61 citations · 207 across the 25 of their papers we have counts for
7 papers · 1 filter
Personalized Graph Summarization: Formulation, Scalable Algorithms, and Applications
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Are users of an online social network interested equally in all connections in the network? If not, how can we obtain a summary of the network personalized to specific users? Can w…
Are Edge Weights in Summary Graphs Useful? -- A Comparative Study
Shinhwan Kang, Kyuhan Lee, Kijung Shin
Which one is better between two representative graph summarization models with and without edge weights? From web graphs to online social networks, large graphs are everywhere. Gra…
Incremental Lossless Graph Summarization
Jihoon Ko, Yunbum Kook, Kijung Shin
Given a fully dynamic graph, represented as a stream of edge insertions and deletions, how can we obtain and incrementally update a lossless summary of its current snapshot? As lar…
SSumM: Sparse Summarization of Massive Graphs
Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko +2
Given a graph G and the desired size k in bits, how can we summarize G within k bits, while minimizing the information loss? Large-scale graphs have become omnipresent, posing cons…
CoCoS: Fast and Accurate Distributed Triangle Counting in Graph Streams
Kijung Shin, Euiwoong Lee, Jinoh Oh +2
Given a graph stream, how can we estimate the number of triangles in it using multiple machines with limited storage? Specifically, how should edges be processed and sampled across…
Detecting Group Anomalies in Tera-Scale Multi-Aspect Data via Dense-Subtensor Mining
Kijung Shin, Bryan Hooi, Jisu Kim +1
How can we detect fraudulent lockstep behavior in large-scale multi-aspect data (i.e., tensors)? Can we detect it when data are too large to fit in memory or even on a disk? Past s…