Cosine Similarity
by Adharsh Chandran J S
2
411
Cosine Similarity
by Adharsh Chandran J S
2
Custom Activity
411
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)
License & Privacy
MIT
Privacy Terms
Technical
Version
1.0.1Updated
21 Apr 2020Works with
Developed in 2019.4.4
Certification
Silver Certified
Tags
data
file
processing
recognition
cosine similiarity
calculate cosine similiarity
cosine
Support
UiPath Community Support
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