Soenneker.Utils.String.CosineSimilarity 3.0.999

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dotnet add package Soenneker.Utils.String.CosineSimilarity --version 3.0.999
                    
NuGet\Install-Package Soenneker.Utils.String.CosineSimilarity -Version 3.0.999
                    
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<PackageReference Include="Soenneker.Utils.String.CosineSimilarity" Version="3.0.999" />
                    
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<PackageVersion Include="Soenneker.Utils.String.CosineSimilarity" Version="3.0.999" />
                    
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<PackageReference Include="Soenneker.Utils.String.CosineSimilarity" />
                    
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paket add Soenneker.Utils.String.CosineSimilarity --version 3.0.999
                    
#r "nuget: Soenneker.Utils.String.CosineSimilarity, 3.0.999"
                    
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#addin nuget:?package=Soenneker.Utils.String.CosineSimilarity&version=3.0.999
                    
Install Soenneker.Utils.String.CosineSimilarity as a Cake Addin
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Install Soenneker.Utils.String.CosineSimilarity as a Cake Tool

alternate text is missing from this package README image alternate text is missing from this package README image alternate text is missing from this package README image

alternate text is missing from this package README image Soenneker.Utils.String.CosineSimilarity

A utility library for comparing strings via Cosine Similarity

Installation

dotnet add package Soenneker.Utils.String.CosineSimularity

Why?

Imagine you have two sentences or documents. Cosine similarity helps you figure out how similar they are by looking at the -words- they share. Here's why it's handy:

Easy to Understand:

Cosine similarity is easy to understand. It's a number between 0 and 1 that represents how similar two documents are. The closer to 1, the more similar they are.

Not Bothered by Length:

Whether a text is long or short doesn't throw off cosine similarity. It cares more about the words and their relationships than the total number of words.

Meaning, Not Just Frequency:

It focuses on the meaning of words, not just how often they show up. So, even if one document has a lot more words than another, they might still be considered similar if they share important terms.

Efficient for Big Tasks:

When you're dealing with lots of documents or a ton of text, cosine similarity is efficient. It doesn't get bogged down by complicated calculations, making it a practical choice for large datasets.

Usage

var text1 = "This is a test";
var text2 = "This is another test";

double result = CosineSimilarityStringUtil.CalculateSimilarityPercentage(text1, text2); // 75
Product Compatible and additional computed target framework versions.
.NET net9.0 is compatible.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

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