76 citations · 194 across the 8 of their papers we have counts for
12 papers
Edge-based Local Push for Personalized PageRank
Hanzhi Wang, Zhewei Wei, Junhao Gan +3
Personalized PageRank (PPR) is a popular node proximity metric in graph mining and network research. Given a graph G=(V,E) and a source node , a single-source PPR (SSPPR)…
Coo: Rethink Data Anomalies In Databases
Haixiang Li, Xiaoyan Li, Yuxing Chen +5
Transaction processing technology has three important contents: data anomalies, isolation levels, and concurrent control algorithms. Concurrent control algorithms are used to elimi…
G-TADOC: Enabling Efficient GPU-Based Text Analytics without Decompression
Feng Zhang, Zaifeng Pan, Yanliang Zhou +4
Text analytics directly on compression (TADOC) has proven to be a promising technology for big data analytics. GPUs are extremely popular accelerators for data analytics systems. U…
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
Nan Tang, Ju Fan, Fangyi Li +5
Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a…
Scalable Graph Neural Networks via Bidirectional Propagation
Ming Chen, Zhewei Wei, Bolin Ding +4
Graph Neural Networks (GNN) is an emerging field for learning on non-Euclidean data. Recently, there has been increased interest in designing GNN that scales to large graphs. Most…
TADOC: Text Analytics Directly on Compression
Feng Zhang, Jidong Zhai, Xipeng Shen +5
This article provides a comprehensive description of Text Analytics Directly on Compression (TADOC), which enables direct document analytics on compressed textual data. The article…