GroupDocs.Classification
20.6.0
GroupDocs.Classification for .NET is an easy to use library that allows to perform sentiment analysis (classification), document classification and raw text classification.
Features:
* Classifies both raw text and documents with IAB-2, Documents or Sentiment taxonomies.
* Sentiment Classification (Analysis) supports English and Chinese and allows to determine the positivity.
* Returns the probability of each class.
Supported document formats:
* Microsoft Word documents - DOC, DOT, DOCX, DOCM, DOTX, DOTM, TXT, RTF;
* Open Document formats - ODP, ODS, ODT, OTT;
* Portable Document Formats - PDF;
For more details on the GroupDocs.Classification for .NET API, please visit GroupDocs website at:
https://www.groupdocs.com/products/classification/net
Note: GroupDocs.Classification for .NET will run in evaluation mode. Text or document content length should be less than 200 (100 for the sentiment analysis in English and 30 for Chinese). In order to test full features of the product, please request a free 30-day temporary license.
See the version list below for details.
Install-Package GroupDocs.Classification -Version 20.6.0
dotnet add package GroupDocs.Classification --version 20.6.0
<PackageReference Include="GroupDocs.Classification" Version="20.6.0" />
paket add GroupDocs.Classification --version 20.6.0
.NET API for Data Classification
A .NET component that enables your applications to analyze text and files as well as classify them based on IAB-2 and Documents taxonomies.
Classification Processing Features
- Support for IAB-2 and Documents taxonomies.
- Select the number of results to return.
- Select precision/recall balance for Documents taxonomy.
- Classify document from stream.
New Features & Enhancements in Version 20.6
- Sentiment Classification (Analysis) performance is doubled.
- Sentiment Classification (Analysis) probability model has been reworked and have became more accurate.
SentimentClassifier.PositiveProbabilitycan be used for a fine-grained sentiment analysis now.
For the detailed list, please visit GroupDocs.Classification for .NET 20.6 Release Notes.
Other File Formats
OpenOffice: ODT, OTT
Fixed Layout: PDF
Other: TXT
Supported Platforms
The machine that GroupDocs.Classification for .NET runs on doesn't need to have Adobe Acrobat, Microsoft Office or OpenOffice installed: GroupDocs.Classification for .NET has their own document processing engine.
Microsoft Windows: Microsoft Windows Desktop (x64) (XP & up), Microsoft Windows Server (x64) (2000 & up), Windows Azure
Mac OS: Mac OS X x64 (10.12+)
Linux: Linux x64 ( 6, 7 ,27, 9, 8.7+, 18.04, 16.04, 14.04, 18, 17, 42.3+, 12 SP2+)
Memory Requirements: 3GB RAM
Development Environments: Microsoft Visual Studio (2013, 2015, 2017, 2019)
Supported Frameworks: .NET Framework 4.7 or later, .NET Core 2.0 or later
Getting Started with GroupDocs.Classification for .NET
Are you ready to give GroupDocs.Classification for .NET a try? Simply execute Install-Package GroupDocs.Classification from Package Manager Console in Visual Studio to fetch & reference GroupDocs.Classification assembly in your project. If you already have GroupDocs.Classification for .Net and want to upgrade it, please execute Update-Package GroupDocs.Classification to get the latest version.
Please check the GitHub Repository for other common usage scenarios.
Classify PDF document by path with IAB-2 taxonomy via C# Code
var response = classifier.Classify("document.pdf", ".", 3, Taxonomy.Iab2);
Console.WriteLine(response.BestClassName, response.BestClassProbability);
Product Page | Docs | Demo | API Reference | Examples | Blog | Free Support | Temporary License
.NET API for Data Classification
A .NET component that enables your applications to analyze text and files as well as classify them based on IAB-2 and Documents taxonomies.
Classification Processing Features
- Support for IAB-2 and Documents taxonomies.
- Select the number of results to return.
- Select precision/recall balance for Documents taxonomy.
- Classify document from stream.
New Features & Enhancements in Version 20.6
- Sentiment Classification (Analysis) performance is doubled.
