Search Indexing and Retrieval
Search Ranking And Recommendation
Index construction, lexical retrieval models, postings mechanics, ranking baselines, and the retrieval-system boundary before serving, vector search, and evaluation tracks.
Search Ranking And Recommendation
TRACKS
Ranking, Evaluation, and Search Quality
Search Ranking And Recommendation
Learning to rank, experimentation, evaluation pipelines, and search quality governance.
Web Crawling and Corpus Acquisition
Search Ranking And Recommendation
Crawler frontiers, politeness, canonicalization, parsing, duplicate control, freshness, corpus governance, and the handoff from web acquisition into search indexing.
Knowledge Graphs and Entity Resolution
Search Ranking And Recommendation
Entity linking, graph modeling, canonicalization, and the data structures used to connect knowledge across noisy sources.
Large-Scale Data Mining
Search Ranking And Recommendation
Approximation, sketching, distributed analytics, graph mining, clustering, and operational judgment for massive datasets without mixing in personalization product loops.
Ads, Auctions, and Marketplace Ranking
Search Ranking And Recommendation
Auction design, bidding signals, marketplace objectives, and the ranking trade-offs unique to monetized retrieval systems.
Query Understanding and Semantic Retrieval
Search Ranking And Recommendation
Intent parsing, reformulation, semantic matching, and the retrieval improvements that start from better representations of user needs.
Experimentation and Online Learning for Ranking
Search Ranking And Recommendation
Interleaving, A/B testing, bandits, feedback loops, and the online methods used to improve ranking systems safely.
Recommendation and Personalization Systems
Search Ranking And Recommendation
Candidate generation, multi-stage ranking, feedback loops, experimentation, fairness, and serving architecture for personalization systems.
Retrieval and Ranking Foundations
Search Ranking And Recommendation
Indexing basics, ranking intuition, query-document matching, and the introductory mental models behind search and recommendation quality.
Vector Search and Embedding Systems
Search Ranking And Recommendation
Draft track for embeddings, ANN indexes, hybrid retrieval, vector databases, and retrieval serving trade-offs.
Search Engine Serving and Operations
Search Ranking And Recommendation
Production search serving: schemas, analyzers, shards, query execution, aggregations, relevance tuning, hybrid search, indexing pipelines, cluster operations, and incidents.