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岗位类型(三级): 同三级=100 / 同二级=90 / 同一级=85 / 不相关=10

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行业(两级):     同二级=100 / 同一级=90 / 不相关=10
fit = min(100, 岗位类型分 × 0.9 + 行业分 × 0.6)
无 AI 分析（两个方向都空）→ 中性分 40
This commit is contained in:
zk
2026-07-14 14:34:35 +08:00
parent 0a413be803
commit dfb79160df
1 changed files with 20 additions and 26 deletions
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manager/src/main/java/org/jiayunet/service/JobMatchService.java
+20 -26
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@@ -148,37 +148,34 @@ public class JobMatchService {
/**
* 计算方向适配得分 fitScore（百分制）
* <p>基于 AI 推荐的岗位方向/行业方向与岗位实际类型/公司行业做层级匹配</p>
* <p>fitScore = 岗位类型分×70% + 行业分×30%</p>
* <p>用户未做过 AI 分析（无 AI 推荐方向）时返回 0</p>
* <p>fitScore = min(100, 岗位类型分×0.9 + 行业分×0.6)：两项加法叠加，均强相关时溢出封顶 100</p>
* <p>用户未做过 AI 分析（无任何 AI 推荐方向）时返回中性分 40（方向未知，疑罪从无）</p>
*/
private int calculateFitScore(JobListItemVo job, List<Long> aiCategoryIds, List<Long> aiIndustryIds,
Map<Long, JobCategory> categoryMap, Map<Long, Industry> industryMap) {
boolean noCategory = aiCategoryIds == null || aiCategoryIds.isEmpty();
boolean noIndustry = aiIndustryIds == null || aiIndustryIds.isEmpty();
// 无任何 AI 推荐方向 → 不参与加分
// 无任何 AI 推荐方向 → 方向未知，给中性分
if (noCategory && noIndustry) {
return 0;
return 40;
}
int categoryScore = calculateCategoryFit(aiCategoryIds, job.getCategoryId(), categoryMap);
int industryScore = calculateIndustryFit(aiIndustryIds, job.getCompanyIndustryId(), industryMap);
double categoryContribution = noCategory ? 0 : calculateCategoryFit(aiCategoryIds, job.getCategoryId(), categoryMap) * 0.9;
double industryContribution = noIndustry ? 0 : calculateIndustryFit(aiIndustryIds, job.getCompanyIndustryId(), industryMap) * 0.6;
return (int) Math.round(categoryScore * 0.7 + industryScore * 0.3);
return Math.min(100, (int) Math.round(categoryContribution + industryContribution));
}
/**
* 计算岗位类型方向匹配分（三级树，取 AI 推荐中的最高分）
* <p>同三级→100，同二级→70，同一级→30，否则→0</p>
* <p>同三级→100，同二级→90，同一级→85，不相关→10（保底）</p>
*/
private int calculateCategoryFit(List<Long> aiCategoryIds, Long jobCategoryId, Map<Long, JobCategory> categoryMap) {
if (aiCategoryIds == null || aiCategoryIds.isEmpty() || jobCategoryId == null) {
return 0;
}
JobCategory jobCategory = categoryMap.get(jobCategoryId);
JobCategory jobCategory = jobCategoryId == null ? null : categoryMap.get(jobCategoryId);
if (jobCategory == null) {
return 0;
return 10;
}
int maxScore = 0;
int maxScore = 10;
for (Long aiId : aiCategoryIds) {
JobCategory aiCategory = categoryMap.get(aiId);
if (aiCategory == null) continue;
@@ -186,11 +183,11 @@ public class JobMatchService {
if (aiCategory.getId().equals(jobCategory.getId())) {
score = 100;
} else if (aiCategory.getParentId() != null && aiCategory.getParentId().equals(jobCategory.getParentId())) {
score = 70;
score = 90;
} else if (aiCategory.getRootId() != null && aiCategory.getRootId().equals(jobCategory.getRootId())) {
score = 30;
score = 85;
} else {
score = 0;
score = 10;
}
maxScore = Math.max(maxScore, score);
if (maxScore == 100) return 100;
@@ -200,17 +197,14 @@ public class JobMatchService {
/**
* 计算行业方向匹配分（两级树，取 AI 推荐中的最高分）
* <p>同二级→100，同一级→60，否则→0</p>
* <p>同二级→100，同一级→90，不相关→10（保底）</p>
*/
private int calculateIndustryFit(List<Long> aiIndustryIds, Long companyIndustryId, Map<Long, Industry> industryMap) {
if (aiIndustryIds == null || aiIndustryIds.isEmpty() || companyIndustryId == null) {
return 0;
}
Industry companyIndustry = industryMap.get(companyIndustryId);
Industry companyIndustry = companyIndustryId == null ? null : industryMap.get(companyIndustryId);
if (companyIndustry == null) {
return 0;
return 10;
}
int maxScore = 0;
int maxScore = 10;
for (Long aiId : aiIndustryIds) {
Industry aiIndustry = industryMap.get(aiId);
if (aiIndustry == null) continue;
@@ -218,9 +212,9 @@ public class JobMatchService {
if (aiIndustry.getId().equals(companyIndustry.getId())) {
score = 100;
} else if (aiIndustry.getParentId() != null && aiIndustry.getParentId().equals(companyIndustry.getParentId())) {
score = 60;
score = 90;
} else {
score = 0;
score = 10;
}
maxScore = Math.max(maxScore, score);
if (maxScore == 100) return 100;