Webinar - A new tool to solve wicked text categorization problems  |  MeaningCloud
Webinar - A new tool to solve wicked text categorization problems 

The new Deep Categorization Customization Tool enables the development of the most accurate models in the most agile way

Wednesday, June 19, 9:00 AM PDT
Duration: 60 min.


Developing text categorization models should be very easy: categories are defined, examples are available in abundance to train the algorithms and machine learning technology is allowed to work its magic.

But reality is very different: there are frequent scenarios where categories are not defined or are evolving, where great precision is required to discriminate among them, where an adequate training corpus is not readily available  or where the context in general is very dynamic.

MeaningCloud’s new Deep Categorization Customization Tool uses a semantic rule language based on the meaning of the text itself and enables an agile categorization development process, in which an iterative and incremental refinement of the categories allows the maximum accuracy to be reached in dynamic environments.

The detailed linguistic analysis and understanding of a text's meaning  allow these systems to learn faster and perform better. Complementing machine learning-based approaches with this powerful semantic technology combines maximum development speed with a fast convergence towards the highest quality.

Register to this MeaningCloud webinar and discover these possibilities, with the aid of 
practical examples.

(Este webinar se ofrece también en español aquí.)

Wednesday, June 19, 9:00 AM PDT

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Agenda:

  • Developing categorization models in the real world
  • Categorization based on pure machine learning. Advantages and limitations
  • Introduction to the Deep Categorization API. Pre-defined models and vertical packs
  • The new Deep Categorization Customization Tool. Semantic rule language
  • Agile model development process. Combination with machine learning
  • Real case: development of a categorization model
  • API Comparison: Deep Categorization vs. Text Classification. When to use one or the other?

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