Shohei Matsugu

2 accepted papers

2024

Efficient Correlated Subgraph Searches for AI-powered Drug Discovery

Hiroaki Shiokawa, Yuma Naoi, Shohei Matsugu

IJCAI 2024poster

Correlated subgraph searches (CSSs) are essential building blocks for AI-powered drug discovery. Given a query molecule modeled as a graph, CSS finds top-k molecules correlated to the query in a database. However, the cost increases exponentially with the molecule size. Herein we present Corgi, a fr…

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2023

Uncovering the Largest Community in Social Networks at Scale

Shohei Matsugu, Yasuhiro Fujiwara, Hiroaki Shiokawa

IJCAI 2023poster

The Maximum k-Plex Search (MPS) can find the largest k-plex, which is a generalization of the largest clique. Although MPS is commonly used in AI to effectively discover real-world communities of social networks, existing MPS algorithms suffer from high computational costs because they iteratively…

Cited by 9 Source ↗PDF ↗Scholar ↗