- Добавил: Maurix
- Дата: 28-03-2021, 18:33
- Комментариев: 0

Автор: Cheng Yang
Издательство: Morgan and Claypool
Год: 2021
Формат: PDF
Страниц: 244
Размер: 10 Mb
Язык: English
Many machine learning algorithms require real-valued feature vectors of data instances as inputs. By projecting data into vector spaces, representation learning techniques have achieved promising performance in many areas such as computer vision and natural language processing. There is also a need to learn representations for discrete relational data, namely networks or graphs. Network Embedding (NE) aims at learning vector representations for each node or vertex in a network to encode the topologic structure. Due to its convincing performance and efficiency, NE has been widely applied in many network applications such as node classification and link prediction.