There's also Doc2vec :: http://deeplearning4j.org/doc2vec.html
Which could work as well. On Wed, Jun 29, 2016 at 8:43 PM, William Colen <william.co...@gmail.com> wrote: > Thank you, Boris. I am new to DeepLearning, so I have no idea the issues we > would face. I was wondering if we can use Features2Vec instead of Word2Vec, > does it make any sense? > The idea was to use DL in low level NLP tasks where we don't have parse > trees yet. > > > 2016-06-29 6:34 GMT-03:00 Boris Galitsky <bgalit...@hotmail.com>: > > > Hi guys > > > > I should mention how we used DeepLearning4J for the OpenNLP.Similarity > > project at > > > > https://github.com/bgalitsky/relevance-based-on-parse-trees > > > > > > The main question is how word2vec models and linguistic information such > > as part trees complement each other. In a word2vec approach any two words > > can be compared. The weakness here is that when learning is based on > > computing a distance between totally unrelated words like 'cat' and 'fly' > > can be meaningless, uninformative and can corrupt a learning model. > > > > > > In OpenNLP.Similarity component similarity is defined in terms of parse > > trees. When word2vec is applied on top of parse trees and not as a > > bag-of-words, we only compute the distance between the words with the > same > > semantic role, so the model becomes more accurate. > > > > > > There's a paper on the way which does the assessment of relevance > > improvent for > > > > > > word2vec (bag-of-words) [traditional] vs word2vec (parse-trees) > > > > > > Regards > > > > Boris > > > > [https://avatars3.githubusercontent.com/u/1051120?v=3&s=400]< > > https://github.com/bgalitsky/relevance-based-on-parse-trees> > > > > bgalitsky/relevance-based-on-parse-trees< > > https://github.com/bgalitsky/relevance-based-on-parse-trees> > > github.com > > Automatically exported from > > code.google.com/p/relevance-based-on-parse-trees > > > > > > > > > > ________________________________ > > From: Anthony Beylerian <anthony.beyler...@gmail.com> > > Sent: Wednesday, June 29, 2016 2:13:38 AM > > To: dev@opennlp.apache.org > > Subject: Re: DeepLearning4J as a ML for OpenNLP > > > > +1 would be willing to help out when possible > > >
