feat(scoring): implemented tiered conflict severity system v2.73.0

src/retrieval/scoring.ts

@@ -168,6 +168,8 @@ function inverseDocumentFrequency(
     return Math.log((smoothN + 1) / (smoothContaining + 1)) + 1;
 }
 
+export type ConflictSeverity = 'NONE' | 'LOW' | 'MEDIUM' | 'HIGH';
+
 export interface ScoredDocument {
     index: number;
     score: number;
@@ -175,6 +177,7 @@ export interface ScoredDocument {
     recencyBoost: number;
     matchedTerms: string[];
     conflictDetected: boolean;
+    conflictSeverity: ConflictSeverity;
     informationDensity: number;
 }
 
@@ -216,8 +219,18 @@ export function scoreTfIdf(
         let score = 0;
         const matchedTerms: string[] = [];
 
-        // Conflict Detection: 문서 내 상충 지표 확인
-        const conflictDetected = docTokens.some(t => SCORING_CONFIG.CONFLICT_INDICATORS.has(t));
+        // Conflict Detection & Severity Analysis (Substring based for better recall with particles)
+        const rawText = `${doc.title} ${doc.content}`.toLowerCase();
+        const conflictMatches = [...SCORING_CONFIG.CONFLICT_INDICATORS].filter(indicator => 
+            rawText.includes(indicator.toLowerCase())
+        );
+        
+        const conflictDetected = conflictMatches.length > 0;
+        let conflictSeverity: ConflictSeverity = 'NONE';
+
+        if (conflictMatches.length >= 4) conflictSeverity = 'HIGH';
+        else if (conflictMatches.length >= 2) conflictSeverity = 'MEDIUM';
+        else if (conflictMatches.length === 1) conflictSeverity = 'LOW';
 
         for (const term of expandedQuery) {
             const tf = termFrequency(term, docTokens);
@@ -255,6 +268,7 @@ export function scoreTfIdf(
             recencyBoost,
             matchedTerms: [...new Set(matchedTerms)],
             conflictDetected,
+            conflictSeverity,
             informationDensity
         };
     });