电影推荐

简介

本文使用小笨羊推荐应用和服务，对MovieLens数据，端到端的搭建完整的电影推荐网站。

演示网址: https://app.aboutdata.top/movie/#/movie

小笨羊网址: https://xiaobenyang.com/

如有问题，请联系小笨羊微信:

具体内容如下，

首页，包括热门排行榜和猜你喜欢，

电影信息页，包含电影信息，"电影评分详情"和"看了又看"(推荐相似电影)。

按照电影平均打分，查询高分电影

搭建一套完整的电影推荐网站，需要下面功能，

模型	功能
排行榜	热门电影排行榜
训练U2I模型	用于用户登录后的首页推荐
训练I2I模型	用户进入电影页面之后推荐
查询模型1	按打分查询电影
查询模型2	按电影查询用户电影评分.

第一步，准备数据

MovieLens是推荐系统的经典数据集，包含用户对电影的打分，用户信息，电影信息等数据。

第一步，准备三个数据，分别是用户表，物品表(电影)，行为表(用户对电影的打分)

1. 用户表

用户表存放的是用户的相关信息，包括性别、年龄、职业。

列名	类型	描述	备注
user_id	long	用户ID
age	int	年龄	数值特征
gender	string	性别	类别特征: M代表男性，F代表女性
occupation	string	职业	类别特征：20中种职业
zip_code	string	邮政编码	‌前两位数字‌：代表省级行政区，中间两位数字‌：代表地级行政区。可以用邮政编码抽取处理特征。同样还有地址抽取，ip抽取等和位置相关的特征

1.1. 使用AlinkLab查看数据

1.2. 使用AlinkLab查看统计信息

2. 物品表

物品表存放的是电影的相关信息，即电影id、电影标题、电影类型

列名	类型	描述
movie_id	long	电影ID
title	string	电影名称，语义进入精排模型
release_date	string	发布日期
video_release_date	string	视频发布日期
imdb_url	string	链接
其他列是影片类型	int	OneHot之后的数据：如果是此类影片值是1，不是值是0。不需要再进行数据处理，直接进入模型即可。

2.1. 使用AlinkLab查看数据

2.2. 使用AlinkLab查看统计信息

3. 行为表

行为表是打分数据，包含用户id、电影id、该用户对此电影的评分、时间。

列名	类型	描述
user_id	long	用户ID
movie_id	long	电影ID
rating	float	打分
ts	long	打分时间，以秒为单位的时间戳；可用来构造用户的序列行为特征，即用户最近n次的打分行为。

3.1. 使用AlinkLab查看数据

3.2. 使用AlinkLab查看统计信息

第二步，训练模型

一共需要如下五个模型：

模型	描述
排行榜	热门电影排行榜
训练U2I模型	用于用户登录后的首页推荐
训练I2I模型	用户进入电影页面之后推荐
查询模型1	按打分查询电影
查询模型2	按电影查询用户电影评分.

1. 排行榜

一般电影推荐网页的首页，会有热门电影排行榜和猜你喜欢两部分。榜单可以非常丰富，按照类别的榜单，按照性别的榜单，按照地域的榜单，不同类别之间的对比等等。

下图例子中的右侧是按照播放次数倒排的电影排行榜。

可以直接用1.1导入教程示例查看使用，也可以按照1.2的步骤直接训练模型。

1.1. 导入任务

可以直接导入教程示例查看使用，也可以按照1.2的步骤训练模型。

任务帖子链接：https://xiaobenyang.com/discuss-post?id=134

点击"导入"，将任务导入自己的项目直接查看。

1.2. 训练步骤

使用排行榜应用训练模型

计算表是行为表(电影打分表), 附加表是物品表(电影信息表)。计算出打分最多的10个电影, 结果包括电影ID，电影名称和点评次数。

填写参数

参数介绍：

参数	取值	介绍
主体列	movie_id	按照电影ID做汇总
计算列	rating	计算打分(rating)的次数(count)，用于排名
统计类型	count	计算打分(rating)的次数(count)，用于排名
是否降序	是	排名按照降序排序
个数	10	返回排名前10的数据
附加列	["title"]	除了返回统计量之外，也返回title(电影标题列)
预测服务名称	应用示例/电影/排行榜B

