158 citations · 312 across the 6 of their papers we have counts for
7 papers
RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases
Dongwon Choi, Sunwoo Kim, Juyeon Kim +5
Recent advances have demonstrated the effectiveness of graph-based learning on relational databases (RDBs) for predictive tasks. Such approaches require transforming RDBs into grap…
Discovering Hypernymy in Text-Rich Heterogeneous Information Network by Exploiting Context Granularity
Yu Shi, Jiaming Shen, Yuchen Li +7
Text-rich heterogeneous information networks (text-rich HINs) are ubiquitous in real-world applications. Hypernymy, also known as is-a relation or subclass-of relation, lays in the…
Dimensionality of social networks using motifs and eigenvalues
Anthony Bonato, David F. Gleich, Myunghwan Kim +4
We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from…
Nonparametric Multi-group Membership Model for Dynamic Networks
Myunghwan Kim, Jure Leskovec
Relational data-like graphs, networks, and matrices-is often dynamic, where the relational structure evolves over time. A fundamental problem in the analysis of time-varying networ…
Latent Multi-group Membership Graph Model
Myunghwan Kim, Jure Leskovec
We develop the Latent Multi-group Membership Graph (LMMG) model, a model of networks with rich node feature structure. In the LMMG model, each node belongs to multiple groups and e…
Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model
Myunghwan Kim, Jure Leskovec
Networks arising from social, technological and natural domains exhibit rich connectivity patterns and nodes in such networks are often labeled with attributes or features. We addr…
Multiplicative Attribute Graph Model of Real-World Networks
Myunghwan Kim, Jure Leskovec
Large scale real-world network data such as social and information networks are ubiquitous. The study of such social and information networks seeks to find patterns and explain the…