Search, Recommendation, and Generation System Map

Search, Recommendation, and Generation System Map

Search begins with an expressed information need. The system interprets a query, retrieves candidates from an eligible corpus, and ranks them for that need.

Recommendation predicts which items may be useful or engaging from user, item, context, and interaction signals. It may have no explicit query. Production recommenders commonly separate candidate retrieval from ranking and post-ranking.

Generation can explain, summarize, or synthesize over retrieved material, but it does not replace corpus eligibility, retrieval, ranking, provenance, or evaluation. Similar interfaces can hide different discovery systems, so product language should name the actual path.