GroupDocs.Classification for .NET is the go-to solution for developers looking to seamlessly integrate document classification and sentiment analysis capabilities into their .NET document processing apps. Our API offers easy-to-use features to efficiently categorize documents and text into distinct groups or categories for insightful analysis. It supports different document formats, including Microsoft Word, PDF, RTF, ODT, OTT, and text files. The .NET document classification API enables developers to categorize documents and raw text based on IAB-2, Documents, and Sentiment taxonomies.
With the API, end users can develop .NET solutions capable of classifying document text according to the type of content. Such solutions help automate categorizing large amounts of text or information into separate data sets. Similarly, our API can perform a thorough sentiment analysis of the given text, which helps understand the tone of the text. You can develop sentiment analysis applications using the .NET API for obtaining useful insights into the feedback shared by customers, analyzing performance, understanding user sentiment towards your products, and classifying text as positive, negative, or more. GroupDocs.Classification for .NET provides everything you need to intelligently categorize document text and build automated solutions targeting web or desktop interfaces.
Before you set up and get started with the .NET document classification and text analysis API, please visit the System Requirements page to check the recommended settings related to the operating systems, frameworks, and more. Please ensure compliance with these requirements to enjoy an issue-free user experience.
Please download the MSI installer or the DLLs from the downloads section to install the library. You can also use the NuGet package to set up the .NET document classification library. The command for the Visual Studio package manager console is shared below:
GroupDocs.Classification for .NET helps you easily classify documents and raw text into specific groups, categories, and sets. It provides methods for sorting document data based on predefined rules and filtering it for further processing. Developers can use a taxonomy of their choice for data categorization with our API and also analyze the tone of text (sentiment analysis). It is a handy analysis tool to understand the mood conveyed in the user-generated text. In this section, we will learn about the classification of document text using the IAB-2 taxonomy with the .NET document classification and text analysis API and try to understand the text's tone or sentiment.
The .NET API for text classification supports IAB-2 taxonomy to help you classify documents conveniently. The following C# code example explains more.
/* Classify documents (Word, PDF, RTF, ODT, TXT) with IAB-2 Taxonomy using C# */ Classifier classifier = new Classifier(); var filename = "document.pdf"; var response = classifier.Classify(filename, "" , 4, Taxonomy.Iab2); response.BestResults.ToList().ForEach(bestResult => Console.WriteLine($"Class: {bestResult.Name}, \t Probability: {bestResult.Probability}"));
Sentiment analysis plays an important role in understanding what the users are trying to convey as their feedback or general sentiment toward your services. Our API provides the methods that you can utilize for comprehensive sentiment analysis. Let's check the following coding example for more reference.
// Learn to analyze the positivity of text using a sentiment classifier in C#.
var sentiment = "Experience is simply the name we give our mistakes";
var sentimentClassifier = new SentimentClassifier();
/// PositiveProbability method returns the positive probability of the sentiment.
var positiveProbability = sentimentClassifier.PositiveProbability(sentiment);
Console.WriteLine($"Positive Probability of the sentiment { positiveProbability }");
Please visit the GitHub examples page of GroupDocs.Classification for .NET to check out more coding examples. You can use our Free Online Text and Document Classification Apps for classifying PDF, DOC, DOCX, RTF, TXT, and ODT documents and text on the fly using your mobile devices.
GroupDocs.Classification for .NET helps you simplify the document classification functionality without any dependency on additional software installations. You do not need to set up Microsoft Office or Adobe Acrobat to use our API. It can seamlessly integrate with your existing document management software, and there are no compatibility issues owing to the support for multiple frameworks. Additionally, the API supports Windows, Linux, and Mac operating systems to provide you with a cross-platform API usage experience. You can independently build robust solutions for managing text categorization using the .NET document classification and text analysis API.
GroupDocs.Classification for .NET is a powerful document classification API for text categorization and sentiment analysis. It enables developers to programmatically classify document text based on different taxonomies and review the tone of the provided text. Our API is loaded with features that help end users conveniently integrate text classification capabilities into various .NET document processing solutions.
The .NET API for document and text classification supports Microsoft Word (DOC, DOCX, DOCM, DOT, DOTM), RTF, PDF, OpenDocument (ODT, OTT), and TXT file formats.
Yes, we provide coding examples for the .NET API, which are available on the GitHub examples page of the API. With the help of code examples, developers can quickly learn to perform document classification and sentiment analysis within their .NET apps.
Of course! You can rest assured about the security of your files while processing them using our API. We ensure the privacy of your data and take all required measures to provide you with a secure user experience.
Absolutely! The .NET document classification library is compatible with multiple .NET frameworks and performs equally well on various operating systems. You do not need additional software installations for categorizing text using the library.
