🎁 User Coverage

User Coverage#

The share of users for whom the system can make useful recommendations.

Important

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What it is#

User coverage is the fraction of the user base for whom the recommender can produce useful recommendations — how many users can the system serve? A system with excellent recommendations for only a subset of users has limited reach:

\[\text{User Coverage} = \frac{|\text{users served}|}{|\text{total users}|}.\]

What limits it#

New users with little or no history (the user-side cold-start problem) may get no personalized recommendations; sparse or atypical users are also hard to serve. Fallbacks — popularity lists, onboarding questionnaires, content-based profiles — extend coverage to these users.

Why it matters#

Coverage and accuracy trade off — it is easy to look accurate by only serving well-understood users — so user coverage keeps the evaluation honest about the whole population.

Theme: Recommender Systems · All terminology

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Mind map — connected ideas

Catalog Coverage · Item Coverage · Relevance in Recommender Systems · Customer Segmentation · Long-Tail Items · Intra-List Diversity (ILD)

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More in Recommender Systems

Catalog Coverage · Cosine Similarity of Item Features · Diminishing Utility · Diversity (in Recommender Systems) · Dominating in Recommender Systems · Genre Overlap · Hit Rate (HR) · Intra-List Diversity (ILD) · Item Coverage · Jaccard index · Novelty (in Recommender Systems) · Relevance in Recommender Systems · Self-Information of Popularity