用机器学习和因果推理改进Instagram的通知管理
- We’re sharing how Meta is applying statistics and machine learning (ML) to improve notification personalization and management on Instagram – particularly on daily digest push notifications.
- 我们将分享Meta如何应用统计学和机器学习（ML）来改善Instagram上的通知个性化和管理--特别是在每日摘要推送通知上。
- By using causal inference and ML to identify highly active users who are likely to see more content organically, we have been able to reduce the number of notifications sent while also improving overall user experience.
- 通过使用因果推理和ML来识别可能看到更多有机内容的高活跃用户，我们已经能够减少发送的通知数量，同时也改善了整体用户体验。
On Instagram, notifications play an important role in providing efficient communication channels between Instagram and our users. As the types of notifications have increased, a need has arisen to provide people with personalized notification experiences to help avoid them receiving excess notifications or ones they may not find to be important.
在Instagram上，通知在为Instagram和我们的用户提供有效的沟通渠道方面发挥着重要作用。随着通知类型的增加，出现了为人们提供个性化的通知体验的需求，以帮助避免他们收到过多的通知或他们可能认为不重要的通知。
At Meta, we have been applying statistics and machine learning (ML) for notification personalization and management on Instagram. Today, we would like to share an example of how we used causal inference and ML to control sending for daily digest push notifications.
在Meta，我们一直在应用统计学和机器学习（ML）来实现Instagram的通知个性化和管理。今天，我们想分享一个例子，说明我们如何使用因果推理和ML来控制每日摘要推送通知的发送。
Moving beyond click-through rate models
超越点击率模式
A daily digest push notification about stories is a type of notification that lists a digest of stories that are shared and ready for someone to view. When such a notification is delivered to someone’s device, they may click on the notification to view the content. Traditionally, an ML model called a click-through rate (CTR) model is used to predict how likely someone is to click on a notification. CTR models have been working well in many applications across the industry. The predicted click probability is used as a proxy to indicate the notification’s quality to the user. If the predicted click probability is too low, the notification will...