Show HN: Mapping Hacker News' Favorite Books with GPT-4o
Analysis
This project leverages GPT-4o to analyze Hacker News comments and create a visual map of recommended books. The methodology involves scraping comments, extracting book references and opinions, and using UMAP and HDBSCAN for dimensionality reduction and clustering. The project highlights the challenges of obtaining high-quality book cover images. The use of GPT-4o for both data extraction and potentially description generation is noteworthy. The project's focus on visualizing book recommendations aligns with the user's stated goal of recreating the serendipitous experience of browsing a physical bookstore.
Key Takeaways
- •Uses GPT-4o for book recommendation extraction and description generation.
- •Employs UMAP and HDBSCAN for visualizing book embeddings.
- •Highlights the difficulty of obtaining reliable book cover images.
- •Aims to recreate the experience of browsing a physical bookstore through a digital map of book recommendations.
“The project uses GPT-4o mini for extracting references and opinions, UMAP and HDBSCAN for visualization, and a hacked-together process using GoodReads and GPT for cover images.”