115 lines
4.4 KiB
Markdown
115 lines
4.4 KiB
Markdown
# 大厂AI推荐数据库 (Crowd Detection Database)
|
||
|
||
## 用途
|
||
|
||
存储大厂AI(千问/元宝/百度/豆包)的高频推荐院校,
|
||
用于反扎堆检测功能。
|
||
|
||
## 数据格式
|
||
|
||
按省份组织,每个JSON文件包含该省的推荐数据 + 溯源元数据(T3.1 schema):
|
||
|
||
```json
|
||
{
|
||
"province": "湖南",
|
||
"last_updated": "2026-06-12",
|
||
"data_year": 2025,
|
||
"source": "千问/元宝/百度/豆包 公开推荐汇总(手动整理)",
|
||
"source_url": "https://github.com/phamnazage-jpg/gaokao-volunteer-system/blob/main/data/crowd_db/hunan.json",
|
||
"source_type": "manual_summary",
|
||
"confidence": 0.85,
|
||
"score_ranges": [
|
||
{
|
||
"range": [560, 580],
|
||
"note": "一本中段",
|
||
"recommendations": [
|
||
{
|
||
"name": "长沙理工大学",
|
||
"major": "会计学",
|
||
"frequency": 4,
|
||
"platforms": ["千问", "元宝", "百度", "豆包"],
|
||
"predicted_increase": 18,
|
||
"alternatives": [
|
||
{ "name": "湖南工商大学", "major": "会计学", "score": 95 },
|
||
{ "name": "湖北经济学院", "major": "财务管理", "score": 92 }
|
||
]
|
||
}
|
||
]
|
||
}
|
||
]
|
||
}
|
||
```
|
||
|
||
## 字段说明
|
||
|
||
### 顶层溯源字段(T3.1)
|
||
|
||
| 字段 | 类型 | 必填 | 说明 |
|
||
| -------------- | --------- | ---- | --------------------------------------------------------------------- |
|
||
| `province` | str | ✅ | 省份中文名 |
|
||
| `last_updated` | str (ISO) | ✅ | 文件最后更新日期 `YYYY-MM-DD` |
|
||
| `data_year` | int | ✅ | 数据参考年份(如 `2025` 代表基于 2025 高考数据) |
|
||
| `source` | str | ✅ | 数据来源描述(人类可读) |
|
||
| `source_url` | str | ⚠️ | 数据源 URL;无则填空串 |
|
||
| `source_type` | str enum | ✅ | `manual_summary` / `official_release` / `platform_scrape` / `derived` |
|
||
| `confidence` | float | ✅ | 数据可信度 `[0.0, 1.0]`;`< 0.5` 视为骨架,loader 打印 UserWarning |
|
||
| `score_ranges` | list | ✅ | 分数段列表;骨架文件允许 `[]` |
|
||
|
||
### 分数段与推荐
|
||
|
||
| 字段 | 说明 |
|
||
| -------------------- | ---------------------------- |
|
||
| `range` | 分数区间 [min, max] |
|
||
| `note` | 段名/批次说明 |
|
||
| `recommendations` | 推荐条目列表 |
|
||
| `frequency` | 4个大厂AI中有几个推荐(0-4) |
|
||
| `platforms` | 具体推荐了哪些AI |
|
||
| `predicted_increase` | 预测2026年分数线上涨分 |
|
||
| `alternatives` | 替代院校推荐 |
|
||
|
||
完整 schema 见 [SCHEMA.md](SCHEMA.md)。
|
||
|
||
## 27省文件清单(T3.1)
|
||
|
||
- 23省:`hebei / shanxi / liaoning / jilin / heilongjiang / jiangsu / zhejiang / anhui / fujian / jiangxi / shandong / henan / hubei / hunan / guangdong / hainan / sichuan / guizhou / yunnan / shaanxi / gansu / qinghai / xinjiang`
|
||
- 4直辖市:`beijing / shanghai / tianjin / chongqing`
|
||
|
||
> 不含 5个自治区(内蒙古/广西/西藏/宁夏)、香港、澳门、台湾。
|
||
|
||
## 数据来源
|
||
|
||
- 手动整理大厂AI公开推荐
|
||
- 高考季后期的实际数据
|
||
- 不爬虫、不抓取(合规考虑)
|
||
- 高置信度文件(`confidence ≥ 0.8`):仅湖南;其余省份当前为骨架初版(`confidence ≈ 0.45`),待人工补完
|
||
|
||
## 更新频率
|
||
|
||
每周更新一次,高考季(6-7月)每周两次
|
||
|
||
## Loader 接口(T3.1)
|
||
|
||
```python
|
||
from data.crowd_db.loader import CrowdDBLoader
|
||
|
||
loader = CrowdDBLoader()
|
||
|
||
# 1) 取推荐
|
||
recs = loader.find_recommendations("湖南", score=575)
|
||
|
||
# 2) 仅取溯源元数据
|
||
meta = loader.load_metadata("湖南")
|
||
# → {province, last_updated, data_year, source, source_url, source_type, confidence, record_count}
|
||
|
||
# 3) 列出全部支持的省份(27 个)
|
||
all_p = loader.list_supported_provinces()
|
||
|
||
# 4) 列出实际存在的省份元数据
|
||
existing = loader.list_provinces()
|
||
```
|
||
|
||
完整数据生成脚本(含 27 省份 schema 校验)位于:
|
||
`/home/long/.hermes/kanban/workspaces/t_71bdee07/gen_provinces.py`
|
||
|
||
详见 [docs/plans/T1-1-crowd-db-setup.md](../../docs/plans/T1-1-crowd-db-setup.md)
|