Diversity (in Recommender Systems)#
How varied the items within a recommendation list are.
Important
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What it is#
Diversity measures how varied the items within a single recommendation list are — the opposite of ten near-identical suggestions. A diverse list spans a user’s multiple interests rather than hammering one.
How it’s measured#
The standard gauge is intra-list dissimilarity — the average pairwise distance between recommended items (often 1 − cosine similarity of their features), captured by Intra-List Diversity. At the catalog level, Gini or entropy across all recommendations measures aggregate diversity.
Why it matters#
Diversity improves the experience — it hedges against a wrong guess about intent and keeps lists interesting — but there’s an accuracy-diversity trade-off, since the most “accurate” items are often similar. Good systems tune diversity without dumping relevance.
Theme: Recommender Systems · All terminology
Hint
Mind map — connected ideas
Novelty (in Recommender Systems) · Coverage · Intra-List Diversity (ILD) · Cosine Similarity of Item Features · Relevance in Recommender Systems · NDCG (Normalized Discounted Cumulative Gain)
Hint
More in Recommender Systems
Catalog Coverage · Cosine Similarity of Item Features · Diminishing Utility · 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 · User Coverage
See also
Source article Adapted (context, re-expressed) in our own words from: Diversity (in Recommender Systems) (insightful-data-lab.com).