hyper graph 超圖
阿新 • • 發佈:2018-12-12
hyper graph 的基礎概念
超圖資料模型hypergraph data model (HDM)是知識圖的基礎(GRAKN.AI)
概念(notations):
- 超圖由非空的頂點集和超邊集組成(a hypergraph consists of a non-empty set of vertices and a set of hyperedges)
- 超邊是一組有限的頂點集合(通過它們在超邊中所扮演的特定角色來區分)(a hyperedge is a finite set of vertices (distinguishable by specific roles they play in that hyperedge))
- 超邊本身也是一個頂點,可以由其他超邊緣連線(a hyperedge is also a vertex itself and can be connected by other hyperedges)
超圖(hyper graph)的邊:超邊(hyper edge),由一個頂點集合構成,頂點數>=2(a set of vertices),如下圖:
數學上的定義
假設一個超圖H=(X,E),其中:X為頂點集合,E為邊的集合,
subhypergraph(子超圖):將一個超圖H去掉一些頂點(vertices)
其中A是X的子集
下圖來自文獻:Zhou D, Huang J. Learning with hypergraphs: clustering, classification, and embedding[C]// International Conference on Neural Information Processing Systems. MIT Press, 2006:1601-1608.