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Advanced RAG 02: Unveiling PDF Parsing
Latest   Machine Learning

Advanced RAG 02: Unveiling PDF Parsing

Last Updated on February 2, 2024 by Editorial Team

Author(s): Florian June

Originally published on Towards AI.

Including key points, diagrams, and code

For RAG, the extraction of information from documents is an inevitable scenario. Ensuring the effectiveness of content extraction from the source is crucial in improving the quality of the final output.

It is important not to underestimate this process. When implementing RAG, poor information extraction during the parsing process can lead to limited understanding and utilization of the information contained in PDF files.

The position of the Pasing process in RAG is shown in Figure 1:

Figure 1 : The position of the Pasing process(red box) in RAG. Image by author.

In practical work, unstructured data is much more abundant than structured data. If these massive amounts of data cannot be parsed, their tremendous value will not be realized.

In unstructured data, PDF documents account for the majority. Effectively handling PDF documents can also greatly assist in managing other types of unstructured documents.

This article primarily introduces methods for parsing PDF files. It provides algorithms and suggestions for effectively parsing PDF documents and extracting as much useful information as possible.

PDF documents are representative of unstructured documents, however, extracting information from PDF documents is a challenging process.

Instead of being a data format, it is more accurate to describe PDF as a collection of printing instructions. A PDF… Read the full blog for free on Medium.

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