핵심 개념
This paper introduces a memory-efficient approach to parallel community detection in large graphs, utilizing weighted Misra-Gries sketches to reduce the memory footprint of Louvain, Leiden, and Label Propagation Algorithms (LPA) at the cost of moderate runtime increase.
통계
The MG-based Louvain algorithm with 8 slots is, on average, 2.07× slower than the default Louvain algorithm on web graphs.
The MG-based Leiden algorithm with 64 slots runs 3.19× slower than the default Leiden algorithm.
The MG-based LPA algorithm with 8 slots is 2.11× slower than the default LPA algorithm.