Core maintenance for hypergraph streams
Authors: 
Qi Luo, Dongxiao Yu, Zhipeng Cai, Yanwei Zheng, Xiuzhen Cheng, Xuemin LinAuthors Info & Claims
Qi Luo, Dongxiao Yu, Zhipeng Cai, Yanwei Zheng, Xiuzhen Cheng, Xuemin LinAuthors Info & ClaimsPages 3709 - 3733
Abstract
This paper studies batch processing of core maintenance in hypergraph streams. We focus on updating the coreness of each vertex after the hypergraph evolves. Unlike existing works that mainly focus on exact coreness updates for the single hyperedge dynamic or approximate update, we propose the first known batch processing algorithms for exact core maintenance with insertions or deletions of multiple hyperedges. By proposing a hyperedge structure Joint Hyperedge Set, we tackle the challenges of quantifying the range of coreness change and finding potential vertices whose coreness may update. In addition, we accelerate coreness updates even further by finding structures that enable parallel execution. Extensive experiments illustrate the efficiency, scalability, and effectiveness of our batch core maintenance algorithms on real-world hypergraphs. It shows that our algorithms can be faster than the single hyperedge processing approaches by a factor of nearly half the number of hyperedges processed, and our parallel algorithms achieve linear acceleration with the increasing number of threads.
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Publication History
Published: 25 August 2023
Accepted: 12 July 2023
Revision received: 28 June 2023
Received: 05 May 2023
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