填写好参数之后，点击运行。
运行成功之后，查看对应服务，点击"预测演示"测试。并查询对应的服务ID。

1.3. API调用

以Vue为例，

var axios = require('axios')
  
//设置小笨羊API访问URL
axios.defaults.baseURL = 'https://xiaobenyang.com/pred'
  
// 设置访问ApiKey, 在管理页面查询https://xiaobenyang.com/calc?func=LabPage&proc=ListMyApikey
axios.defaults.headers.common['APIKEY'] = '*'

axios.post(null, {
        'predServId': '40',
        'clause': ''
})

参数介绍

参数	描述	介绍
predServId	服务ID	在服务列表里查询
clause	表达式	''是所有数据

1.4. 请求结果

[
  {
    "pred": "[{\"rank\":1,\"movie_id\":50,\"title\":\"Star Wars (1977)\",\"rating_count\":583.0},{\"rank\":2,\"movie_id\":258,\"title\":\"Contact (1997)\",\"rating_count\":509.0},{\"rank\":3,\"movie_id\":100,\"title\":\"Fargo (1996)\",\"rating_count\":508.0},{\"rank\":4,\"movie_id\":181,\"title\":\"Return of the Jedi (1983)\",\"rating_count\":507.0},{\"rank\":5,\"movie_id\":294,\"title\":\"Liar Liar (1997)\",\"rating_count\":485.0},{\"rank\":6,\"movie_id\":286,\"title\":\"English Patient, The (1996)\",\"rating_count\":481.0},{\"rank\":7,\"movie_id\":288,\"title\":\"Scream (1996)\",\"rating_count\":478.0},{\"rank\":8,\"movie_id\":1,\"title\":\"Toy Story (1995)\",\"rating_count\":452.0},{\"rank\":9,\"movie_id\":300,\"title\":\"Air Force One (1997)\",\"rating_count\":431.0},{\"rank\":10,\"movie_id\":121,\"title\":\"Independence Day (ID4) (1996)\",\"rating_count\":429.0}]",
    "__alink_lookup_id__": 0
  }
]

2. 首页推荐(猜你喜欢)

首页推荐，也就是猜你喜欢，用来推荐用户感兴趣的电影。使用热门召回和ALS召回，解决冷启动和个性化推荐的需求。这部分用户上来就会看到，非常重要。下图左侧是猜你喜欢的示例，

2.1. 导入任务

可以直接导入教程示例查看使用，也可以按照1.2的步骤训练模型。

任务帖子链接：https://xiaobenyang.com/discuss-post?id=133

点击"导入"，将任务导入自己的项目查看。

2.2. 训练和部署

这里使用推荐系统应用训练模型，包含召回和精排

数据

召回训练数据是行为表(电影打分表)
精排训练数据是行为表(电影打分表), 标签设置为"rating>=4"(打分大于等于4是正样本，其他是负样本)
用户数据是用户表
物品数据是电影表

这里使用了同一个行为表作为召回和精排的训练数据，实际应用中召回训练数据和精排训练数据是不同的，需要根据业务情况精心设计负样本。召回一般用随机采样全部行为作为负样本，精排一般是用曝光之后没有点击(评分)作为负样本。

填写参数，确定召回和排序的方式
运行和部署

2.3. API调用

以Vue为例，设置user_id

var axios = require('axios')
  
// 设置小笨羊API访问URL
axios.defaults.baseURL = 'https://xiaobenyang.com/pred'
  
// 设置访问ApiKey, 在管理页面查询https://xiaobenyang.com/calc?func=LabPage&proc=ListMyApikey
axios.defaults.headers.common['APIKEY'] = '*'

axios.post(null, {
        'predServId': '39',
        'user_id': userId
})

