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Correcting Postal Addresses

Level: Medium

Description: You work as a data analyst for a delivery company, and some packages were not delivered last week due to address typos. Thanks to the postal carriers, addresses that were not found due to typos were marked as such. Given a dataset with successful deliveries (due to no typos) and unsuccessful ones (due to typos), your goal is to automatically fix the incorrect addresses by leveraging the correct ones.

Author: Aline Bessa

Dataset: Postal Data on KNIME Community Hub

Method 1 Method 2 Two methods are equivalent in output under specific input data and configuration conditions. usa_addresses.csvHas typosTop : YES (incorrect address)Bottom: NO (correct address)Maximal number of related words =1default : LevenshteinNeighor Count =1Levenshtein (normalized) Get unique row CSV Reader Row Splitter String Matcher Similarity Search Joiner GroupBy Method 1 Method 2 Two methods are equivalent in output under specific input data and configuration conditions. usa_addresses.csvHas typosTop : YES (incorrect address)Bottom: NO (correct address)Maximal number of related words =1default : LevenshteinNeighor Count =1Levenshtein (normalized) Get unique row CSV Reader Row Splitter String Matcher Similarity Search Joiner GroupBy

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