version 1.0.0 (Compatible with OutSystems 11)

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on 16 Apr

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Compare Fuzzy Text using Levenshtein Distance algorithm.

Use this component to compare two strings using Levenshtein Distance algorithm. this component calculate and find the distance between two string and shows how many characters required to match these two strings.

Threshold for Considering Strings as Same:

In practice, the threshold for considering two strings as the "same" depends on the context:

1. Exact Match:
.100% similarity score.
.Use this when exact matches are required (e.g., password checks).

2. High Similarity (90% - 100%):
.Typically considered the same with minor typos or variations.
.Good for name matching, plagiarism detection, or spell checkers.

3. Moderate Similarity (70% - 90%):
.Considered similar, but not necessarily the same.
.Useful for fuzzy searches or autocorrect suggestions.

4. Low Similarity (< 70%):
.Generally considered different.
.Significant differences in spelling or structure.

Commonly Used Thresholds:

= 90%: Considered as the same or almost identical.

70% - 90%: Considered as similar, but may need manual verification.

< 70%: Considered different.

Example Use Cases:

Spell Checkers / Autocorrect: = 85% to suggest corrections.

Search Engines: = 70% to show relevant results.

Plagiarism Detection: = 90% to flag as potentially copied content.

Name Matching (e.g., customer databases): = 85% to account for typos.

Release notes (1.0.0)

License (1.0.0)

BSD-3 license (https://opensource.org/licenses/BSD-3-Clause)

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