While standard PDF viewers facilitate keyword retrieval, they often lack aggregate analytical capabilities. This web application provides quantitative insights regarding token distribution within PDF documents.
Key Features:
- Longitudinal Analysis: Visualization of word frequency across pages for selected tokens.
- Frequency Metrics: Identification of the most frequently occurring tokens.
- Length Metrics: Extraction of the longest tokens.
- Client-Side Processing: All PDF operations are executed in the frontend, requiring negligible backend resources.
Demo: ignaz.dev
Case Study:
The PostgreSQL manual (Version 18), comprising over 3,000 pages, is available here. The analysis below illustrates the distribution of the tokens view and materialized within this document:
Multi-architecture images (amd64, arm) are available via Docker Hub:
brunoir/pdf-freq-analysis
Clone the repository and execute the development script:
npm run dev
- Text Extraction: @hyzyla/pdfium
- Autocomplete: primereact, @kamilmielnik/trie
- Other: react, @nivo/line