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Text Analytics

Welcome to the Text Analytics Forum

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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. Support Thai language

    Please support Thai language I would like to try sentiment analytics on local website

    1 vote
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    0 comments  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  2. Fix your home page

    Put in 5000 characters (or a bit less) and see the 403 error (in console): https://azure.microsoft.com/en-gb/services/cognitive-services/text-analytics/#features

    1 vote
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    0 comments  ·  Documentation  ·  Flag idea as inappropriate…  ·  Admin →
  3. Offer a plain Javascript REST API Quick Start guide

    The existing Quick Start guide for Javascript has a dependency on Require which has a dependency on Node. Offer a plain Javascript guide using Javascript's built in fetch() method which has no dependencies. There is a working example (sans key) here: https://github.com/bofrank/text-analytics-js or the attached

    1 vote
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    0 comments  ·  API  ·  Flag idea as inappropriate…  ·  Admin →
  4. Improving accuracy in Named Entity Recognition

    Hi

    I currently work with a Fintech start-up and we run into a compliance requirements to remove personal names from a bunch of texts.

    We resorted to looking into Azure ML and yes, it appears promising by delivering a c. 80% accuracy in screening out individual names.

    Yet - it's not perfect. We have a database of hundreds of thousands of verified names and can contribute if needed.

    It would be grateful if we will be approached by a Microsoft person and we can share this database if see fit. trust the wealth of data we have would greatly improve…

    1 vote
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    0 comments  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  5. Add support for word classification

    I would like to have a single word classification or the entire sentence.

    Example Input: "I have mastered the advanced technique"

    Example Output:
    "I" -> noun
    "have" -> auxiliary verb, verb
    "mastered" -> verb
    "the" -> article
    "advanced" -> adjective
    "technique" -> noun

    1 vote
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    0 comments  ·  API  ·  Flag idea as inappropriate…  ·  Admin →
  6. Add Container Image for Named Entity Recognition (NER)

    There are container images for 3 services currently; one of them is key phrase extraction, but that is not nearly as powerful as NER. It would be great to have NER also come in a container for running on-prem without having to send the actual data to Azure.

    2 votes
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    0 comments  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  7. 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 →
  8. Wrong Results Some Times

    im using this for clients comments in a hotel, i notice that a some times is not so accured, a comment like "Tienen un excelente servicio" that in inglish is "you have an excelent service" just got a 0.17 = 17% of satisfaction, but when i use the same text in the public test API in this link https://azure.microsoft.com/es-es/services/cognitive-services/text-analytics/

    it get a 85% of satisfaction, im using this in a flow but it's suppose to be the same.

    1 vote
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    0 comments  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  9. 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?

    2 votes
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    1 comment  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  10. 1 vote
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    0 comments  ·  Key Phrase Extraction  ·  Flag idea as inappropriate…  ·  Admin →
  11. 1 vote
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    1 comment  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
  12. Why input is required strictly in JSON format?

    Any thoughts why this isn't simplified for the most common use cases? I have txt/docx/pdf/image file as input and all the complexities or converting to structured format should be abstracted away from user. Isn't this a very common use case that you have several unstructured or different types of files present in blob containers, let the API crawls through it and present its results. Similar to what Azure Search does? Also, why don't you unify these services, meaning the text analytics in Azure ML recognizes only 3 NER types, whereas Azure cognitive services recognizes more. Shouldn't this all be internally…

    2 votes
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    1 comment  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  13. Armenian incorrectly detected as English

    Armenian (not currently supported for detection) is being labeled as English with a confidence of 1.

    Examples:

    For input text: 'Տուն'
    The detected language is 'en'. Confidence is: 1.

    For input text: 'Անձնական Տվյալների Ցուցակ'
    The detected language is 'en'. Confidence is: 1.

    For input text: 'Ժողովրդագրություն'
    The detected language is 'en'. Confidence is: 1.

    For input text: 'Օժանդակ'
    The detected language is 'en'. Confidence is: 1.

    For input text: 'Կապի անհատներ'
    The detected language is 'en'. Confidence is: 1.

    For input text: 'Տվյալների Հաստատում'
    The detected language is 'en'. Confidence is: 1.

    Many many more examples. Meanwhile, other popular…

    1 vote
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    0 comments  ·  Language Detection  ·  Flag idea as inappropriate…  ·  Admin →
  14. Francisco Franco is not the spanish "jefe del estado" anymore

    If you enter "Clamor empresarial en presencia del jefe del Estado para poner fin cuanto antes a la violencia en Cataluña" in the test page, Text Analytics returns Francisco Franco!!! as "jefe del Estado".
    This guy died in 1975.

    1 vote
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    1 comment  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  15. Support Arabic Jordan Country Language

    Can you support Arabic language for Jordan country.

    2 votes
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    0 comments  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  16. Ability to call these API's from Analysis Services (SSAS)

    We use tabular model as our semantic layer and hence can't call these API's from Power BI. Is there a way we can call these API's from tabular model ? Our immediate need is for Key Phrases. It's really a pain to do this manually as we are importing the data into Power BI, which is not a scalable solution.

    1 vote
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    0 comments  ·  API  ·  Flag idea as inappropriate…  ·  Admin →
  17. 1 vote
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    1 comment  ·  Entity Recognition  ·  Flag idea as inappropriate…  ·  Admin →
  18. Issue on Decoding UTF-16

    Hello, I'm running your original tutorial sample on Azure Notebook, but here there is one error regarding UTF-16 decoding saying truncation happened.

    How to solve this?
    Thanks.

    1 vote
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    0 comments  ·  Documentation  ·  Flag idea as inappropriate…  ·  Admin →
  19. Support for Danish

    Please add support for Danish. We need to analyze text string to help the kids in special situations.

    1 vote
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    Completed  ·  1 comment  ·  Language Support  ·  Flag idea as inappropriate…  ·  Admin →
  20. The introduction 'not' completely confuses the sentiment analysis and is really unusable in real life.

    Example - "I didn't have a bad trip to Seattle. I enjoyed seeing the Space Needle!" returns 9% sentiment! Not really usable.

    1 vote
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    Resolved  ·  1 comment  ·  Sentiment Analysis  ·  Flag idea as inappropriate…  ·  Admin →
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