1) The upshot seems to be that it's a defensive patent, and in any case the
code was released under Apache 2.0, so it's fine to use.
https://code.google.com/p/word2vec/
https://groups.google.com/forum/#!topic/word2vec-toolkit/1hID9F74_Ho
2) The gensim implementation predates the patenting
(thanks for that reference, Mathieu...interesting!)
FM.
On 1 July 2015 at 06:52, Mathieu Blondel <math...@mblondel.org> wrote:
>
>
> On Wed, Jul 1, 2015 at 8:43 PM, Dale Smith <dsm...@nexidia.com> wrote:
>
>> Apparently so; here is a python/cython implementation.
>>
>>
>>
>> http://rare-technologies.com/deep-learning-with-word2vec-and-gensim/
>>
>
> word2vec is *not* deep learning. The skip-gram model has been shown
> recently to reduce to a certain matrix factorization [*]. So it's a shallow
> network with only one hidden layer and without non-linearities.
>
> Mathieu
>
> [*] Neural Word Embedding as Implicit Matrix Factorization by O. Levy and
> Y. Goldberg.
>
>
>
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