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20122020
most citedA Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

39 citations · 62 across the 8 of their papers we have counts for

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cs.DS201939 cited

A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Pinghui Wang, Yiyan Qi, Yuanming Zhang +4

Estimating set similarity and detecting highly similar sets are fundamental problems in areas such as databases, machine learning, and information retrieval. MinHash is a well-know…

cs.DS2019

A Fast Sketch Method for Mining User Similarities over Fully Dynamic Graph Streams

Peng Jia, Pinghui Wang, Jing Tao +1

Many real-world networks such as Twitter and YouTube are given as fully dynamic graph streams represented as sequences of edge insertions and deletions. (e.g., users can subscribe…

cs.DS2018

REPT: A Streaming Algorithm of Approximating Global and Local Triangle Counts in Parallel

Pinghui Wang, Peng Jia, Yiyan Qi +3

Recently, considerable efforts have been devoted to approximately computing the global and local (i.e., incident to each node) triangle counts of a large graph stream represented a…

cs.DS2018

Utilizing Dynamic Properties of Sharing Bits and Registers to Estimate User Cardinalities over Time

Pinghui Wang, Peng Jia, Xiangliang Zhang +3

Online monitoring user cardinalities (or degrees) in graph streams is fundamental for many applications. For example in a bipartite graph representing user-website visiting activit…

cs.DS2018

Submodular Optimization Over Streams with Inhomogeneous Decays

Junzhou Zhao, Shuo Shang, Pinghui Wang +2

Cardinality constrained submodular function maximization, which aims to select a subset of size at most to maximize a monotone submodular utility function, is the key in many d…