Last October 5th we presented our webinar “Learn to develop custom text classifiers with MeaningCloud”. Thank you all for your attendance.
We began by presenting how to do text classification with MeaningCloud and why it is necessary to develop models that are adapted to each specific application scenario. The bulk of the presentation consisted in using a practical case (analysis of restaurant reviews) to show how these models can be developed using our product.
MeaningCloud offers tools that combine two technologies to create classification models:
- Machine learning technology allows to develop models quickly from a set of previously classified training texts.
- Rule-based technology creates a layer on top of the learning-based model that increases precision and recall.
This combination of technologies provides our users with the fastest development speed and greatest accuracy in the classification.
IMPORTANT: Data and models used in the webinar’s case study can be downloaded from a tutorial, whose first installment is this post. Stay tuned for the second part.
Interested? Here you have the presentation and the recording of the webinar.
(También presentamos este webinar en español. Tenéis la grabación aquí.)