Files
reader/configs/term_cleanup_policy.json
T
root 590d050218 keyword cleanup: v2 engine, alias rule layer, LLM semantic suggestions
- build_review_bundle.py: 新增 _compute_percentile/_compute_growth,
  候选池从固定阈值改为百分位排名 + 增速因子 (v2 policy)
- term_cleanup_policy.json: 升级 v2 schema
- generate_term_cleanup_suggestions.py: 新增 _prepare_alias_suggestions,
  规则层输出 alias (大小写/单复数/分词变体)
- generate_term_cleanup_semantic_suggestions.py: 新增 LLM 语义建议脚本
  (DeepSeek API, 产出 semantic alias/stopword/promote)
- SKILL.md: 更新为 5 Phase 工作流程
- 首轮清洗 apply: interest 54, aliases 17组, stopwords 17个
- docs/design/keyword-cleanup-flow-overview.md: 流程文档
- plans/: 引擎设计方案
2026-05-14 17:17:49 +08:00

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{
"schema_version": "v2",
"interest_keyword_review": {
"percentile_max": 0.05,
"growth_promotion": 0.5
},
"watch_term_review": {
"percentile_min": 0.05,
"percentile_max": 0.20
},
"alias_review": {
"min_total_count": 2,
"min_days_seen": 2
},
"stopword_review": {
"max_total_count": 2,
"max_days_seen": 2
},
"notes": [
"v2: interest/watch 使用百分位排名 + 增速因子替代固定阈值",
"percentile 越小表示排名越高(top 5% = percentile 0.05)",
"growth = recent_count / total_count,衡量近期活跃度",
"watch_term_review 的 percentile_min 可理解为兴趣边界下限,低于此值的词归入 interest 候选",
"growth_promotion(默认 0.5)用于识别近期集中爆发词,即使排位不高也主动推荐确认"
]
}