Titlebook: Hypergraph Computation; Qionghai Dai,Yue Gao Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and The Author(s) 2023 Hypergraph.Hypergraph

填料

978-981-99-0187-6The Editor(s) (if applicable) and The Author(s) 2023

palette

Hypergraph Computation978-981-99-0185-2Series ISSN 2365-3051 Series E-ISSN 2365-306X

苦笑

rheumatism

誘惑

LUDE

Artificial Intelligence: Foundations, Theory, and Algorithmshttp://image.papertrans.cn/h/image/430640.jpg

預(yù)測

Hypergraph Structure Evolution,tion of the static mechanism when confronting random and increasing data scenarios. In this chapter, we introduce dynamic hypergraph structure evolution methods, including both hypergraph component optimization and hypergraph structure optimization. Finally, we briefly introduce the incremental learning method on growing data.

conifer

Hypergraph Computation for Social Media Analysis,e used in such analysis. In this chapter, we introduce three typical applications of hypergraph computation, i.e., recommender system, sentiment analysis, and emotion recognition, from which hypergraph computation has shown great value on social media analysis.

不公開

Hypergraph Computation for Computer Vision,and solve visual problems by hypergraph computation. For example, in social image retrieval, hypergraphs are used to model the high-order relationship among social images based on both visual and textual information, which is the high-order modeling of elements within samples.

TRACE

Hypergraph Computation Paradigms, subject is a vertex in the hypergraph. Hypergraph structure computation is to conduct hypergraph structure prediction, which aims to find the connections among vertices. This chapter is a general introduction of hypergraph computation paradigms to show how to formulate the task in the hypergraph computation framework.