For those who don't want to use the API and for evaluation purposes, I would propose that we choose some reference text and I convert it into a sequence of SDRs. This file could be used for training. I would also generate a list of all words contained in the text, together with their SDRs to be used as conversion table. As a simple test measure we could feed a sequence of SDRs into a trained network and see if the HTM makes the right prediction about the following word(s). The last file to produce for a complete framework would be a list of lets say 100 word sequences with their correct continuation. The word sequences could be for example the beginnings of phrases with more than n words (n being the number of steps ahead that the CLA can predict ahead) This could be the beginning of a measuring set-up that allows to compare different CLA-implementation flavors.
Any suggestions for a text to choose? Francisco On 24.08.2013, at 17:12, Matthew Taylor wrote: > Very cool, Francisco. Here is where you can get cept API credentials: > https://cept.3scale.net/signup > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Fri, Aug 23, 2013 at 5:07 PM, Francisco Webber <[email protected]> wrote: > Just a short post scriptum: > > The public version of our API doesn't actually contain the generic conversion > function. But if people from the HTM community want to experiment just click > the "Request for Beta-Program" button and I will upgrade your accounts > manually. > > Francisco > > On 24.08.2013, at 01:59, Francisco Webber wrote: > > > 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 > > > _______________________________________________ > 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
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