Taxonomic Classification of Raw Text using C# - (IAB-2 & Document Taxonomy)
In an article, we discussed how we can [analyze and classify complete documents programmatically]. It is often required to classify just some part of the document or only a few statements. In this article, we will identify the best possible taxonomic categories of the selected text. We will learn how we can classify text according to IAB-2 and document taxonomies using C#.
Taxonomic Classification of Documents using C# - (IAB-2 & Document Taxonomy)
A classification is basically an approach in which text is systematically identified and then organized according to rules. Taxonomy defines the science of such classification. When you are dealing with a bunch of textual documents, it gets hard to find a topic of any document until the taxonomic classification of the content. In this article, you will learn how to programmatically classify documents according to IAB-2 and document taxonomy using C#.
Classify your Customer Feedback using Sentiment Analysis in C#
Suppose that you have the opportunity to receive comments or reviews from your customers or some other source and you want to evaluate how positive they are. There is a way to analyze such comments called sentiment analysis. This post focuses on the sentiment analysis tool based on a deep neural network model using C#. This model is suitable for a wide range of tasks.
Upcoming release of GroupDocs.Classification for .NET
GroupDocs.Classification for .NET allows you to classify document or text with IAB-2 or Document taxonomies. Have a look at the image below:
You can see how API classifies an input text to IAB-2. If you haven’t already explored the online app, visit it now.
We are going to launch GroupDocs.Classification API for .NET platform very soon. That means, whatever features you can avail/evaluate in the online app, will be available in a back-end API that you can integrate in any of your (existing or new) .