Cosine Similarity

by Adharsh Chandran J S

2

411

Cosine Similarity

by Adharsh Chandran J S

2

Custom Activity

411

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Summary

Summary


Overview

Overview

A commonly used approach to match similar documents is based on counting the maximum number of common words between the documents.
Still, this approach has an inherent flaw: as the size of the document increases, the number of common words tends to grow even if the documents cover different topics.
The cosine similarity helps overcome this fundamental flaw in the ‘count-the-common-words’ or Euclidean distance approach.
Input:
  • TestingDocumentText - string containing the text content to be tested
  • TrainingDocumentText - string containing the text content to be trained
Output:
  • CosineSimilarityValue - decimal value ranging between [0-1]

Features

Features


Additional Information

Additional Information

Dependencies


Code Language

Visual Basic

Runtime

Windows Legacy (.Net Framework 4.6.1)

Publisher

Adharsh Chandran J S

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License & Privacy

MIT

Privacy Terms

Technical

Version

1.0.1

Updated

21 Apr 2020

Works with

Developed in 2019.4.4

Certification

Silver Certified

Tags

data
file
processing
recognition
cosine similiarity
calculate cosine similiarity
cosine

Support

UiPath Community Support