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CI_​IA_​AP-Duplicate_​Invoice_​Detection

The purpose of this flow is to identify duplicate invoices.
We prepare a set of invoices labelled as duplicates or non-duplicates.
We have calculated the absolute value of the difference between:
- The amounts of two invoices,
- The dates of two invoices,
- The Levenshtein distance between the invoice numbers,
- The distance between the two BERT vectors of the descriptions.
Next, we create a model trained on this dataset based on the neural network.

Data Preprocessing Training Model evaluation and export Data Preprocessing Deploying Reporting Deploying Training extract prediction Excel Reader Excel Reader Keras NetworkLearner Keras NetworkExecutor Scorer Rule Engine Partitioning Keras NetworkWriter DataPreparation Keras NetworkReader Keras NetworkExecutor Data Preparation Excel Writer Column Filter Networkarchitecture Data Preprocessing Training Model evaluation and export Data Preprocessing Deploying Reporting Deploying Training extract prediction Excel Reader Excel Reader Keras NetworkLearner Keras NetworkExecutor Scorer Rule Engine Partitioning Keras NetworkWriter DataPreparation Keras NetworkReader Keras NetworkExecutor Data Preparation Excel Writer Column Filter Networkarchitecture

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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: YMAM
Created at: 2023-07-22
On NodePit since: 2023-08-27
Last update: 2026-01-07
Created with KNIME version: v4.7.2
Tags: internal controlduplicate invoiceduplicate detectionLevenshteinpurchases

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