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  1. 1 vote
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      1 comment  ·  Flag idea as inappropriate…  ·  Admin →
    • Please develop some basic, written tutorials. Developers don't want to watch videos ... slow and i can't copy the code :)

      For each major enviromnent/language please develop a written (printable / pdf) that describes how to get started and to write your first application using ypour API. Then supplement this with other examples illustrating simple but 'real' problems being solved through the software/API. - Thanks

      1 vote
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        0 comments  ·  Flag idea as inappropriate…  ·  Admin →
      • error

        Using a curl command I am able to detect Vietnamese, Korean, Thai & Japansese with http://api.cortical.io/rest/text/detect_language, but can only get a fingerprint for English & Vientnamese other languages tested returned an error.

        "error_description":"It is not possible to create a meaningful semantic fingerprint from the input text. The most likely causes are, that the input text was empty, too small, was not provided in UTF-8 format, or contained fragments of symbols or other non-alphabetic characters.","suggested_resolution":"Please try to provide either a larger text fragment and/or remove non-alphabetic characters from the input text (leaving punctuation characters in)."

        Is Cortical able to create…

        1 vote
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          3 comments  ·  Flag idea as inappropriate…  ·  Admin →
        • using language other than english

          Except language detection, no api parameters indicates in which language we need to work.
          i saw only "en_associative or en-synonymous" .And It seems we have to contact sales to access a retina french database.
          So how can we try to validate interest ?
          ( i tried with default en_.. but got only non significant words le,la, les, de, des ... which demonstrate no use of language )
          is this product only trained for english ?

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            1 comment  ·  Flag idea as inappropriate…  ·  Admin →
          • keyword extraction from german text

            i am using the fullclient rest-api within python. i tried to extract keywords from german text. unfortunately the results are quite poor. major problem is that stop words like "der", "die", "das" and so on are primarily returned. these are probably the most common terms in an usual text but also the least relevant. is it possible to optimize the language specific operations, e.g. train the algorithm myself?

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              1 comment  ·  Flag idea as inappropriate…  ·  Admin →
            • Time series of texts (posts)

              Tutorial on time series of texts

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                1 comment  ·  Flag idea as inappropriate…  ·  Admin →
              • Scalable Comparison for Large Number of Documents

                I have a large number of documents, of 500 to 2000 words, that I would like link to each other based on semantic similarity. The number of documents will increase rapidly so a process of comparing each document with all other documents will not scale.

                As a solution I plan to retrieve a retina representation (Fingerprint) for each document from:
                /text?retina_name=en_associative

                Then find the 50 documents with the largest intersection of the values in the Fingerprint, then retrieve a representation of similarity with those 50 documents form:
                compare?retina_name=en_associative

                Is this the most efficient strategy ?

                2 votes
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                  7 comments  ·  Flag idea as inappropriate…  ·  Admin →
                • cURL support for compare?

                  I am trying to compare two texts using the curl API function, but I'm not certain how based on the example because it only says:

                  Request URL
                  http://api.cortical.io:80/rest/compare?retina_name=en_associative

                  but doesn't provide how we would input the two elements. I tried curl -X GET -H "api-key: xxxxx" "http://api.cortical.io:80/rest/compare?retina_name=en_associative&body=[{"term": "Pablo Picasso"},{"text": "Gustav Klimt was born in Baumgarten, near Vienna in Austria-Hungary, the second of seven children"}]"

                  but that did not work. Any help would be appreciated. Thanks.

                  3 votes
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                    1 comment  ·  Flag idea as inappropriate…  ·  Admin →
                  • Issues with Similarity Explorer

                    Human with Baby = 13% related but Shoes with Baby = 19% how exactly this is working i wanted to find out which is more related term to baby of course it's human not shoes.

                    1 vote
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                      4 comments  ·  Flag idea as inappropriate…  ·  Admin →
                    • Unexpected low similarity between a term and a text

                      I am using the compare api and ultimately I am trying to search for news articles that have to do with License agreements between companies. And in my first test I ran the following example but got a low 0.05 cosine similarity.

                      [
                      {
                      "term": "License Agreement"
                      },
                      {
                      "text": "Google and apple sign License Agreement to use a new search technology"
                      }
                      ]

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                        1 comment  ·  Flag idea as inappropriate…  ·  Admin →
                      • Training Domain Knowledge on top of Retinas for detecting similar phrases

                        If we could use use topic modeler to define phrases in terms existing terms in Retina. Eg. Grease my hands = Corruption or Crime sub government. And after creating the signature train the retina's with that so next time if I have a sentence like "I will pass the deal just make sure Mr X hands are greased." Is it possible to do it in Amazon Image?

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                          0 comments  ·  Flag idea as inappropriate…  ·  Admin →
                        • Unexpected response according to the context of a text!

                          With the interactive api I tried "/expressions/contexts" (http://api.cortical.io/Expression.htm#!/expressions/getContextsForExpression_post_1) with the following text input and I did not expect to get “cheese” as a result in the list.
                          {
                          "text": "I was drinking beer with my friends at the Oktoberfest"
                          }
                          Do you have any suggestion to improve the result here? Maybe it would be awesome just to get words describing the context which are actually used in the text?

                          2 votes
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                            2 comments  ·  Flag idea as inappropriate…  ·  Admin →
                          • Use of semantic fingerprints for a specific and isolated business domain?

                            Would it be possible to use the cortical.io Retina for a specific and isolated business domain that’s only accessible for one partner?

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                              0 comments  ·  Flag idea as inappropriate…  ·  Admin →

                              yes this would definitely be possible.
                              In the near future cortical.io’s technology will also be available as Amazon Machine Image via the Amazon Marketplace. Like this you would have your own cortical.io-Server instance.
                              Soon there will also be retinas in Spanish, French, German, Italian, Dutch, Swedish, Polish, Russian. You will be able to train specific domain language on top of the basic retinas.

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