GroupDocs.Classification
21.1.0
dotnet add package GroupDocs.Classification --version 21.1.0
NuGet\Install-Package GroupDocs.Classification -Version 21.1.0
<PackageReference Include="GroupDocs.Classification" Version="21.1.0" />
paket add GroupDocs.Classification --version 21.1.0
#r "nuget: GroupDocs.Classification, 21.1.0"
// Install GroupDocs.Classification as a Cake Addin #addin nuget:?package=GroupDocs.Classification&version=21.1.0 // Install GroupDocs.Classification as a Cake Tool #tool nuget:?package=GroupDocs.Classification&version=21.1.0
Advanced .NET API for Document & Text Classification
GroupDocs.Classification for .NET is a powerful, intuitive API designed for developers seeking advanced text and document classification capabilities within their .NET applications. With support for multiple taxonomies, including IAB-2, Sentiment, and Document Taxonomy, this API enables precise content categorization, sentiment analysis, and structured document classification. It’s ideal for use cases like content management, targeted advertising, and customer feedback analysis. GroupDocs.Classification for .NET is cross-platform compatible, supporting Windows, macOS, and Linux, and seamlessly integrates into .NET projects without requiring third-party software like Microsoft Office or Adobe Acrobat®.
Raw Text Classification
Advanced Taxonomy Classification
Classify raw text with IAB-2, Documents, Sentiment, and Sentiment3.
Structure-Free Classification
Classify text without relying on document structure.
Document Classification
Multi-Format Document Classification
Classify DOC, PDF, OpenOffice, RTF, and TXT.
Flexible Document Format Support
Supports classification of multiple document formats.
Flexible Taxonomies
IAB-2 Taxonomy for News
Use IAB-2 for news and site classification.
Document Classes Taxonomy
Classify documents like invoices, CVs, forms, and emails.
Multi-Language Sentiment Taxonomy
Sentiment analysis in English, Chinese, Spanish, and German.
Multi-Language Support
Multi-Language Sentiment Analysis
Perform sentiment analysis in multiple languages.
Sentiment3 Multi-Language Classification
Supports multi-language sentiment classification.
Taxonomy Configuration
Custom Classification Parameters
Configure precision/recall balance and bestClassesCount.
Tailored Classification Process
Customize classification settings to meet specific needs.
Thread-Safe Operation
Concurrent Document Classification
Safely classify documents concurrently.
Multithreaded Processing Support
Enable efficient processing across multiple threads.
Cross-Platform Compatibility
Cross-Platform Support
Works on Windows, macOS, and Linux.
No Extra Software Needed
No Office or Acrobat required for classification.
Comprehensive SDK and Examples
.NET SDK with Demos
Fully-featured SDK with examples in C#.
Developer Integration Support
Examples to help developers integrate quickly.
High Accuracy Classification
Accurate Classification Algorithms
Uses advanced machine learning for accuracy.
Real-Time Classification
Supports instant classification for timely results.
Integration and Usability
.NET Language Integration
Easy to integrate with C#, VB.NET, J#.
User-Friendly API
Quick and effective implementation in applications.
IAB-2 Taxonomy Support
IAB-2 Digital Content Classification
Categorize content using IAB-2 standards.
Sentiment Analysis
Positive/Negative Sentiment Analysis
Classify text as positive, negative, or neutral.
Granular Sentiment3 Taxonomy
Supports detailed sentiment classification.
Documents Taxonomy
Predefined Document Categories
Classify documents like advertisements and emails.
Fallback "Other" Category
Handle unclassified or uncertain documents.
Custom Classification
Define Custom Categories
Create custom classification categories for specific needs.
Flexible Configuration
Supports tailored classification for business use.
Supported Document Formats
Format | Description |
---|---|
Adobe® Portable Document Format | |
DOC | Microsoft Word® 97-2003 Document |
DOCM | Microsoft Word® Macro-Enabled Document |
DOCX | Microsoft Word® Document |
DOT | Microsoft Word® 97-2003 Template |
DOTM | Microsoft Word® Macro-Enabled Template |
DOTX | Microsoft Word® Template |
ODT | OpenDocument Text |
OTT | Open Document Text Template |
RTF | Rich Text Document |
TXT | Plain Text Document |
Supported GroupDocs.Classification Taxonomies
IAB-2 Taxonomy
IAB-2 taxonomy categories are commonly used for content classification, especially in advertising and digital marketing. For more details, visit the IAB website.
