@Carin between those two resources we should be able to come up with an adequate word "look up" mechanism eh?
On Fri, Oct 16, 2015 at 12:12 PM, cogmission (David Ray) < [email protected]> wrote: > Here's a resource: The Moby Part of Speech file!!! > > Linked on my server: www.mindlab.ai/mobypos.txt > > That's one resource! > > On Fri, Oct 16, 2015 at 12:05 PM, cogmission (David Ray) < > [email protected]> wrote: > >> Yep, precisely. Do it in the encoder! The encoder would take in a whole >> sentence and encode each word according to its "position" within a >> sentence, and its POS. For instance: The word "Where" would be encoded >> differently depending on the what its location in the sentence is... >> >> >> >> On Fri, Oct 16, 2015 at 11:50 AM, Matthew Taylor <[email protected]> >> wrote: >> >>> We don't have to use the fingerprints. Another way is to simply encode >>> the part of speech (POS) for each word. I'm sure that statements and >>> questions have different temporal POS patterns that should be recognizable. >>> >>> >>> --------- >>> Matt Taylor >>> OS Community Flag-Bearer >>> Numenta >>> >>> On Fri, Oct 16, 2015 at 9:10 AM, Richard Crowder <[email protected]> >>> wrote: >>> >>>> My 2 cent's - This sounds similar to DeepQA, that helped IBM Watson win >>>> Jeopardy? >>>> http://researcher.watson.ibm.com/researcher/view_group.php?id=2099 >>>> >>>> On Fri, Oct 16, 2015 at 4:39 PM, cogmission (David Ray) < >>>> [email protected]> wrote: >>>> >>>>> Awesome Idea! I for one am in! >>>>> >>>>> I think there are some questions that arise concerning capability and >>>>> approach? >>>>> >>>>> My main question is: >>>>> >>>>> Considering that training a Cortical.io Fingerprint will organize SDRs >>>>> according to subject applicability, I'm not sure whether it will >>>>> differentiate according to degree of interrogative-ness? I have the same >>>>> question as to the HTM; whether predictions and anomalies can >>>>> differentiate >>>>> according to degree of interrogative-ness... >>>>> >>>>> So my immediate suggestion for a solution to the above is to do it in >>>>> the "Encoder". That is, to spatially aggregate inputs (sentences) >>>>> according >>>>> to their Part-Of-Speach question word order... For example: >>>>> >>>>> 1. Sentences beginning with Is, Are, Why, How, Do, What, Where, >>>>> Whether etc. should be encoded closer to each other... >>>>> 2. Sentence fragments and clauses which accomplish the same as the >>>>> above, should have the same encoding nature. >>>>> >>>>> That's all I have for now... >>>>> >>>>> On Fri, Oct 16, 2015 at 10:23 AM, Matthew Taylor <[email protected]> >>>>> wrote: >>>>> >>>>>> Hello NuPIC, >>>>>> >>>>>> Here is a question for anyone interested in NLP, Cortical.IO's API, >>>>>> and phrase classification... >>>>>> >>>>>> This tweet from Carin Meier got me thinking last night: >>>>>> https://twitter.com/gigasquid/status/654802085335068672 >>>>>> >>>>>> Could we do this with text fingerprints from Cortical and HTM? What >>>>>> if we put together a collection of human-gathered "statements" and a list >>>>>> of "questions". For each phrase, we turned each word into an SDR via >>>>>> Cortical's API, and train one model on the statement phrases (resetting >>>>>> sequences between phrases) and one for questions. So we'll have one model >>>>>> that's only seen statements and one that's only seen phrases. >>>>>> >>>>>> If there are typical word patterns that exist mostly in one type of >>>>>> phrase or another, it may be possible to feed new phrases as SDRs into >>>>>> each >>>>>> model, and use the lowest anomaly to identify whether it is a statement >>>>>> or >>>>>> question? >>>>>> >>>>>> Does this seem feasible? Is anyone interested in this project? >>>>>> >>>>>> Thanks, >>>>>> >>>>>> --------- >>>>>> Matt Taylor >>>>>> OS Community Flag-Bearer >>>>>> Numenta >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> *With kind regards,* >>>>> >>>>> David Ray >>>>> Java Solutions Architect >>>>> >>>>> *Cortical.io <http://cortical.io/>* >>>>> Sponsor of: HTM.java <https://github.com/numenta/htm.java> >>>>> >>>>> [email protected] >>>>> http://cortical.io >>>>> >>>> >>>> >>> >> >> >> -- >> *With kind regards,* >> >> David Ray >> Java Solutions Architect >> >> *Cortical.io <http://cortical.io/>* >> Sponsor of: HTM.java <https://github.com/numenta/htm.java> >> >> [email protected] >> http://cortical.io >> > > > > -- > *With kind regards,* > > David Ray > Java Solutions Architect > > *Cortical.io <http://cortical.io/>* > Sponsor of: HTM.java <https://github.com/numenta/htm.java> > > [email protected] > http://cortical.io > -- *With kind regards,* David Ray Java Solutions Architect *Cortical.io <http://cortical.io/>* Sponsor of: HTM.java <https://github.com/numenta/htm.java> [email protected] http://cortical.io