- Sentiment Classification (Analysis) probability model has been reworked and have became more accurate.
SentimentClassifier.PositiveProbabilitycan be used for a fine-grained sentiment analysis now.
For the detailed list, please visit GroupDocs.Classification for .NET 20.6 Release Notes.
Other File Formats
OpenOffice: ODT, OTT
Fixed Layout: PDF
Other: TXT
Supported Platforms
The machine that GroupDocs.Classification for .NET runs on doesn't need to have Adobe Acrobat, Microsoft Office or OpenOffice installed: GroupDocs.Classification for .NET has their own document processing engine.
Microsoft Windows: Microsoft Windows Desktop (x64) (XP & up), Microsoft Windows Server (x64) (2000 & up), Windows Azure
Mac OS: Mac OS X x64 (10.12+)
Linux: Linux x64 ( 6, 7 ,27, 9, 8.7+, 18.04, 16.04, 14.04, 18, 17, 42.3+, 12 SP2+)
Memory Requirements: 3GB RAM
Development Environments: Microsoft Visual Studio (2013, 2015, 2017, 2019)
Supported Frameworks: .NET Framework 4.7 or later, .NET Core 2.0 or later
Getting Started with GroupDocs.Classification for .NET
Are you ready to give GroupDocs.Classification for .NET a try? Simply execute Install-Package GroupDocs.Classification from Package Manager Console in Visual Studio to fetch & reference GroupDocs.Classification assembly in your project. If you already have GroupDocs.Classification for .Net and want to upgrade it, please execute Update-Package GroupDocs.Classification to get the latest version.
Please check the GitHub Repository for other common usage scenarios.
Classify PDF document by path with IAB-2 taxonomy via C# Code
var response = classifier.Classify("document.pdf", ".", 3, Taxonomy.Iab2);
Console.WriteLine(response.BestClassName, response.BestClassProbability);
Product Page | Docs | Demo | API Reference | Examples | Blog | Free Support | Temporary License
Release Notes
Dependencies
-
.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)
Used By
NuGet packages (2)
Showing the top 2 NuGet packages that depend on GroupDocs.Classification:
| Package | Downloads |
|---|---|
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GroupDocs.Total
GroupDocs.Total for .NET is a compilation of every .NET API offered by GroupDocs. We compile it on a daily basis to ensure that it contains the most up to date versions of each of our .NET document manipulation APIs.
With GroupDocs.Total for .NET developers can use all our APIs with a single license. However, you can order any individual API as well. The APIs we offer include:
GroupDocs.Viewer
GroupDocs.Annotation
GroupDocs.Conversion
GroupDocs.Comparison
GroupDocs.Signature
GroupDocs.Assembly
GroupDocs.Metadata
GroupDocs.Search
GroupDocs.Parser
GroupDocs.Watermark
GroupDocs.Editor
GroupDocs.Merger
GroupDocs.Redaction
GroupDocs.Classification
GroupDocs.Total for .NET Documentation
https://docs.groupdocs.com/display/gdtotalproductfamily/GroupDocs.Total+for+.NET
Free support for GroupDocs.Total for .NET is provided on our support forum:
https://forum.groupdocs.com/
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Conholdate.Total
Conholdate.Total for .NET is a complete package to work with a large number of file formats from Microsoft Word, Excel, PowerPoint, Outlook, Project, Visio, Adobe Acrobat, Illustrator, Photoshop, AutoCAD, OpenOffice and many more.
Conholdate.Total for .NET allows you to use any API released under Aspose and GroupDocs for .NET in order to create, convert, read, edit, update and print popular document formats. Moreover, you may view, annotate, watermark, assemble, classify, search, redact, parse, merge and compare documents without needing to install the native applications.
Conholdate.Total for .NET also includes specialized APIs to read and create barcodes, extract text from images using OCR as well as extract human marked data from questioners, surveys, quizzes, MCQ papers and feedback forms.
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GitHub repositories
This package is not used by any popular GitHub repositories.
