A Review of Network Representation Learning

Abstract

With the development of the technology, social software such as Facebook, Twitter, YouTube, QQ, WeChat has also achieved great development. According to the existing data, in the first quarter of 2018, WeChat’s monthly number has reached 1 billion [1]. At the same time, these large-scale nodes also carry a large amount of external information such as texts and pictures, forming a complex information network. Information networks are widely used in real life and have enormous academic and economic value. Academically, artificial intelligence, big data, deep learning and other technologies are developing rapidly. Large and complex neural networks and complex information networks urgently need to make a reasonable analysis of data [2]. In terms of application value, information networks and social networks also have a wide range of application scenarios, such as recommendation systems, community discovery and other tasks [3]. Therefore, the research and application of complex information networks is a hot issue in the field of artificial intelligence, and it is necessary to study it.