JOURNAL ARTICLE

Vertical Memristive Crossbar Array for Multilayer Graph Embedding and Analysis

Abstract

Abstract Graph data structures effectively represent objects and their relationships, enabling the modeling of complex connections in various fields. Recent work demonstrate that metal at diagonal crossbar arrays (m‐CBA) can effectively represent planar graphs. However, they are unsuitable for representing multilayer graphs having multiple relationships across different layers. Using conventional software, embedding multilayer graphs in high‐dimensional Euclidean spaces introduces significant mathematical complexity and computational burden, often resulting in information loss. This study proposes a unique graph embedding (mapping) method utilizing a fabricated vertical m‐CBA (vm‐CBA), where a custom‐built measurement system thoroughly validated its functionality. This structure directly maps multilayer graphs into a 3D vm‐CBA, accurately representing inter‐layer and intra‐layer connections. The practical link prediction and information scores across various real‐world datasets demonstrated that vm‐CBA achieved enhanced accuracy compared to conventional embeddings, even with a significantly decreased number of operations.

Keywords:
Crossbar switch Embedding Planar Diagonal Power graph analysis Euclidean geometry Graph Computer science Layer (electronics) Software Theoretical computer science Materials science Computational science Algorithm Mathematics Artificial intelligence Nanotechnology Geometry Computer graphics (images)

Metrics

2
Cited By
4.04
FWCI (Field Weighted Citation Impact)
29
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Complex Network Analysis Techniques
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Advanced Graph Neural Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
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