From 93087001f97658df26ce09effb440ef683e94ffd Mon Sep 17 00:00:00 2001
From: Linrador <68631622+Linrador@users.noreply.github.com>
Date: Fri, 12 Jun 2026 09:21:35 +0200
Subject: [PATCH] updated rating

---
 backend/rating.go | 20 ++++++++++++++------
 1 file changed, 14 insertions(+), 6 deletions(-)

diff --git a/backend/rating.go b/backend/rating.go
index 5144447..012d95d 100644
--- a/backend/rating.go
+++ b/backend/rating.go
@@ -1348,6 +1348,7 @@ func computeHighlightRatingWithUsername(segments []aiSegmentMeta, durationSec fl
 	var totalWeighted float64
 
 	var positionEffectiveWeighted float64
+	var positionFlagged float64
 	var peakQuality float64
 
 	var longest float64
@@ -1395,6 +1396,7 @@ func computeHighlightRatingWithUsername(segments []aiSegmentMeta, durationSec fl
 			continue
 		}
 		positionEffectiveWeighted += effectiveWeightedDur
+		positionFlagged += segDur
 
 		if quality > peakQuality {
 			peakQuality = quality
@@ -1424,17 +1426,22 @@ func computeHighlightRatingWithUsername(segments []aiSegmentMeta, durationSec fl
 	positionDensityNorm := ratingSoftCap(positionDensity, 5.5)
 	coverageNorm := ratingSoftCap(weightedCoverageRatio, 0.20)
 	longestNorm := ratingSoftCap(longest, 24.0)
+	positionDurationNorm := ratingSoftCap(positionFlagged, 45.0)
 	confNorm := ratingSmoothStep((avgConfidence - 0.30) / 0.65)
 
 	// Positionen dominieren. Kleidung/Objekte fließen durch Combo-Segment-Qualität (peakNorm) ein.
+	// Die Länge der erkannten Positionen wird bewusst stark gewichtet:
+	// längstes Positions-Segment (longestNorm) + Gesamtdauer aller Positionen (positionDurationNorm).
+	// Je länger eine Position erkannt wird, desto höher der Score.
 	// Keine Penalties, keine Caps – die Formel bewertet natürlich nach Positions-Intensität.
 	// Summe = 1.00.
 	raw :=
-		0.42*positionDensityNorm +
-			0.26*peakNorm +
-			0.18*coverageNorm +
-			0.08*longestNorm +
-			0.06*confNorm
+		0.34*positionDensityNorm +
+			0.22*peakNorm +
+			0.13*coverageNorm +
+			0.16*longestNorm +
+			0.11*positionDurationNorm +
+			0.04*confNorm
 
 	// Sehr wenig Material nicht überbewerten.
 	if totalFlagged < 5.0 && n <= 1 {
@@ -1469,13 +1476,14 @@ func computeHighlightRatingWithUsername(segments []aiSegmentMeta, durationSec fl
 	r.AvgConfidence = ratingRound(avgConfidence, 3)
 
 	appLogf(
-		"✅ %s rating score=%.1f stars=%d bonus=%.1f segs=%d flagged=%.1f posDensity=%.2f coverage=%.4f longest=%.1f avgConf=%.3f",
+		"✅ %s rating score=%.1f stars=%d bonus=%.1f segs=%d flagged=%.1f posFlagged=%.1f posDensity=%.2f coverage=%.4f longest=%.1f avgConf=%.3f",
 		ratingLogSubject(username),
 		r.Score,
 		r.Stars,
 		ratingRound(excellenceBonus*100, 1),
 		r.Segments,
 		r.FlaggedSeconds,
+		ratingRound(positionFlagged, 1),
 		positionDensity,
 		r.WeightedCoverageRatio,
 		r.LongestSegmentSeconds,