参数介绍

参数	描述	介绍
predServId	服务ID	在服务列表里查询
user_id	用户ID

2.4. 请求结果

[
  {
    "score": 0.6648386815137506,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Usual%20Suspects,%20The%20(1995)",
    "movie_id": 12,
    "title": "Usual Suspects, The (1995)"
  },
  {
    "score": 0.6563065434252864,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Star%20Wars%20(1977)",
    "movie_id": 50,
    "title": "Star Wars (1977)"
  },
  {
    "score": 0.6282466883685336,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Empire%20Strikes%20Back,%20The%20(1980)",
    "movie_id": 172,
    "title": "Empire Strikes Back, The (1980)"
  },
  {
    "score": 0.6280127697511231,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Princess%20Bride,%20The%20(1987)",
    "movie_id": 173,
    "title": "Princess Bride, The (1987)"
  },
  {
    "score": 0.6277787911507777,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Raiders%20of%20the%20Lost%20Ark%20(1981)",
    "movie_id": 174,
    "title": "Raiders of the Lost Ark (1981)"
  },
  {
    "score": 0.6256703001101849,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Alien%20(1979)",
    "movie_id": 183,
    "title": "Alien (1979)"
  },
  {
    "score": 0.33804561940672695,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Faust%20%281994%29",
    "movie_id": 1367,
    "title": "Faust (1994)"
  },
  {
    "score": 0.3168786077333079,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?imdb-title-118764",
    "movie_id": 1463,
    "title": "Boys, Les (1997)"
  },
  {
    "score": 0.30891279055970633,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/M/title-exact?Santa%20with%20Muscles%20(1996)",
    "movie_id": 1500,
    "title": "Santa with Muscles (1996)"
  },
  {
    "score": 0.27920416768385836,
    "user_id": 22,
    "imdb_url": "http://us.imdb.com/Title?Angel+Baby+(1995/I)",
    "movie_id": 1643,
    "title": "Angel Baby (1995)"
  }
]

3. 进入电影详情页，特别推荐电影

指定电影ID, 推荐相似的电影

3.1. 导入任务

可以直接导入教程示例查看使用，也可以按照1.2的步骤训练模型。

任务帖子链接：https://xiaobenyang.com/discuss-post?id=135

点击"导入"，将任务导入自己的项目查看。

3.2. 训练和部署

使用I2I应用训练模型，数据表是行为表(电影打分表), 附加表是物品表(电影信息表)。给定一个电影，推荐相似的电影列表。
填写参数

运行和部署

3.3. API调用

以Vue为例，设置movie_id, 推荐相似电影列表，并关联电影信息

var axios = require('axios')
  
//设置小笨羊API访问URL
axios.defaults.baseURL = 'https://xiaobenyang.com/pred'
  
// 设置访问ApiKey, 在管理页面查询https://xiaobenyang.com/calc?func=LabPage&proc=ListMyApikey
axios.defaults.headers.common['APIKEY'] = '*'

axios.post(null, {
            'predServId': '43',
            "movie_id": this.movieId
})

3.4. 请求结果

{
    "recom": "[{\"score\":3.739997579363967,\"movie_id\":173,\"title\":\"Princess Bride, The (1987)\"},{\"score\":3.715278204571951,\"movie_id\":169,\"title\":\"Wrong Trousers, The (1993)\"},{\"score\":3.69654889421144,\"movie_id\":1169,\"title\":\"Fresh (1994)\"},{\"score\":3.666642062382044,\"movie_id\":64,\"title\":\"Shawshank Redemption, The (1994)\"},{\"score\":3.633121867118959,\"movie_id\":114,\"title\":\"Wallace & Gromit: The Best of Aardman Animation (1996)\"},{\"score\":3.632576019023612,\"movie_id\":318,\"title\":\"Schindler's List (1993)\"},{\"score\":3.6205990685449594,\"movie_id\":174,\"title\":\"Raiders of the Lost Ark (1981)\"},{\"score\":3.6162683197891154,\"movie_id\":408,\"title\":\"Close Shave, A (1995)\"},{\"score\":3.604905994911123,\"movie_id\":50,\"title\":\"Star Wars (1977)\"},{\"score\":3.5979400813672933,\"movie_id\":613,\"title\":\"My Man Godfrey (1936)\"}]",
    "movie_id": 2
}

