Text Analysis & Comprehension

Integrate natural language processing (NLP) into your mobile and web applications to discover insight and relationships in text.

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Text Analysis & Comprehension

Benefits of using Text Analysis and Comprehension

Train models on your data

Train models on your data

To recognize various policy numbers or codes, Our text comprehension service specifies all to classify documents and comprehend in a simpler way to easily understand the message.

Get better answers from your text

Get better answers from your text

Our Text Analysis Service helps to discover the context and relationships from product reviews, customer support incidents, news articles, social media feeds, and more.

Organize documents by topics

Organize documents by topics

To analyze the collection of documents to organize in related terms and topics automatically, our comprehend service is the best option for providing reach navigation and personalized content.

Support for general and industry-specific text

Support for general and industry-specific text

Our comprehend service benefits to recognize insights from unstructured data powered by advanced Machine Learning that identifies medical text and the relationship between text.

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Use cases for Text Analysis & Comprehension

  • Voice of customer analysis:

    Our ML based comprehend service helps analyze customer interactions in the form of social media posts, online comments, emails, and more to find the elements for positive and negative experiences.
  • More accurate search:

    ML-based Accurate Search assists a better search experience that focuses on the intent and context of the search by allowing your search engine to index major phrases, sentiments, entities, and more.
  • Knowledge management and discovery:

    To categorize and organize all your documents for easy search with topic names, knowledge management, and discovery is the solution to personalize content recommendations for all your readers.
  • Classify support tickets for better issue handling

    Our custom classification support helps to categorize the inbound documents based on the content automatically. Following that, custom entities are used to extract relevant data to improve customer satisfaction.
  • Perform Medical Cohort Analysis

    Medical cohort analysis helps to better understand the medical information to structure, organize, and index the unstructured data. Majorly used to recognize recruit patients to suitable clinical elements in no time.

Key features of our Text Analysis & Comprehension Service using ML

  • Keyphrase Extraction:

    To support the key phrases of text, the keyphrase extraction API returns the talking points along with a confidence score.
  • Sentiment Analysis:

    To return the overall sentiment of the text, including positive, negative, neutral, and mixed, we integrate sentiment analysis API.
  • Syntax Analysis:

    To analyze text using Parts of Speech (PoS) and Tokenization, Amazon Comprehend Syntex API allows customers to identify labels within the text, and word boundaries.
  • Entity Recognition:

    Entities that are automatically categorized based on the provided text are returned based on their name, i.e., Places, People, and Locations through Entity Recognition API.
  • Comprehend Medical:

    Comprehend Medical helps to identify the relations between TTP (test, treatment, and procedures) and extracted subtypes connected with Medications.
  • Custom Entities:

    Custom entities authorize to customize the terms that are identified and domain-specific. With the help of AutoML, comprehend will learn from the private index and train for further terms recognition.
  • Language Detection:

    One that identifies medical data and links them to codes ICD-10-CM and concept in standard medical ontologies is Medical Ontology Linking API. It helps to detect contextual information as entity attributes.
  • Medical Ontology Linking:

    If your text is written in over 100 languages, our Language Detection API automatically recognizes that text and returns it to the dominant language with a strong score to support the dominant language.
  • Custom Classification:

    API that allows you to build classification models for the custom text without ML is Custom Classification API. No ML code is in need, you can do with SDK to integrate your custom classifier into your app.
  • Topic Modeling:

    To get relevant topics and terms from a collection of document storage, Topic Modeling identifies it and organizes it into a set to map them with the related document.
  • Multiple Language Support:

    Build your application with our Multiple Language Support assistance that helps to detect text in various languages and convert them to German, English, French, Italian, and more to perform text analysis further.