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When Engagement Meets Similarity: Efficient (k,r)-Core Computation on Social Networks

Summary: Defines the (k,r)-core to jointly enforce engagement (min degree k) and pairwise attribute similarity in social networks, with algorithms to enumerate all maximal (k,r)-cores and compute the maximum core (NP-hard). Introduces pruning techniques, a novel (k,k')-core upper bound, and vertex-order heuristics to accelerate two mining algorithms; experiments on real data show effective cohesive subgraph discovery and substantial performance gains. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11593
Venue
VLDB
Year
2017
Pagerank
6.224902e-05
Overall Rank
4,394 | 69.44%
DOI
-

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