faculty_expertise
♥Cherished
Scrape and enrich faculty information from university department websites using specialized crawlers for different content management systems. The tool extracts contact details and research expertise, then generates structured semantic summaries of faculty research using AI, enabling institutional analysis of departmental expertise and interdisciplinary relationships.
Clauded With Love Rating
7.5 / 10
This project scrapes faculty information from UCSB departmental websites and enriches it with AI-generated research summaries to create structured institutional expertise databases. It uses nbdev for literate programming and provides specialized scrapers for different CMS platforms along with OpenAI integration for semantic analysis.
Code Quality6.5
Usefulness8.0
Claude Usage7.5
Documentation8.5
Originality7.0
Highlights
- ✓Clean nbdev-based architecture with notebook-driven development that maintains documentation and code together
- ✓Practical modular design with specialized scrapers for different CMS types (Drupal, WordPress) showing real-world adaptability
- ✓Comprehensive README with clear installation options, usage examples, and well-organized project structure explanation
To Improve
- →Add error handling and validation for malformed HTML, network failures, and API rate limits in the scraping and enrichment modules
- →Include unit tests and CI/CD pipeline to ensure reliability across different department website structures and API changes