About BizPub.ai

Existing journal ranking and publication databases share common issues:

• Outdated, poorly designed interfaces with clunky user experience
• Not transparent enough about how data is collected or processed
• Static and infrequently updated
• Manually maintained by human labor
• No open data access for researchers

I've been trying to build this with my students for many years. It always fails the same way:

• Students who built the crawlers and analytics code come and go — code goes stale, bugs go unfixed
• Publishers change their sites and crawlers break
• Rule-based parsing and matching algorithms are brittle
• Manual data validation and correction is labor intensive and costly

Maintenance is the hard part and not sustainable for the long run.

BizPub.ai is my experiment in using AI agents to autonomously crawl, clean, and maintain the publication database. The agents analyze publisher websites to develop crawlers, crawl data with strategies to avoid banning, run automatic quality validation, and self-heal when publisher sites change or data quality issues are reported by humans—all with as little human intervention as possible. The entire project is now maintained by me and AI.