How to automatically categorize and archive large amounts of documents?

Automatically categorizing and archiving large amounts of documents can be achieved through a combination of technologies such as natural language processing (NLP), machine learning, and document management systems. Here's how it works and an example:

How It Works

1. Document Ingestion: Collect documents from various sources (e.g., email, cloud storage, or local files).
2. Text Extraction: Use Optical Character Recognition (OCR) for scanned documents or direct text extraction for digital files.
3. Content Analysis: Apply NLP techniques to extract keywords, topics, and metadata (e.g., dates, authors).
4. Classification: Use machine learning models (e.g., supervised learning with labeled data) to categorize documents into predefined folders or tags.
5. Archiving: Store categorized documents in a structured format, often in a document management system (DMS) or cloud storage.

Example

A company receives thousands of invoices, contracts, and reports daily. An automated system:

• Extracts text from PDFs using OCR.
• Identifies document types (e.g., "Invoice," "Contract") using NLP.
• Tags them with metadata like "Vendor Name" or "Date."
• Moves them to corresponding folders in a cloud-based DMS.

Recommended Solution

For scalable and efficient document management, Tencent Cloud's Document Management Service (DMS) can be used. It supports automated classification, OCR, and secure storage, helping businesses organize large volumes of documents with minimal manual intervention. Additionally, Tencent Cloud's AI and Big Data services can enhance classification accuracy with advanced NLP models.

For example, a financial institution can use Tencent Cloud DMS to automatically categorize loan applications, contracts, and regulatory reports, ensuring quick retrieval and compliance.