Wissenswertes

Key Takeaways: Metehan analyzed Common Crawl (CC) data and found a correlation to citation frequency in LLM Chats such as ChatGPT, Perplexity and others: Most major LLMs were trained on CC data (64% of models studied, 80%+ of GPT-3 tokens) CC prioritizes high-authority domains in its crawling via Harmonic Centrality These same domains tend to be cited most frequently by LLMs Feel free to use his tool to analyze Common Crawl authority scores for your domain or industry:...

Key Takeaways: Anderson analyzed the Google Leak & DOJ testimony: A deep dive mapping Google's Search Essentials and Helpful Content questions to leaked Content Warehouse attributes like Q*, siteAuthority, contentEffort, and predictedDefaultNsr. From Navboost to contentEffort he provides a clear understanding of how Google is or likely is working ICYMI: Back in 2024 the Website Boosting article from Mario Fischer visually outlined it pretty well Example I: EEAT decoded E-E-A-

Key Takeaways: Query Fan-Out auf Basis von Such-Ergebnissen ist sequentieller, sich wiederholender Prozess Es ist möglich diesen Prozess...

Search Engines moved beyond keywords into understanding language in the vector space Maximum Inner Product Search (MIPS) aims at maximizing the inner product of a given query for a set of vectors