Hi Paul,
I cannot compare it to SemanticVectors as I don't know SemanticVectors.
But word vectors that are produced by word2vec have interesting properties.
Here is the description of the original word2vec web site:
https://code.google.com/p/word2vec/#Interesting_properties_of_the_word_vectors
Interesting properties of the word vectors
It was recently shown that the word vectors capture many linguistic regularities, for example
vector
operations vector('Paris') - vector('France') + vector('Italy') results in a vector that is
very
close to vector('Rome'), and vector('king') - vector('man') + vector('woman') is close to
vector('queen')
Thanks,
Koji
(2014/11/20 20:01), Paul Libbrecht wrote:
> Hello Koji,
>
> how would you compare that to SemanticVectors?
>
> paul
>
> On 20 nov. 2014, at 10:10, Koji Sekiguchi <koji@r.email.ne.jp> wrote:
>
>> Hello,
>>
>> It's my pleasure to share that I have an interesting tool "word2vec for Lucene"
>> available at https://github.com/kojisekig/word2vec-lucene .
>>
>> As you can imagine, you can use "word2vec for Lucene" to extract word vectors from
Lucene index.
>>
>> Thank you,
>>
>> Koji
>> --
>> http://soleami.com/blog/comparing-document-classification-functions-of-lucene-and-mahout.html
>
>
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