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minstrel/internal/recommendation/similarity.go
T

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package recommendation
// SimilarityWeights balances the per-axis contribution to the weighted Jaccard
// score. v1 hardcodes the defaults — operators cannot tune via YAML. If
// telemetry justifies it, expose under recommendation.similarity.* later.
type SimilarityWeights struct {
TagsWeight float64
ArtistsWeight float64
}
// DefaultSimilarityWeights is the v1 axis balance per the M3 design.
// Tags carry more signal than artists because a session's "vibe" tracks
// genre more directly than artist identity (a session can mix artists
// within a genre but rarely mixes genres).
var DefaultSimilarityWeights = SimilarityWeights{
TagsWeight: 0.7,
ArtistsWeight: 0.3,
}
// Similarity returns weighted-Jaccard similarity in [0, 1] between two
// session vectors. Returns 0 if either input is Seed=true (low-confidence
// vectors don't contribute to scoring).
func Similarity(a, b SessionVector, w SimilarityWeights) float64 {
if a.Seed || b.Seed {
return 0.0
}
tagJ := setJaccardKeys(a.Tags, b.Tags)
artistJ := setJaccardSlice(a.Artists, b.Artists)
return tagJ*w.TagsWeight + artistJ*w.ArtistsWeight
}
// setJaccardKeys collapses two map keysets to sets and returns
// |A ∩ B| / |A B|. Both empty → 0 (not NaN).
func setJaccardKeys(a, b map[string]int) float64 {
if len(a) == 0 && len(b) == 0 {
return 0.0
}
intersect := 0
for k := range a {
if _, ok := b[k]; ok {
intersect++
}
}
union := len(a) + len(b) - intersect
if union == 0 {
return 0.0
}
return float64(intersect) / float64(union)
}
// setJaccardSlice deduplicates each input slice into a set and returns
// |A ∩ B| / |A B|. Both empty → 0 (not NaN).
func setJaccardSlice(a, b []string) float64 {
if len(a) == 0 && len(b) == 0 {
return 0.0
}
aset := make(map[string]struct{}, len(a))
for _, x := range a {
aset[x] = struct{}{}
}
bset := make(map[string]struct{}, len(b))
for _, x := range b {
bset[x] = struct{}{}
}
intersect := 0
for k := range aset {
if _, ok := bset[k]; ok {
intersect++
}
}
union := len(aset) + len(bset) - intersect
if union == 0 {
return 0.0
}
return float64(intersect) / float64(union)
}