What is Document understanding and what are the steps in DU? #interviewquestions
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Steps in Document Understanding
There are generally five main steps involved in the Document Understanding process in UiPath:
1. Digitization:
- Convert the document into a machine-readable format using OCR. This step involves using OCR engines to extract text and layout information from scanned images or PDFs.
2. Classification:
- Identify the type of document. This step involves determining what type of document you are processing (e.g., invoice, receipt, or purchase order). You can use machine learning models or rules-based approaches for classification.
3. Data Extraction:
- Extract specific data points from the document. This can be done using templates, machine learning models, or intelligent keyword-based extraction techniques to pull out relevant data like invoice numbers, dates, amounts, etc.
4. Validation:
- Review and validate the extracted data. Human-in-the-loop validation can be implemented to ensure that the extracted data is accurate. This step is crucial when dealing with high-stakes data.
5. Exporting:
- Export the extracted and validated data to the desired destination. This could be a database, an ERP system, an Excel file, or any other output format required by the business process.
These steps can be combined and configured based on the specific requirements of the document processing workflow in your automation project.
Видео What is Document understanding and what are the steps in DU? #interviewquestions канала Gravity Automation
Steps in Document Understanding
There are generally five main steps involved in the Document Understanding process in UiPath:
1. Digitization:
- Convert the document into a machine-readable format using OCR. This step involves using OCR engines to extract text and layout information from scanned images or PDFs.
2. Classification:
- Identify the type of document. This step involves determining what type of document you are processing (e.g., invoice, receipt, or purchase order). You can use machine learning models or rules-based approaches for classification.
3. Data Extraction:
- Extract specific data points from the document. This can be done using templates, machine learning models, or intelligent keyword-based extraction techniques to pull out relevant data like invoice numbers, dates, amounts, etc.
4. Validation:
- Review and validate the extracted data. Human-in-the-loop validation can be implemented to ensure that the extracted data is accurate. This step is crucial when dealing with high-stakes data.
5. Exporting:
- Export the extracted and validated data to the desired destination. This could be a database, an ERP system, an Excel file, or any other output format required by the business process.
These steps can be combined and configured based on the specific requirements of the document processing workflow in your automation project.
Видео What is Document understanding and what are the steps in DU? #interviewquestions канала Gravity Automation
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20 сентября 2024 г. 9:30:15
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