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by Adharsh Chandran J S
2
Activity
420
Summary
Summary
Cosine similarity is a metric used to determine how similar the documents are irrespective of their size
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:
Output:
Features
Features
The cosine similarity is advantageous because even if the two similar documents are far apart by the Euclidean distance because of the size (like, the word ‘cricket’ appeared 50 times in one document and 10 times in another), they could still have a smaller angle between them. Smaller the angle, higher the similarity.
Additional Information
Additional Information
Dependencies
Centivus.EnglishStemmer.dll
Code Language
Visual Basic
Runtime
Windows Legacy (.Net Framework 4.6.1)
License & Privacy
MIT
Privacy Terms
Technical
Version
1.0.1Updated
April 21, 2020Works with
Studio: 19.4.4 - 22.10
Certification
Silver Certified
Support
UiPath Community Support