The Journal of Machine Learning, GEO & Next-Gen Search Retrieval
Empirical forensic teardowns, Information Retrieval evaluations, and Generative Engine Optimization playbooks.
How to build and deploy high-performance Python MCP servers to expose real-time Search Console telemetry and site crawl graphs to Claude Code, Gemini, and local coding agents.
An empirical forensic investigation of 100 domains impacted by recent Google Core Updates: analyzing site reputation abuse, parasite SEO decay, and classifier thresholds.
A reverse-engineering of Google’s multi-stage neural retrieval pipeline: how NavBoost click logs, Dense Passage Retrieval, and Cross-Encoder rerankers select sources for AI Overviews.
How to build semantic topic clusters based on entity attribute trees, predicate relationships, and micro-contextual vector spaces rather than flat keyword groups.