 Название: Graph Data Mining: Algorithm, Security and Application
Автор: Qi Xuan, Zhongyuan Ruan, Yong Min
Издательство: Springer
Год: 2021
Страниц: 256
Язык: английский
Формат: pdf (true), epub
Размер: 42.0 MB
Graph data is powerful, thanks to its ability to model arbitrary relationship between objects and is encountered in a range of real-world applications in fields such as bioinformatics, traffic network, scientific collaboration, world wide web and social networks. Graph data mining is used to discover useful information and knowledge from graph data. The complications of nodes, links and the semi-structure form present challenges in terms of the computation tasks, e.g., node classification, link prediction, and graph classification. In this context, various advanced techniques, including graph embedding and graph neural networks, have recently been proposed to improve the performance of graph data mining.
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Graph Data Mining: Algorithm, Security and Application (Big Data Management) 
