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NLP in practice: A Web App Demo for text summarization and Named-entity recognition

KI Demos

Once you have identified, extracted, and cleansed the content needed for your use case, the next step is to have an understanding of that content. In many use cases, the content with the most important information is written down in a natural language (such as English, German, Spanish, Chinese, etc.) and not conveniently tagged. To extract information from this content you will need to rely on some levels of text mining, text extraction, or possibly full-up natural language processing (NLP) techniques.

With this tool, you can easily summarize or extract enties of current news or your own texts using artificial intelligence. The underlying algorithms extract the essential and important information from a text or news article. This can save you a lot of time and you will still be well informed.

Enjoy summarizing! Your AISOMA Team.

App features:

  • Supported Languages: English | German
  • Macro Understanding: Text Summarization (News or own plain Text)
  • Comparison
  • Micro Understanding: Extracting entities (such as companies, people, dollar amounts, key initiatives, etc.)
  • Dynamically adjust the size of the summary (number of words)

Feedback is welcome (just click on the Feedback Link in the App)