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Text Analytics

Welcome to the Text Analytics Forum

Categories

API – Any ideas or feedback pertaining to features or enhancements to Text Analytics API.

Documentation – Any ideas or suggestions for the API Reference or Documentation.

Language Support – Submit a request to have a particular language supported.

Samples & SDK Request – Let us know if you would like to see a Code sample or SDK provided.


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  1. 5 votes
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    0 comments  ·  Offline Support  ·  Flag idea as inappropriate…  ·  Admin →
  2. Russian language support for Text Analytics

    Will be very nice if russian will be supported by platform

    5 votes
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    1 comment  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  3. Publish a swagger / Open API specs

    Publish swagger / Open API JSON specs to allow developers to generate language specific client libraries.

    5 votes
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    2 comments  ·  Samples & SDK requests  ·  Flag idea as inappropriate…  ·  Admin →

    For Text Analytics:
    You can get to it from the API Reference Page. There is an “API Definition” button on the top right of the page. It will point you to

    westus.dev.cognitive.microsoft.com/docs/ser..

    Thanks!
    Luis Cabrera
    Text Analytics Program Manager

  4. Slovenian language support

    We have a lot of cases in Slovenia for Text Analytics.
    in the following order:
    Sentiment (1st), Key phrases(2nd), Entity Recognition(3rd).

    4 votes
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    Under Review  ·  1 comment  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  5. 4 votes
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    Under Review  ·  0 comments  ·  Service Limits  ·  Flag idea as inappropriate…  ·  Admin →
  6. Support larger, "one time" documents for topic analysis

    Instead of posting 100 x paragraph sized strings (documents) for topic analysis, I want to post a potentially large document (essay, thesis) and receive a ranked list of topics (by confidence) covered within.

    4 votes
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    0 comments  ·  Topic Detection  ·  Flag idea as inappropriate…  ·  Admin →
  7. Key phrase for Office document on Text Analytics API

    I want to use the Key phrase in our Office document for analyzing.
    Exce, PowerPoint, Word, OneNote.

    Analyze scenario:
    Which key phrase used in each departments.
    Which key phrase used in each projects.
    Which key phrase used in well referencing documents.

    4 votes
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    Under Review  ·  0 comments  ·  Key Phrase Extraction  ·  Flag idea as inappropriate…  ·  Admin →
  8. Text Analytics topic by string

    I want to be able to send the API a string of multiple words or a single word, and get detailed topics about that string. If I send the words, Grass, Mountain, Hiking Trail, Hawk, Mushroom, Beach, I would like to know these are related to the Outdoors, and Animals, etc. Basically a very simple Wolfram Alpha or Open Calais API.

    4 votes
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    Under Review  ·  0 comments  ·  Topic Detection  ·  Flag idea as inappropriate…  ·  Admin →
  9. Can we extend text analytics API for general text classification, instead of just sentiment analysis?

    Can we extend text analytics API for general text classification, instead of just sentiment analysis?
    e.g. From customer chat information can we predict if the incoming request is an escalation of general inquiry
    OR
    news category classification - business news/ sports news/ politics etc.

    Thanks,
    Azured

    3 votes
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    0 comments  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  10. How we can calculate sentiment for large documens? (more than 5120 characters)

    We are trying to analyze a large document (more than 5120 characters). We don't know how to calculate the overall sentiment score of the entire document.
    Let imagine we have a document with 5200 characters. So we can split it into two chunks( first with 5120 characters and the second is 80 characters) and the overall score calculates as an average of two documents. But this approach is not right because the second smaller document with 80 characters can dramatically affect the result.
    What are your suggestions?
    How we should split and calculate the overall score?

    3 votes
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    1 comment  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  11. Does the key phrase functionality allow words to be singularised from a plural or changed from past tense to present tense in an automated

    Currently, when using the key phrase extraction to count where IT issues are logged, phrases like "Service" and "Services", "Project" and "Projects", "Business" and "Businesses", etc all show up as separate phrases. However, we would like these plural phrases to be listed and counted as singular phrases so the single & plural instances of the phrase are all grouped & counted together. Is this something that would be possible?
    (similarly, being able to recognise and group togethre a past tense word into the present tense - i.e. "Pay" & "Paid" - would be a useful feature.

    3 votes
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    0 comments  ·  Key Phrase Extraction  ·  Flag idea as inappropriate…  ·  Admin →
  12. Identify location and travel types and subtypes for Named Entity Recognition

    Locality "here" Map coordinates if have access to location
    Locality "nearby" within 0.5 miles
    District "London" - Geofence for London
    Affiliated address"Mum's house"
    PlaceOfWork" - your workplace
    Address "Barclay's Head Office"
    Bus stop
    Motorway Junction "M25 J4"
    Road Vector "A256"
    Road Junction "corner of 6th and 12th street"
    Bridge "London Bridge"
    Station "London Victoria" (Coach/Bus)

    3 votes
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    Under Review  ·  0 comments  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  13. Hints for key phrases to improve extraction on small texts

    As mentioned in the guides, Key phrase extraction works best when you give it bigger chunks of text to work on. This means that the same text results in different sets of key phrases when it is part of a larger dataset and when it is submitted as a single record.

    It would be helpful, if we have the option of also including a set of key phrases (or as mentioned in other idea submissions - custom keywords or vocabulary) so that the results are better and consistent even when the API is dealing with small chunks of text.

    3 votes
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    Under Review  ·  0 comments  ·  Key Phrase Extraction  ·  Flag idea as inappropriate…  ·  Admin →
  14. Poor sentiment score for positive statement

    “It was great and he did help me.”
    Cognitive gives 18% which to me looks incorrect.

    3 votes
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    Started  ·  2 comments  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  15. Service Accuracy

    It would be nice to have a page in the documentation that describe the API performance and accuracy.

    3 votes
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    Under Review  ·  0 comments  ·  Documentation  ·  Flag idea as inappropriate…  ·  Admin →
  16. Support Portuguese language for key-phrases

    Please support Portuguese language for key-phrase extraction

    3 votes
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    1 comment  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  17. Arabic sentiments still need some work

    Arabic sentiment analysis still provides a 50% score on most sentiments. I was hoping to sell the idea to a local university, but Arabic will be a major part of the story.

    3 votes
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    Under Review  ·  0 comments  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  18. sentiment analysis - Hindi Language

    Hope to see some support for Sentiment Analysis in Hindi language

    3 votes
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    Under Review  ·  0 comments  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  19. 我希望可以提供中文

    I want write procedure code Taiwan chinese
    can you help me? give me Reference direction?

    3 votes
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    Under Review  ·  0 comments  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  20. We need more details on the score from Sentiment analysis

    The sentiment analysis score is descibed as "returns a numeric score between 0 and 1. Scores close to 1 indicate positive sentiment and scores close to 0 indicate negative sentiment. Sentiment score is generated using classification techniques. The input features of the classifier include n-grams, features generated from part-of-speech tags, and word embeddings."

    We need more information about the scoring. The text "I'm sorry, but you could do so much better." returns 0.58 but it is very negative. What can we do to ensure that we can trust the results? Would it be useful to use longer pieces of text?

    3 votes
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    Started  ·  4 comments  ·  Documentation  ·  Flag idea as inappropriate…  ·  Admin →
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