- Automotive
- Books and Literature
- Business and Finance
- Careers
- Education
- Events and Attractions
- Family and Relationships
- Fine Art
- Food & Drink
- Healthy Living
- Hobbies & Interests
- Home & Garden
- Medical Health
- Movies
- Music and Audio
- News and Politics
- Personal Finance
- Pets
- Pop Culture
- Real Estate
- Religion & Spirituality
- Science
- Shopping
- Sports
- Style & Fashion
- Technology & Computing
- Television
- Travel
- Video Gaming
Documents Taxonomy
The Documents taxonomy is designed to classify various types of documents:
- ADVE - Advertisements, brochures
- Email - E-mails
- Form - Forms
- Letter - Letters
- Memo - Memorandums
- News - Articles, including news articles
- Invoice - Invoices
- Report - Reports
- Resume - CVs, resumes
- Scientific - Scientific papers
- Other - Other classes of documents or cases where the classifier is uncertain
Sentiment Taxonomy
The Sentiment taxonomy is used for classifying text based on sentiment:
- Negative
- Positive
Sentiment3 Taxonomy
The Sentiment3 taxonomy provides a more granular classification with three categories:
- Negative
- Neutral
- Positive
System Requirements
Category | Details |
---|---|
Operating Systems | - Windows: Windows 7 and above, including server versions. |
- macOS: macOS 10.12+. | |
- Linux: Various distributions including Ubuntu, CentOS, and more. | |
Memory Requirements | Minimum 3GB RAM |
Development Environments | Fully compatible with Microsoft Visual Studio 2013 and higher. |
Supported Frameworks | .NET Framework 4.7+, .NET Core 2.0+, and .NET Standard 2.0. |
Installation
NuGet Package Manager GUI
- Open Visual Studio and your project.
- Go to Tools > NuGet Package Manager > Manage NuGet Packages for Solution.
- Search for "GroupDocs.Classification".
- Click Install.
Package Manager Console
- Open the Package Manager Console.
- Run the command:
Install-Package GroupDocs.Classification
Manual Download
- Download from the GroupDocs website.
- Add a reference to
GroupDocs.Classification.dll
in your project.
Licensing
GroupDocs.Classification Cloud API is offered under a flexible licensing model. You can start with a free trial to evaluate the API, and when you are ready for production, various licensing options are available based on your project requirements. Please feel free to Contact Us for more detailed licensing information.
GroupDocs.Classification for .NET Code Samples
Basic Usage Examples
Classify a Document by Path
var classifier = new Classifier(); var response = classifier.Classify("document.pdf", ".", 3, Taxonomy.Iab2); Console.WriteLine(response.BestClassName, response.BestClassProbability);
Classify Raw Text
var response = classifier.Classify("Medicine is an important part of our lives"); Console.WriteLine(response.BestClassName, response.BestClassProbability);
Sentiment Analysis
var sentimentClassifier = new SentimentClassifier(); var positiveProbability = sentimentClassifier.PositiveProbability("This is a must-have item."); Console.WriteLine($"Positive sentiment probability: {positiveProbability}");
Tags
Document Classification API
| Text Extraction
| .NET Cloud API
| Metadata Management
| REST API
| SDK for .NET
| IAB-2 Taxonomy
| Sentiment Analysis
| Batch Processing
| Cloud API
| Metadata Parsing
| Text Parsing
| Document Taxonomy
| Custom Classification
| JWT Authentication
| Secure API
| Data Encryption
| Scalable API
| API Explorer
| Platform Agnostic
| Real-time Classification
| High Accuracy Classification
| Machine Learning
| Cross-Platform
| Multi-Platform Support
| Automatic Scaling
| Docker Support
| Self-hosting
| GitHub Repository
| API Integration
| Document Processing
| Content Management
| Targeted Advertising
| Customer Feedback
| Sentiment Taxonomy
| Text Processing
Product | Versions Compatible and additional computed target framework versions. |
---|---|
.NET | net5.0 was computed. net5.0-windows was computed. net6.0 was computed. net6.0-android was computed. net6.0-ios was computed. net6.0-maccatalyst was computed. net6.0-macos was computed. net6.0-tvos was computed. net6.0-windows was computed. net7.0 was computed. net7.0-android was computed. net7.0-ios was computed. net7.0-maccatalyst was computed. net7.0-macos was computed. net7.0-tvos was computed. net7.0-windows was computed. net8.0 was computed. net8.0-android was computed. net8.0-browser was computed. net8.0-ios was computed. net8.0-maccatalyst was computed. net8.0-macos was computed. net8.0-tvos was computed. net8.0-windows was computed. |
.NET Core | netcoreapp2.0 was computed. netcoreapp2.1 was computed. netcoreapp2.2 was computed. netcoreapp3.0 was computed. netcoreapp3.1 was computed. |
.NET Standard | netstandard2.0 is compatible. netstandard2.1 was computed. |
.NET Framework | net461 was computed. net462 was computed. net463 was computed. net47 was computed. net471 was computed. net472 was computed. net48 was computed. net481 was computed. |
MonoAndroid | monoandroid was computed. |
MonoMac | monomac was computed. |
MonoTouch | monotouch was computed. |
Tizen | tizen40 was computed. tizen60 was computed. |
Xamarin.iOS | xamarinios was computed. |
Xamarin.Mac | xamarinmac was computed. |
Xamarin.TVOS | xamarintvos was computed. |
Xamarin.WatchOS | xamarinwatchos was computed. |
-
.NETStandard 2.0
- Aspose.PDF (>= 19.9.0)
- Aspose.Words (>= 19.9.0)
- System.Drawing.Common (>= 4.6.0)
- System.Numerics.Vectors (>= 4.5.0)
- System.Reflection.Emit (>= 4.3.0)
- System.Reflection.Emit.ILGeneration (>= 4.3.0)
- System.Text.Encoding.CodePages (>= 4.6.0)
NuGet packages
This package is not used by any NuGet packages.
GitHub repositories
This package is not used by any popular GitHub repositories.