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Author

Shengxin Liu

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Open access Sep 2026

Efficient Querying of Maximum Connectivity-Based Quasi-Cliques in Large Graphs

Structural graph queries involving connectivity constraints are fundamental primitives in modern data management and analytics. Compared with degree- and edge-based variants, connectivity-based γ-quasi-cliques (γ-CQCs) impose stronger structural constraints and fault tolerance, where robustness is measured by vertex...

Yang Liu, He-Jiao Huang, Kai-Qiang Yu et al. · 0 citations
Book Open access Aug 2026

HURST: Heterogeneity-Adaptive Urban Foundation Models for Spatiotemporal Prediction via Self-Partitional Mixture-of-Spatial-Experts

HURST is a Heterogeneity-Adaptive URban Foundation Model for Spatio-Temporal Prediction that is capable of capturing the spatial pattern of heterogeneity underlying the urban setting to enhance the UFM's performance and presents two key technical innovations.

Zirui Zhou, Xun Zhou, Kanyu Bao et al. · 0 citations
Conference May 2026

Listing Minimal Cores in Large Real-World Graphs

Cohesive subgraph mining is a fundamental task in graph data analytics. We re-visit the problem of listing all minimal $k$-cores, where a $k$-core is a subgraph in which every vertex has degree at least $k$, and minimality requires that no proper subset remains a $k$-core. Existing methods are computationally prohibiti...

Yukai Sun, Kaiqiang Yu, Shengxin Liu et al. · 0 citations
#edge computing Sep 2026

Efficient Minimum $k$-Truss Search: A Decomposition-Based Approach

Cohesive subgraph mining has been extensively studied and finds numerous graph mining applications such as link farm identification, community detection, and product recommendation. Among various cohesive subgraph structures, the <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k...

Qifan Zhang, Yang Liu, Kaiqiang Yu et al. · 0 citations

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