GraMi is a novel framework for frequent subgraph mining in a single large graph, GraMi outperforms existing techniques by 2 orders of magnitudes. GraMi supports finding frequent subgraphs as well as frequent patterns, Compared to subgraphs, patterns offer a more powerful version of matching that captures transitive interactions between graph nodes (like friend of a friend) which are very common in modern applications. Also, GraMi supports user-defined structural and semantic constraints over the results, as well as approximate results. For more details, check our paper: Mohammed Elseidy, Ehab Abdelhamid, Spiros Skiadopoulos, and Panos Kalnis. GRAMI: Frequent Subgraph and Pattern Mining in a Single Large Graph. PVLDB, 7(7):517-528, 2014.
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questions about the node label and the edge label? #21
Dear author, I have several questions about the node label and the edge label.
1) Node labels typically represent some attribute or classification of a node, GraMi will not only look for substructures that are not only structurally identical but also of the same label, is that right?
2) Does the edge label do the same thing?
Dear author, I have several questions about the node label and the edge label. 1) Node labels typically represent some attribute or classification of a node, GraMi will not only look for substructures that are not only structurally identical but also of the same label, is that right? 2) Does the edge label do the same thing?