Approximate String Matcher – Powerful Fuzzy Matching in KNIME

Hi everyone,

We’ve recently published a new community node on the KNIME Community Hub:

Approximate String Matcher.

This node allows you to calculate string similarity scores between a reference table and a comparison table, with flexible matching algorithms and filtering options.

Key features:

• Choose from algorithms such as Levenshtein Edit Distance, Longest Common Subsequence, or Positional Matching.

• Apply a user-defined threshold to decide which rows are considered a match.

• Match logic: all columns in the comparison table and all rows in the reference table are combined in a logical OR fashion, and the best match is decisive.

• Flexible output: return matching rows, non-matching rows, or all rows.

• Optional extra columns:

Numeric match value

• Best reference match

• Alignment string showing modifications to align comparison with reference

Example workflow

We’ve created an overview example workflow that demonstrates how the node works and how to configure it:

🔗 Approximate String Matcher Overview Examples

Contact us

🌐 Website: https://www.exorbyte.com

📧 Email: consulting@exorbyte.com

💛 We’d love to hear your feedback, use cases, and ideas for improvement.

Feel free to try it out and let us know how it works in your workflows!

—

exorbyte Team