{"id":8244,"date":"2022-03-22T17:14:22","date_gmt":"2022-03-22T16:14:22","guid":{"rendered":"https:\/\/sourcing-force.com\/?p=8244"},"modified":"2023-05-05T23:09:37","modified_gmt":"2023-05-05T21:09:37","slug":"how-machine-learning-improves-data-cleansing","status":"publish","type":"post","link":"https:\/\/sourcing-force.com\/en\/how-machine-learning-improves-data-cleansing\/","title":{"rendered":"How Machine Learning Improves Data Cleansing"},"content":{"rendered":"

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Machine Learning Improves Data Cleansing<\/h2>\n

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One of the many Holy Grails of machine learning<\/strong> within the spend analysis domain is\u00a0the ability to disambiguate and classify customer purchases accurately, quickly, and automatically. It’s a fun problem to try to tackle since it’s approachable from many different angles.<\/span><\/em><\/p>\n


At a very simple level, one could iterate through all item purchases and try to categorize each purchase based on the name of the purchase and the name of the available categories to which you’re mapping. As an example, a “spoon” can be mapped to the following UNSPSC categories which all have the word “spoon” in them.
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