it isn't a mathematical notation, it's linguistic in nature. In Europe, '4th May' is shortened to 4/5. In the US, 'May 4th' is shortened to 5/4. Neither is right, wrong or illogical. I'm from the UK, but have spent a lot of time working with US based clients/colleagues. They only way I've found to avoid confusion and ambiguity is to use YYYY/MM/DD.
knwl.english.adverbs = [ 'red', 'blue', 'green', 'orange', 'black', 'white', 'yellow', 'purple', 'really', 'sweet', 'sour', 'bitter', 'evil', ]; NLP. You keep using that word. I do not think it means what you think it means.
Nice library!
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NLP or adverbs? Both seemed to be applied incorrectly...
He means to say that Natural Language Processing isn't just scanning a text for patterns, like this library does, hence it's not a NLP library in the strict meaning of the term. It's an interesting project but it's really a parser, not a NLP.
This is not NLP. The code just finds words in list of pre-defined words. It ignores the context of the sentence or perform any "real" NLP analyzing.
http://www.quora.com/Why-are-rule-based-methods-becoming-unp...
Nice parser collection. But there a more powerful NLP libraries out there for JS: https://github.com/spencermountain/nlp_compromise
That module looks pretty useful. I've been resorting to node-natural [0] and then using a quick part of speech tagger so far, but this looks a lot better and doesn't have a heap of baggage. [0] https://github.com/NaturalNode/natural
knwl.english.adverbs = [ 'red', 'blue', 'green', 'orange', 'black', 'white', 'yellow', 'purple', 'really', 'sweet', 'sour', 'bitter', 'evil', ]; NLP. You keep using that word. I do not think it means what you think it means.