Files
minstrel/internal/recommendation/score.go
T

86 lines
2.7 KiB
Go

// Package recommendation implements the weighted-shuffle scoring engine
// from spec §6. The Score function is pure and takes an injectable RNG so
// tests can pin jitter to deterministic values.
package recommendation
import (
"time"
)
// ScoringInputs are the per-track facts the score function consumes.
// ContextualMatchScore is in [0, 1] — max similarity between the user's
// current session vector and any non-seed contextual_like row for this
// track. Set by LoadCandidates after a bulk fetch.
type ScoringInputs struct {
IsGeneralLiked bool
LastPlayedAt *time.Time // nil = never played
PlayCount int // total play_events
SkipCount int // play_events with was_skipped=true
ContextualMatchScore float64 // [0, 1]; 0 when no signal
}
// ScoringWeights are the operator-tunable knobs. Defaults live in
// config.RecommendationConfig and are propagated here per request.
type ScoringWeights struct {
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
}
// Score computes the weighted-shuffle score per spec §6:
//
// score = base
// + (is_general_liked ? LikeBoost : 0)
// + recency_decay * RecencyWeight
// - skip_ratio * SkipPenalty
// + contextual_match_score * ContextWeight
// + small_random_jitter
//
// Higher score = more likely to surface. rng is a function returning a
// uniform sample in [0,1) — pass math/rand.Float64 in production, a fixed
// value in tests.
func Score(in ScoringInputs, w ScoringWeights, now time.Time, rng func() float64) float64 {
s := w.BaseWeight
if in.IsGeneralLiked {
s += w.LikeBoost
}
s += recencyDecay(in.LastPlayedAt, now) * w.RecencyWeight
s -= skipRatio(in.PlayCount, in.SkipCount) * w.SkipPenalty
s += in.ContextualMatchScore * w.ContextWeight
s += (rng()*2 - 1) * w.JitterMagnitude
return s
}
// recencyDecay returns a value in [0, 1]:
// - never played → 1.0 (cold-start tracks compete favorably with stale ones).
// - age < 30 days → linear ramp age_days / 30.
// - age ≥ 30 days → 1.0 (capped).
//
// Negative ages (clock skew) clamp to 0 to avoid math weirdness.
func recencyDecay(lastPlayed *time.Time, now time.Time) float64 {
if lastPlayed == nil {
return 1.0
}
age := now.Sub(*lastPlayed)
days := age.Hours() / 24
if days < 0 {
return 0.0
}
if days >= 30 {
return 1.0
}
return days / 30.0
}
// skipRatio returns skips/plays in [0, 1]; never-played tracks return 0
// rather than dividing by zero, so they aren't penalized.
func skipRatio(plays, skips int) float64 {
if plays == 0 {
return 0.0
}
return float64(skips) / float64(plays)
}