fix: switch tier bonuses from additive to percentage-based
Additive bonuses (+12 fixed points) didn't scale with the blended
score range. Log-compressed popularity puts most scores in a narrow
80-92 band, making +12 disproportionately large.
Percentage multipliers scale naturally:
Artist: exact +15%, starts-with +8%, substring 0%, none -15%
Album: credit-exact +15%, credit-contains +10%, title-exact +5%,
title-contains 0%, none -10%
A tier-0 exact match with blended score 86 gets 86×1.15=99.
A tier-1 starts-with with blended score 92 gets 92×1.08=99.
The 4× popularity gap exactly offsets the 7% tier advantage —
proportional behavior where the boost scales with the artist's
existing score rather than being a fixed number.
This commit is contained in:
+23
-24
@@ -902,29 +902,28 @@ const (
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minBlendedScore = 25
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)
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// tierBonus maps artist name-match tiers to additive score adjustments.
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// These are soft bonuses — a sufficiently popular lower-tier result can
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// overcome the tier advantage. The effective gap between adjacent tiers
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// (~6 points on a 0–100 scale) requires roughly a 4–5× popularity
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// difference to overcome.
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// tierBonus maps artist name-match tiers to percentage score multipliers.
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// Applied as: score = score * (1 + multiplier). A popular lower-tier
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// result can overcome the tier advantage when the popularity gap is
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// proportionally larger than the tier difference.
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//
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//nolint:gochecknoglobals
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var tierBonus = map[int]int{
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0: 12, // exact match: "shannon" == "shannon"
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1: 6, // starts with: "shannon" in "shannon and the clams"
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2: 0, // substring: "shannon" in "del shannon"
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3: -10, // no substring match: only individual words matched
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var tierBonus = map[int]float64{
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0: 0.15, // exact match: +15%
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1: 0.08, // starts with: +8%
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2: 0.0, // substring: no change
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3: -0.15, // no substring match: -15%
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}
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// rgTierBonus maps release group match tiers to additive score adjustments.
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// rgTierBonus maps release group match tiers to percentage multipliers.
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//
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//nolint:gochecknoglobals
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var rgTierBonus = map[int]int{
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0: 12, // artist credit exact match
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1: 8, // artist credit contains query
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2: 4, // title exact match
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3: 0, // title contains query
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4: -5, // no match in either field
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var rgTierBonus = map[int]float64{
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0: 0.15, // artist credit exact match: +15%
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1: 0.10, // artist credit contains query: +10%
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2: 0.05, // title exact match: +5%
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3: 0.0, // title contains query: no change
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4: -0.10, // no match: -10%
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}
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// mbSpecialPurposeArtists is a set of MusicBrainz Special Purpose
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@@ -1115,14 +1114,14 @@ func (e *Service) boostNameMatches(query string, result *MBSearchResult) {
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return
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}
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// Apply tier bonus/penalty to artist scores. This replaces
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// the hard tier sort — tiers are now additive adjustments to
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// the blended score, so a sufficiently popular near-match can
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// overcome an unpopular exact match.
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// Apply tier multiplier to artist scores. Percentage-based so the
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// boost scales with the artist's existing score — a popular
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// near-match can overcome an unpopular exact match when the
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// popularity gap is proportionally larger than the tier difference.
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if len(result.Artists) > 1 {
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for i := range result.Artists {
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tier := nameMatchTier(q, strings.ToLower(result.Artists[i].Name))
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result.Artists[i].Score += tierBonus[tier]
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result.Artists[i].Score = int(float64(result.Artists[i].Score) * (1.0 + tierBonus[tier]))
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}
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sort.SliceStable(result.Artists, func(i, j int) bool {
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@@ -1134,13 +1133,13 @@ func (e *Service) boostNameMatches(query string, result *MBSearchResult) {
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e.disambiguateSameNameArtists(q, result.Artists)
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}
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// Apply tier bonus/penalty to release group scores.
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// Apply tier multiplier to release group scores.
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if len(result.ReleaseGroups) > 1 {
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for i := range result.ReleaseGroups {
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tier := rgMatchTier(q,
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strings.ToLower(result.ReleaseGroups[i].Title),
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strings.ToLower(result.ReleaseGroups[i].ArtistCredit))
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result.ReleaseGroups[i].Score += rgTierBonus[tier]
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result.ReleaseGroups[i].Score = int(float64(result.ReleaseGroups[i].Score) * (1.0 + rgTierBonus[tier]))
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}
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sort.SliceStable(result.ReleaseGroups, func(i, j int) bool {
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