4. 按打分查询模型

这是"统计和查询"模型, 查询电影所有的评分记录

4.1. 导入任务

可以直接导入教程示例查看使用，也可以按照1.2的步骤训练模型。

任务帖子链接：https://xiaobenyang.com/discuss-post?id=132

点击"导入"，将任务导入自己的项目查看。

4.2. 训练和部署

使用"统计和查询"应用，待统计表是行为表(电影评分表)，计算每个电影的评分；附加特征表是物品表(电影信息表), 用于关联物品特征; 结果统计表的统计值，并关联附加特征表的特征。

填写参数

4.3. API调用

指定电影平均分和打分次数, 搜索所有满足条件的电影，并关联电影信息（电影名称和电影类型)

var axios = require('axios')
  
//设置小笨羊API访问URL
axios.defaults.baseURL = 'https://xiaobenyang.com/pred'
  
// 设置访问ApiKey, 在管理页面查询https://xiaobenyang.com/calc?func=LabPage&proc=ListMyApikey
axios.defaults.headers.common['APIKEY'] = '*'

axios.post(null, {
    'predServId': '41',
    'clause': 'movie_id=' + this.movieId
})

4.4. 请求结果

{
    "clause": "movie_id=2",
    "pred": "[{\"user_id\":5,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875636053},{\"user_id\":268,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875744173},{\"user_id\":276,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":874792436},{\"user_id\":217,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":889069782},{\"user_id\":87,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879876074},{\"user_id\":250,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878090414},{\"user_id\":201,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":884112487},{\"user_id\":64,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":889737609},{\"user_id\":13,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882397650},{\"user_id\":95,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888955909},{\"user_id\":213,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878955914},{\"user_id\":373,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":877100416},{\"user_id\":293,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888907101},{\"user_id\":193,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":890860198},{\"user_id\":363,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891495809},{\"user_id\":256,\"rating\":5.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882164480},{\"user_id\":200,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":884130046},{\"user_id\":207,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":877822770},{\"user_id\":393,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":887746206},{\"user_id\":222,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878183837},{\"user_id\":399,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882512708},{\"user_id\":301,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882076587},{\"user_id\":379,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":880525540},{\"user_id\":387,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":886483195},{\"user_id\":92,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875653699},{\"user_id\":450,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882474001},{\"user_id\":303,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879467191},{\"user_id\":178,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882827375},{\"user_id\":83,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":881971771},{\"user_id\":407,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875553509},{\"user_id\":327,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":887820385},{\"user_id\":1,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":876893171},{\"user_id\":325,\"rating\":1.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891478772},{\"user_id\":455,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879111786},{\"user_id\":30,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875061066},{\"user_id\":320,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":884749281},{\"user_id\":405,\"rating\":1.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":885547953},{\"user_id\":466,\"rating\":1.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":890284819},{\"user_id\":536,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882360227},{\"user_id\":346,\"rating\":5.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875263473},{\"user_id\":197,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891409981},{\"user_id\":72,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":880037376},{\"user_id\":110,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":886988536},{\"user_id\":600,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888451908},{\"user_id\":622,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882671363},{\"user_id\":551,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":892784780},{\"user_id\":618,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891309091},{\"user_id\":495,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye 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(1995)\",\"ts\":892790676},{\"user_id\":709,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879848511},{\"user_id\":416,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":886317115},{\"user_id\":561,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":885809752},{\"user_id\":292,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":881105778},{\"user_id\":305,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":886324580},{\"user_id\":521,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":886063310},{\"user_id\":249,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879641284},{\"user_id\":727,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye 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(1995)\",\"ts\":888801522},{\"user_id\":764,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":876244856},{\"user_id\":844,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":877387933},{\"user_id\":632,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879459505},{\"user_id\":671,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":884035892},{\"user_id\":943,\"rating\":5.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888639953},{\"user_id\":267,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878972463},{\"user_id\":826,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":885690713},{\"user_id\":650,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891381709},{\"user_id\":896,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":887160000},{\"user_id\":795,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":883252599},{\"user_id\":234,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":892335142},{\"user_id\":442,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":883390544},{\"user_id\":868,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":877112290},{\"user_id\":815,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878696355},{\"user_id\":798,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875743787},{\"user_id\":49,\"rating\":1.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888069606},{\"user_id\":807,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":892978338},{\"user_id\":886,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":876033368},{\"user_id\":889,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":880182460}]"
}

