How to implement intelligent recommendations and personalized push in uniapp

How to implement intelligent recommendations and personalized push in uniapp

With the rapid development of mobile Internet, users hope to get personalized information when using mobile applications. Professional and intelligent recommendation service. In the uniapp framework, we can use some common technical means to implement intelligent recommendations and personalized push functions. This article will introduce how to implement these two functions in uniapp and provide specific code examples.

1. Intelligent Recommendation Algorithm

Intelligent recommendation is a method that automatically recommends the most relevant content to users based on their behavior and preferences. Common intelligent recommendation algorithms include collaborative filtering-based algorithms, content-based algorithms and deep learning-based algorithms. In uniapp, we can use uniCloud cloud functions and databases to implement intelligent recommendation functions.

1. Create cloud function

Create a cloud function in uniCloud and name it recommend. Write the specific recommendation algorithm code in the entry function of the cloud function.

The sample code is as follows:

const uniID = require('uni-id')

exports.main = async (event, context) => { 
  const {userID} = event
  // 根据userID获取用户的历史行为数据
  const historyData = await uniID.db.collection('history').where({userID: userID}).get()
  // 根据历史行为数据进行推荐算法计算
  const recommendData = CalculateRecommend(historyData)
  return recommendData
}

function CalculateRecommend(historyData) {
  // 算法的具体实现逻辑
  // ...
  return recommendData
}

2. Call the cloud function

Call the cloud function in uniapp to complete the recommended function.

The sample code is as follows:

uniCloud.callFunction({
  name: 'recommend',
  data: {
    userID: '123456'
  },
  success: (res) => {
    console.log(res.result)
    // 对推荐结果进行处理
    // ...
  },
  fail: (err) => {
    console.log(err)
  }
})

2. Personalized push

Personalized push is to push relevant content to users based on their specific attributes or preferences. In uniapp, we can use the subscription message function of the WeChat applet to achieve personalized push.

1. Get the user's authorization to subscribe to messages

Configure the messages that need to be subscribed in app.json, and obtain the user's authorization to subscribe to messages after the user authorizes them.

The sample code is as follows:

{
  "mp-weixin": {
    "window": {
      "navigationBarTitleText": "Uni-App",
      "navigationStyle": "custom"
    },
    "permission": {
      "subscribeMsg": {
        "desc": "Uni-App需要获取你的订阅消息通知权限"
      }
    }
  }
}

2. Get the template ID of the subscription message

Create a template for the subscription message on the WeChat public platform and get the template ID.

3. Send subscription message

Call the wx.requestSubscribeMessage method in uniapp to send a subscription message to the user.

The sample code is as follows:

wx.requestSubscribeMessage({
  tmplIds: ['模板ID1', '模板ID2'],
  success: (res) => {
    if (res['模板ID1'] === 'accept') {
      // 用户同意订阅模板ID1的消息
      // 发送个性化推送
    }
    // ...
  },
  fail: (err) => {
    console.log(err)
  }
})

Through the above steps, we can implement intelligent recommendation and personalized push functions in uniapp. The calculation of the intelligent recommendation algorithm is realized through cloud functions, and the subscription message function of the WeChat applet is used to realize personalized push. The above code is only an example, and the specific implementation can be modified and optimized according to actual needs.

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