抖音的核心技术是人工智能推荐引擎。人工智能推荐引擎是一种系统,该系统能够基于用户在某个内容上的评分或偏好设置来推荐信息。
以视频平台为例,为了做出精确的推荐,推荐引擎需要电影的类型、概要、演员和导演等各方面的数据、用户的观影记录,以及与该用户具有相似观影习惯的一个庞大的用户群的所有数据,还要考虑评论、社交平台上的留言、甚至屏幕上显示何种语言等等因素。
数据量如此巨大,因此需要大量的内存和存储来处理这些工作负载。
The core technology of Tik Tok is the AI recommendation engine. The AI recommendation engine is a system that can recommend information based on the user's rating or preference settings on a certain content.
Take the video platform as an example. In order to make accurate recommendations, the recommendation engine needs data on the type, synopsis, actors and directors of the movie, the user's viewing history, and all the data of a large user base with similar viewing habits as the user. It also needs to consider comments, messages on social platforms, and even what language is displayed on the screen.
With such a huge amount of data, a large amount of memory and storage is required to handle these workloads.
TikTok architecture technical aspects: Spring+multithreading+algorithms+MySQL+Dubbo+HR (Java position)