24 citations · 28 across the 3 of their papers we have counts for
3 papers
cs.SI2023★ 4 cited
Significant-attributed Community Search in Heterogeneous Information Networks
Yanghao Liu, Fangda Guo, Bingbing Xu +3
Community search is a personalized community discovery problem aimed at finding densely-connected subgraphs containing the query vertex. In particular, the search for communities w…
cs.AI2023
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning
Boshen Shi, Yongqing Wang, Fangda Guo +3
Graph domain adaptation models are widely adopted in cross-network learning tasks, with the aim of transferring labeling or structural knowledge. Currently, there mainly exist two…
cs.DB2021★ 24 cited
Multi-attributed Community Search in Road-social Networks
Fangda Guo, Ye Yuan, Guoren Wang +2
Given a location-based social network, how to find the communities that are highly relevant to query users and have top overall scores in multiple attributes according to user pref…