Chapter 21: Search, Ranking & Recommendation Systems

Search, ranking, and recommendation systems turn user intent, content, and behavior into an ordered set of useful results. This chapter follows the path from indexing and candidate retrieval through scoring, personalization, and controlled experimentation.

• 21.1 Inverted Indices & Search Engines (Lucene/Elasticsearch/OpenSearch)
• 21.2 Ranking Algorithms: TF-IDF, BM25, Learning-to-Rank
• 21.3 Recommendation Architectures: Collaborative Filtering, Content-Based, Hybrid, Two-Tower Retrieval + Ranking
• 21.4 Real-Time Personalization: Feature Freshness, Online Learning, A/B Test Infrastructure
• Chapter 21 References