# MovieTaster-Open

**Repository Path**: mirrors_sudoconf/MovieTaster-Open

## Basic Information

- **Project Name**: MovieTaster-Open
- **Description**: 使用Item2Vec做电影推荐
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-26
- **Last Updated**: 2025-11-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# MovieTaster-Open
使用Item2Vec做电影推荐

[Demo>](https://movietaster.leanapp.cn/movies/)

![MovieTaster-demo-输入多个电影](http://7xkdra.com1.z0.glb.clouddn.com/image/blog/MovieTaster/movie_rec_multi.png)

[原理详情请参考>](http://lujiaying.github.io/2017/08/15/MovieTaster-%E4%BD%BF%E7%94%A8Item2Vec%E5%81%9A%E7%94%B5%E5%BD%B1%E6%8E%A8%E8%8D%90/)

## 目录结构
- datas:  存放语料
- models: 存放电影向量
- utils: 工具类，包括生成推荐电影列表等


## 使用说明

0. 在根目录下载并编译[fasttext](https://github.com/facebookresearch/fastText)

1. 处理语料。结束后将在```./datas/```下生成fasttext所需要的格式

```
$ cd datas && tar -xzvf corpus.tar.gz
$ cd ..
$ python utils/process.py
```

2. 参考```./run.sh```中生成词向量的参数配置，任选一个。

```
$ ./fasttext skipgram -input ./datas/doulist_0804_09.movie_id -output ./models/fasttext_model_0804_09_skipgram -minCount 5 -epoch 50 -neg 100
```

3. 查看模型效果

```
$ python utils/eval.py
movie_name_id_dict is 130206 from [./datas/doulist_0804_09.json]
movie_name_id_dict is 130206 from [./datas/doulist_0804_09.json]
movie_id_name_dict is 130206 from [./datas/doulist_0804_09.json]
[2017-08-18 07:52:53,579][pid:22831] eval.topk_like: INFO: [1210]小时代 top 5 likes:
[2017-08-18 07:52:54,149][pid:22831] eval.topk_like: INFO: [2396]小时代2：青木时代 0.820323
[2017-08-18 07:52:54,149][pid:22831] eval.topk_like: INFO: [3387]分手合约 0.606063
[2017-08-18 07:52:54,150][pid:22831] eval.topk_like: INFO: [4087]不二神探 0.604207
[2017-08-18 07:52:54,150][pid:22831] eval.topk_like: INFO: [3839]天台爱情 0.601879
[2017-08-18 07:52:54,150][pid:22831] eval.topk_like: INFO: [821]致我们终将逝去的青春 0.600836
[2017-08-18 07:52:54,150][pid:22831] eval.topk_like: INFO: [144]倩女幽魂 top 5 likes:
[2017-08-18 07:52:54,690][pid:22831] eval.topk_like: INFO: [2719]倩女幽魂3：道道道 0.685621
[2017-08-18 07:52:54,690][pid:22831] eval.topk_like: INFO: [1812]倩女幽魂2：人间道 0.681594
[2017-08-18 07:52:54,691][pid:22831] eval.topk_like: INFO: [466]胭脂扣 0.678032
[2017-08-18 07:52:54,691][pid:22831] eval.topk_like: INFO: [261]青蛇 0.671541
[2017-08-18 07:52:54,692][pid:22831] eval.topk_like: INFO: [156]东邪西毒 0.664057
[2017-08-18 07:52:54,692][pid:22831] eval.topk_like: INFO: [2602]悟空传 top 5 likes:
[2017-08-18 07:52:55,253][pid:22831] eval.topk_like: INFO: [5648]闪光少女 0.671337
[2017-08-18 07:52:55,253][pid:22831] eval.topk_like: INFO: [2189]绣春刀II：修罗战场 0.646861
[2017-08-18 07:52:55,254][pid:22831] eval.topk_like: INFO: [8297]逆时营救 0.634753
[2017-08-18 07:52:55,254][pid:22831] eval.topk_like: INFO: [12571]京城81号Ⅱ 0.625549
[2017-08-18 07:52:55,254][pid:22831] eval.topk_like: INFO: [10545]父子雄兵 0.623032
[2017-08-18 07:52:55,254][pid:22831] eval.topk_like: INFO: [56]美国往事 top 5 likes:
[2017-08-18 07:52:55,789][pid:22831] eval.topk_like: INFO: [18]天堂电影院 0.756449
[2017-08-18 07:52:55,790][pid:22831] eval.topk_like: INFO: [14]辛德勒的名单 0.737502
[2017-08-18 07:52:55,790][pid:22831] eval.topk_like: INFO: [17]教父 0.735216
[2017-08-18 07:52:55,790][pid:22831] eval.topk_like: INFO: [69]闻香识女人 0.734119
[2017-08-18 07:52:55,790][pid:22831] eval.topk_like: INFO: [42]西西里的美丽传说 0.732334
[2017-08-18 07:52:55,791][pid:22831] eval.topk_like: INFO: [2644]战狼2 top 5 likes:
[2017-08-18 07:52:56,346][pid:22831] eval.topk_like: INFO: [1456]大护法 0.612700
[2017-08-18 07:52:56,347][pid:22831] eval.topk_like: INFO: [2107]战狼 0.580637
[2017-08-18 07:52:56,347][pid:22831] eval.topk_like: INFO: [2602]悟空传 0.580365
[2017-08-18 07:52:56,347][pid:22831] eval.topk_like: INFO: [9941]建军大业 0.575422
[2017-08-18 07:52:56,347][pid:22831] eval.topk_like: INFO: [19040]阿唐奇遇 0.573613
```