Jeff, I thought about this already. We have a REST API where you can send a word in and get the SDR back, and vice versa. I invite all who want to experiment to try it out. You just need to get credentials at our website: www.cept.at.
In mid-term it would be cool to create some sort of evaluation set, that could be used to measure progress while improving the CLA. We are continuously improving our Retina but the version that is currently online works pretty well already. I hope that will help Francisco On 24.08.2013, at 01:46, Jeff Hawkins wrote: > Francisco, > Your work is very cool. Do you think it would be possible to make available > your word SDRs (or a sufficient subset of them) for experimentation? I > imagine there would be interested in the NuPIC community in training a CLA > on text using your word SDRs. You might get some useful results more > quickly. You could do this under a research only license or something like > that. > Jeff > > -----Original Message----- > From: nupic [mailto:[email protected]] On Behalf Of Francisco > Webber > Sent: Wednesday, August 21, 2013 1:01 PM > To: NuPIC general mailing list. > Subject: Re: [nupic-dev] HTM in Natural Language Processing > > Hello, > I am one of the founders of CEPT Systems and lead researcher of our retina > algorithm. > > We have developed a method to represent words by a bitmap pattern capturing > most of its "lexical semantics". (A text sensor) Our word-SDRs fulfill all > the requirements for "good" HTM input data. > > - Words with similar meaning "look" similar > - If you drop random bits in the representation the semantics remain intact > - Only a small number (up to 5%) of bits are set in a word-SDR > - Every bit in the representation corresponds to a specific semantic feature > of the language used > - The Retina (sensory organ for a HTM) can be trained on any language > - The retina training process is fully unsupervised. > > We have found out that the word-SDR by itself (without using any HTM yet) > can improve many NLP problems that are only poorly solved using the > traditional statistic approaches. > We use the SDRs to: > - Create fingerprints of text documents which allows us to compare them for > semantic similarity using simple (euclidian) similarity measures > - We can automatically detect polysemy and disambiguate multiple meanings. > - We can characterize any text with context terms for automatic > search-engine query-expansion . > > We hope to successfully link-up our Retina to an HTM network to go beyond > lexical semantics into the field of "grammatical semantics". > This would hopefully lead to improved abstracting-, conversation-, question > answering- and translation- systems.. > > Our correct web address is www.cept.at (no kangaroos in Vienna ;-) > > I am interested in any form of cooperation to apply HTM technology to text. > > Francisco > > On 21.08.2013, at 20:16, Christian Cleber Masdeval Braz wrote: > >> >> Hello. >> >> As many of you here i am prety new in HTM technology. >> >> I am a researcher in Brazil and I am going to start my Phd program soon. > My field of interest is NLP and the extraction of knowledge from text. I am > thinking to use the ideas behind the Memory Prediction Framework to > investigate semantic information retrieval from the Web, and answer > questions in natural language. I intend to use the HTM implementation as > base to do this. >> >> I apreciate a lot if someone could answer some questions: >> >> - Are there some researches related to HTM and NLP? Could indicate them? >> >> - Is HTM proper to address this problem? Could it learn, without > supervision, the grammar of a language or just help in some aspects as Named > Entity Recognition? >> >> >> >> Regards, >> >> Christian >> >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org _______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
