Dynamic hypergraph embedding onto concentric hypersphere manifold intended for effective visualization

Applied Network Science

Research

Shuta Ito¹  Takayasu Fushimi¹ 

[1] School of Computer Science, Tokyo University of Technology, 1404-1 Katakura-machi, 192–0982, Hachioji-City, Tokyo, Japan;

关键词: ;   

DOI  :  10.1007/s41109-023-00568-1

 received in 2023-03-12, accepted in 2023-06-27,  发布年份 2023

来源: Springer

【 摘 要 】

Hypergraph is a graph structure that can efficiently express the relationship of multiple nodes and has attracted attention in recent years. As with normal graphs, the structure changes every moment, and it is an important research topic in graph mining to capture structural changes. Many existing graph embedding methods focus on prediction tasks, and few focus on the visualization of structural changes. In this study, we aim to output embeddings for effective visualization in terms of spatial efficiency, node classification accuracy, graph structure maintenance, computational efficiency, and structural change detection performance. Our proposed method gets inspired by modularity maximization, quantifies connection strength between hypernodes and hyperedges, and embeds hypernodes on the surface of concentric spheres with a radius equal to the timestep, where a spherical surface has a wide area in the middle range. These devices are expected to correspond to the following two characteristics: (1) a graph has more node pairs whose distances are middle-range than short- and long-range; (2) a growing graph generally has an increasing number of nodes. Evaluation experiments using multiple real hypergraphs show that the proposed method is superior to existing visualization methods in the abovementioned terms.

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

41116_2023_38_Article_IEq110.gif

41116_2023_38_Article_IEq109.gif

41116_2023_38_Article_IEq108.gif

41116_2023_38_Article_IEq107.gif

41116_2023_38_Article_IEq106.gif

41116_2023_38_Article_IEq105.gif

41116_2023_38_Article_IEq104.gif

41116_2023_38_Article_IEq103.gif

41116_2023_38_Article_IEq102.gif

41116_2023_38_Article_IEq101.gif

41116_2023_38_Article_IEq100.gif

41116_2023_38_Article_IEq99.gif

41116_2023_38_Article_IEq98.gif

41116_2023_38_Article_IEq96.gif

41116_2023_38_Article_IEq95.gif

41116_2023_38_Article_IEq94.gif

Fig. 1

41116_2023_38_Article_IEq92.gif

41116_2023_38_Article_IEq91.gif

41116_2023_38_Article_IEq90.gif

41116_2023_38_Article_IEq89.gif

41116_2023_38_Article_IEq87.gif

41116_2023_38_Article_IEq86.gif

41116_2023_38_Article_IEq85.gif

41116_2023_38_Article_IEq84.gif

41116_2023_38_Article_IEq83.gif

41116_2023_38_Article_IEq82.gif

41116_2023_38_Article_IEq81.gif

41116_2023_38_Article_IEq80.gif

41116_2023_38_Article_IEq78.gif

41116_2023_38_Article_IEq77.gif

41116_2023_38_Article_IEq76.gif

41116_2023_38_Article_IEq75.gif

41116_2023_38_Article_IEq73.gif

41116_2023_38_Article_IEq72.gif

41116_2023_38_Article_IEq71.gif

41116_2023_38_Article_IEq70.gif

41116_2023_38_Article_IEq68.gif

Fig. 4

41116_2023_38_Article_IEq66.gif

41116_2023_38_Article_IEq65.gif

41116_2023_38_Article_IEq64.gif

41116_2023_38_Article_IEq63.gif

13065_2023_981_Figaa_HTML.gif

41116_2023_38_Article_IEq62.gif

41116_2023_38_Article_IEq61.gif

41116_2023_38_Article_IEq60.gif

41116_2023_38_Article_IEq59.gif

41116_2023_38_Article_IEq58.gif

41116_2023_38_Article_IEq57.gif

41116_2023_38_Article_IEq56.gif

41116_2023_38_Article_IEq55.gif

Fig. 3

41116_2023_38_Article_IEq53.gif

41116_2023_38_Article_IEq52.gif

41116_2023_38_Article_IEq51.gif

41116_2023_38_Article_IEq49.gif

41116_2023_38_Article_IEq48.gif

41116_2023_38_Article_IEq47.gif

41116_2023_38_Article_IEq46.gif

41116_2023_38_Article_IEq45.gif

41116_2023_38_Article_IEq44.gif

41116_2023_38_Article_IEq43.gif

41116_2023_38_Article_IEq42.gif

41116_2023_38_Article_IEq40.gif

41116_2023_38_Article_IEq39.gif

41116_2023_38_Article_IEq38.gif

41116_2023_38_Article_IEq37.gif

41116_2023_38_Article_IEq36.gif

41116_2023_38_Article_IEq34.gif

41116_2023_38_Article_IEq33.gif

41116_2023_38_Article_IEq31.gif

41116_2023_38_Article_IEq30.gif

41116_2023_38_Article_IEq28.gif

41116_2023_38_Article_IEq27.gif

12888_2023_4982_Article_IEq6.gif

12888_2023_4982_Article_IEq5.gif

12888_2023_4982_Article_IEq2.gif

12888_2023_4982_Article_IEq4.gif

12888_2023_4982_Article_IEq1.gif

41116_2023_38_Article_IEq20.gif

41116_2023_38_Article_IEq19.gif

41116_2023_38_Article_IEq18.gif

41116_2023_38_Article_IEq17.gif

41116_2023_38_Article_IEq16.gif

40798_2023_605_Article_IEq1.gif

Fig. 4

Fig. 1

Fig. 6

Fig. 1

Fig. 13

Fig. 3

Fig. 3

Fig. 11

Fig. 8

Fig. 10

Fig. 1

Fig. 10

Fig. 9

Fig. 1

42492_2023_141_Article_IEq65.gif

Fig. 3

Fig. 4

Fig. 20

Fig. 2

Fig. 19

Fig. 4

Fig. 18

Fig. 6

Fig. 8

Fig. 1

Fig. 7

Fig. 8

Fig. 17

Fig. 3

Fig. 16

Fig. 15

Fig. 2

Fig. 14

Fig. 3

Fig. 13

Fig. 12

Fig. 11

Fig. 3

Fig. 1

Fig. 10

Fig. 9

Fig. 3

Fig. 1

Fig. 4

Fig. 1

Fig. 2

Fig. 8

Fig. 2

Fig. 5

41239_2023_389_Article_IEq68.gif