Bring structure to document collections
Content classification turns an unlabelled collection into documents organised by their purpose.
A project from peoly’s published portfolio.
- 01Document content
- 02Type classification
- 03Organized storage
The challenge: a collection without categories
When documents arrive without useful labels, deciding where each belongs can become a repetitive manual task. Filenames alone may not tell the person processing them what type of content is inside.
Classifying by content
peoly’s published natural-language-processing solution analyses document content and assigns predefined types. Those types provide a structure for storing documents in a database or sorting them into the corresponding categories.
The original portfolio illustrates this with an unlabelled collection of PDF files: a classifier sorts them into agreed groups without requiring someone to open each file individually. The categories are defined for the task rather than assumed from the document’s filename.
Connecting the result to the workflow
Classification becomes useful when the result has a destination. This project description connects content analysis with the organisation and storage of the documents.
For a new collection, the starting point is representative documents, a clear category scheme and the handling rules for each category. The workflow also needs a decision about how to treat content that cannot be assigned confidently. These choices turn a model output into a practical document-processing step.
A similar challenge in your operation?
Tell us about your data, devices and the workflow you want to improve.