activity
20122022
most citedBLOCKBENCH: A Framework for Analyzing Private Blockchains

211 citations · 523 across the 28 of their papers we have counts for

collaborators

28 papers

cs.SI2022

Efficient Sampling Algorithms for Approximate Motif Counting in Temporal Graph Streams

Jingjing Wang, Yanhao Wang, Wenjun Jiang +2

A great variety of complex systems, from user interactions in communication networks to transactions in financial markets, can be modeled as temporal graphs consisting of a set of…

cs.HC2022★ 1 cited

The Metaverse Data Deluge: What Can We Do About It?

Beng Chin Ooi, Gang Chen, Mike Zheng Shou +5

In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space…

cs.DS2020

Enhancing Balanced Graph Edge Partition with Effective Local Search

Zhenyu Guo, Mingyu Xiao, Yi Zhou +2

Graph partition is a key component to achieve workload balance and reduce job completion time in parallel graph processing systems. Among the various partition strategies, edge par…

cs.CY2020

Understanding the Dynamics of Drivers' Locations for Passengers Pickup Performance: A Case Study

Punit Rathore, Ali Zonoozi, Omid Geramifard +1

With the emergence of e-hailing taxi services, a growing number of scholars have attempted to analyze the taxi trips data to gain insights from drivers' and passengers' flow patter…

cs.SI2020

Efficient Sampling Algorithms for Approximate Temporal Motif Counting (Extended Version)

Jingjing Wang, Yanhao Wang, Wenjun Jiang +2

A great variety of complex systems ranging from user interactions in communication networks to transactions in financial markets can be modeled as temporal graphs, which consist of…

cs.DS2020

GRMR: Generalized Regret-Minimizing Representatives

Yanhao Wang, Michael Mathioudakis, Yuchen Li +1

Extracting a small subset of representative tuples from a large database is an important task in multi-criteria decision making. The regret-minimizing set (RMS) problem is recently…