flat:6.20添加视频板块存档

stores/useRecommedIndexedDBStore.js

@@ -10,7 +10,7 @@ import {
     msg
 } from '@/common/globalFunction.js'
 import baseDB from './BaseDBStore';
-
+import config from '../config';
 
 class JobRecommendation {
     constructor() {
@@ -62,6 +62,30 @@ class JobRecommendation {
     }
 }
 
+/**
+ * 计算加权用户行为偏好
+ * @param {Object} data - 用户行为数据，包括 categories、experience、areas、salary 等
+ * @param {Object} weights - 每一类行为的权重
+ * @returns {Object} 加权合并后的结果（key 为行为项，value 为权重后的分值）
+ */
+function applyWeightsToUserData(data, weights) {
+    const result = {}
+
+    for (const key in data) {
+        if (key === 'salary') {
+            result.salary = weights.salary
+        } else if (typeof data[key] === 'object') {
+            result[key] = {}
+            for (const itemKey in data[key]) {
+                const rawValue = data[key][itemKey]
+                result[key][itemKey] = parseFloat((rawValue * weights[key]).toFixed(2))
+            }
+        }
+    }
+
+    return result
+}
+
 // **🔹 创建推荐系统**
 export const jobRecommender = new JobRecommendation();
 
@@ -121,8 +145,9 @@ export const useRecommedIndexedDBStore = defineStore("indexedDB", () => {
     }
 
     function analyzer(jobsData) {
-        const result = jobAnalyzer.analyze(jobsData)
-        const sort = jobAnalyzer.printUnifiedResults(result)
+        const result = jobAnalyzer.analyze(jobsData) // 转换格式化
+        const result2 = applyWeightsToUserData(result, config.weights) // 添加权重
+        const sort = jobAnalyzer.printUnifiedResults(result2) // 转换格式化
         return {
             result,
             sort