Thanks for the pointers everyone. Very useful. On Wed, Oct 21, 2015 at 1:19 PM, David Ray <[email protected]> wrote:
> Hi Carin, > > To add to what Alex said, allegories for each of the Python end points > exist for Java also. I'm on mobile right now because I'm getting Electrical > work done; so it would be difficult to prepare a list of links, but I can > as soon as I arrive at the coffee shop. > > You can get an example for the use of the Metrics Alex speaks of by > looking at the Breaking News demo; together with an example of using a > combination of the different end points. Additionally the fox eats demo > shows you how to get a fingerprint out of the cortical API put it into the > HTM and then get the results out of the HTM and do a reverse look up on the > cortical API to get a human-readable term back. > > One more point the cortical API is good for disambiguation of contexts and > it can also give you a similar list of terms used in multiple languages; > you also can differentiate contacts by subtracting context from a term for > instance: > Apple - Jaguar would give you a context which eliminates the animal > context and perhaps give you music or computers. > > Last but not least there's also an Android API > > Cheers, > David > > Sent from my iPhone > > On Oct 21, 2015, at 11:55 AM, Alex Lavin <[email protected]> wrote: > > Hi Carin, > I’ve run some experiments with the Cortical.io <http://cortical.io> > classify endpoint and have found it to be a useful tool. The Python client > allows you to query the endpoint [1] with positive examples that represent > the class, and negative examples that do not; it may be useful to use the > negative examples as those which may cause false positives. In return you > get a fingerprint (bitmap) representing the class. Now you can classify > text examples by first getting their fingerprints (via the term or text > endpoints [2, 3]), and then calculating the distance to the category > fingerprints; the API also offers an endpoint with many distance > calculations [4]. So once you’ve created multiple category fingerprints you > can classify text by determining which category is “closest”, as defined by > the distance metrics. > > [1] > https://github.com/cortical-io/python-client-sdk/blob/master/cortical/classifyApi.py > [2] > https://github.com/cortical-io/python-client-sdk/blob/master/cortical/termsApi.py > [3] > https://github.com/cortical-io/python-client-sdk/blob/master/cortical/textApi.py > [4] > https://github.com/cortical-io/python-client-sdk/blob/master/cortical/compareApi.py > > Cheers, > Alex > >
