1 citations · 1 across the 4 of their papers we have counts for
5 papers
Pre-trained Prompt-driven Semi-supervised Local Community Detection
Li Ni, Hengkai Xu, Lin Mu +2
Semi-supervised local community detection aims to leverage known communities to detect the community containing a given node. Although existing semi-supervised local community dete…
Community Search in Time-dependent Road-social Attributed Networks
Li Ni, Hengkai Xu, Lin Mu +2
Real-world networks often involve both keywords and locations, along with travel time variations between locations due to traffic conditions. However, most existing cohesive subgra…
Community and hyperedge inference in multiple hypergraphs
Li Ni, Ziqi Deng, Lin Mu +3
Hypergraphs, capable of representing high-order interactions via hyperedges, have become a powerful tool for modeling real-world biological and social systems. Inherent relationshi…
Affiliation-based Local Community Detection across Multiple Networks
Li Ni, Zhou Xie, Yiwen Zhang +2
Real-world networks are often constructed from different sources or domains, including various types of entities and diverse relationships between networks, thus forming multi-doma…
ComGPT: Detecting Local Community Structure with Large Language Models
Li Ni, Haowen Shen, Lin Mu +2
Large Language Models (LLMs), like GPT-3.5-turbo, have demonstrated the ability to understand graph structures and have achieved excellent performance in various graph reasoning ta…