5. 按电影查询用户电影评分详情

这是"统计和查询"模型, 查询电影所有的评分记录

5.1. 导入任务

可以直接导入教程示例查看使用，也可以按照1.2的步骤训练模型。

任任务帖子链接：https://xiaobenyang.com/discuss-post?id=131

点击"导入"，将任务导入自己的项目查看。

5.2. 训练和部署

使用"统计和查询"应用，待统计表是行为表(电影评分表)，计算每个电影的评分；附加特征表是物品表(电影信息表), 用于关联物品特征; 查询表是行为表(电影评分表)，结果以查询表为左表，关联待统计表的统计值，和附加特征表的特征。

填写参数

5.3. API调用

指定电影ID, 搜索所有评分记录，并计算平均评分

var axios = require('axios')
  
//设置小笨羊API访问URL
axios.defaults.baseURL = 'https://xiaobenyang.com/pred'
  
// 设置访问ApiKey, 在管理页面查询https://xiaobenyang.com/calc?func=LabPage&proc=ListMyApikey
axios.defaults.headers.common['APIKEY'] = '*'

axios.post(null, {
          'predServId': '42',
          'clause': '__alink_avg__ >= ' + this.minAvgRating + " and " + '__alink_count__>= ' + this.minCount
})

5.4. 请求结果

{
    "clause": "movie_id=2",
    "pred": "[{\"user_id\":5,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875636053},{\"user_id\":268,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":875744173},{\"user_id\":276,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":874792436},{\"user_id\":217,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":889069782},{\"user_id\":87,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":879876074},{\"user_id\":250,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878090414},{\"user_id\":201,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":884112487},{\"user_id\":64,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":889737609},{\"user_id\":13,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":882397650},{\"user_id\":95,\"rating\":2.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888955909},{\"user_id\":213,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":878955914},{\"user_id\":373,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":877100416},{\"user_id\":293,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":888907101},{\"user_id\":193,\"rating\":3.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":890860198},{\"user_id\":363,\"rating\":4.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye (1995)\",\"ts\":891495809},{\"user_id\":256,\"rating\":5.0,\"__alink_avg__\":3.206107,\"movie_id\":2,\"title\":\"GoldenEye 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}

第三步，搭建电影网站

本示例使用Vue2, 调用第二步中部署的模型预测服务。

ALinkLab

电影推荐

简介

第一步，准备数据

1. 用户表

1.1. 使用AlinkLab查看数据

1.2. 使用AlinkLab查看统计信息

2. 物品表

2.1. 使用AlinkLab查看数据

2.2. 使用AlinkLab查看统计信息

3. 行为表

3.1. 使用AlinkLab查看数据

3.2. 使用AlinkLab查看统计信息

第二步，训练模型

1. 排行榜

1.1. 导入任务

1.2. 训练步骤

1.3. API调用

1.4. 请求结果

2. 首页推荐(猜你喜欢)

2.1. 导入任务

2.2. 训练和部署

2.3. API调用

2.4. 请求结果

3. 进入电影详情页，特别推荐电影

3.1. 导入任务

3.2. 训练和部署

3.3. API调用

3.4. 请求结果

4. 按打分查询模型

4.1. 导入任务

4.2. 训练和部署

4.3. API调用

4.4. 请求结果

5. 按电影查询用户电影评分详情

5.1. 导入任务

5.2. 训练和部署

5.3. API调用

5.4. 请求结果

第三步，搭建电影网站