Sep 3, 2011 · ABSTRACT. With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network ...
Aug 1, 2011 · Abstract. With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has ...
ABSTRACT. With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become ...
In [34] , Zhu et al. propose SpiderMine to probabilistically find the top k-large frequent subgraph patterns from a single large networks. Their focus is more ...
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We propose Spider-Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability ...
1. Mining Top-K Large Structural Patterns in a Massive Network. · 2. A Direct Mining Approach To Efficient Constrained Graph Pattern Discovery.
Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu Mining Top-K Large Structural Patterns in a Massive Network VLDB, 2011. VLDB 2011 ...
Mining Top-k Frequent Patterns in Large Geosocial Networks: A Mnie ...
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Mar 16, 2023 · Abstract: Frequent pattern mining (FPM) has played an important role in many graph domains, such as bioinformatics and social networks.
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ABSTRACT. We investigate the problem of correlated subgraphs mining (CSM) where the goal is to identify pairs of subgraph patterns that fre-.
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Presentation on theme: "Mining Top-K Large Structural Patterns in a Massive Network Feida Zhu 1, Qiang Qu 2, David Lo 1, Xifeng Yan 3, Jiawei Han 4, and Philip ...