16 citations · 18 across the 5 of their papers we have counts for
5 papers
Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
Yankai Chen, Yixiang Fang, Qiongyan Wang +2
Node importance estimation problem has been studied conventionally with homogeneous network topology analysis. To deal with network heterogeneity, a few recent methods employ graph…
An Augmented Index-based Efficient Community Search for Large Directed Graphs
Yankai Chen, Jie Zhang, Yixiang Fang +2
Given a graph G and a query vertex q, the topic of community search (CS), aiming to retrieve a dense subgraph of G containing q, has gained much attention. Most existing works focu…
WISK: A Workload-aware Learned Index for Spatial Keyword Queries
Yufan Sheng, Xin Cao, Yixiang Fang +4
Spatial objects often come with textual information, such as Points of Interest (POIs) with their descriptions, which are referred to as geo-textual data. To retrieve such data, sp…
GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs
Linhao Luo, Yixiang Fang, Moli Lu +3
Heterogeneous graphs, which contain nodes and edges of multiple types, are prevalent in various domains, including bibliographic networks, social media, and knowledge graphs. As a…
Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
Linhao Luo, Yixiang Fang, Xin Cao +2
Community detection, aiming to group the graph nodes into clusters with dense inner-connection, is a fundamental graph mining task. Recently, it has been studied on the heterogeneo…