Jaccard index#
Intersection over union of two sets, a similarity measure.
Important
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What it is#
The Jaccard index (Jaccard similarity coefficient) measures the overlap between two sets — the size of their intersection over the size of their union. For items, the sets are typically the users who liked each item, or their tags / features.
The formula#
ranging 0 to 1 — 0 for disjoint sets, 1 for identical ones; the complement \(1 - J\) is the Jaccard distance.
When to use it#
It is the natural choice for binary (like / dislike, present / absent) data, where magnitudes don’t matter — only which elements are shared. Contrast with cosine, which works on real-valued vectors.
Theme: Recommender Systems · All terminology
Hint
Mind map — connected ideas
Cosine Similarity of Item Features · Intra-List Diversity (ILD) · Genre Overlap · Cramér’s V · Relevance in Recommender Systems · Catalog Coverage
Hint
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 · 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: Jaccard index (insightful-data-lab.com).