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09_​Fuzzy_​String_​Matching

Fuzzy Matching of Strings

This workflow demonstrates how to apply a fuzzy matching of two string. The string matcher was designed exactly for this task, but is limited to the levenshtein distance.

With the support of distance matrices and the Similarity Search node, you have more option to compare strings. In the String Distance node, the distance can be chosen together with its parameters. Afterwards in the Similarity Search node you can find the closest match (e.g. the nearest neighbor) between the values from the first table to your lookup table in the second table. If provided, the node will use the distance from the distance matrix inport.

This workflow demonstrates how to apply a fuzzy matching of two string, using either the String Matcher (uses the Levenshtein distance) node or aSimilarity Search. searches for the three most similar stringalways uses the levenshtein distancecalculate distancesselect distance measure in this nodeSearch for all valuesof the first table for theclosest match in the second tableusing the distance in the third connectionduplicate the column String Matcher String Distances Similarity Search String Manipulation Generate some data This workflow demonstrates how to apply a fuzzy matching of two string, using either the String Matcher (uses the Levenshtein distance) node or aSimilarity Search. searches for the three most similar stringalways uses the levenshtein distancecalculate distancesselect distance measure in this nodeSearch for all valuesof the first table for theclosest match in the second tableusing the distance in the third connectionduplicate the column String Matcher String Distances Similarity Search String Manipulation Generate some data

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: iris.adae
Created at: 2016-06-22
On NodePit since: 2020-12-09
Last update: 2024-12-26
Created with KNIME version: v4.1.0
Tags: NLPNatural Language Processingsimilarity searchfuzzy matching

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