Creating Effective Training Datasets for Machine Learning
Zoning Documents for Data Extraction
PDF documents like contracts and privacy policies are ripe with rich data points. Whether it’s detailed communications or transactions, these documents contain valuable information that can provide smarter insights. But harnessing this information is no easy task.
Zoning is specifically designed to turn unstructured information typically stored in PDFs into readily accessible blocks of data that can be used in machine learning environments to drive smarter business outcomes.
In this whitepaper, we’ll explain and detail why zoning content within PDF’s and categorizing them into different zone types is an essential endeavor.
How zoning works and why it’s an essential step for data creation
How zoning is employed in typical workflows
Challenges with zoning and how to overcome them
The type of datasets produced by the zoning process