NLP (Natural Language Processing)
Theoretical FoundationsNLP (Natural Language Processing) is a branch of artificial intelligence focused on enabling computers to process, analyze, and understand human language — the foundation of search engines and AI Search.
In semantic SEO applications, key NLP techniques include TF-IDF, BM25, contextual embeddings (BERT), Semantic Role Labels, and Frame Semantics. Understanding NLP helps you write content that works for both machines and humans. It also enables conscious optimization for each stage of the RAG pipeline. NLP enables advanced semantic analysis techniques — SRL, Entity Salience, Information Density.
While the mathematical foundations are complex, SEO practitioners benefit from understanding NLP's practical implications. Passive voice reduces Salience through SRL analysis. Generalities decrease Information Density scores. Poor structure increases the Cost of Retrieval. Modern SEO tools incorporate automated NLP analysis, enabling content optimization based on these principles.