A new algorithm for mining frequent connected subgraphs based on adjacency matrices
Most of the Frequent Connected Subgraph Mining (FCSM) algorithms have been focused on detecting duplicate candidates using canonical form (CF) tests. CF tests have high computational complexity, which affects the efficiency of graph miners. In this paper, we introduce novel properties of the canonic...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2010 |
| País: | México |
| Institución: | Instituto Nacional de Astrofísica, Óptica y Electrónica |
| Repositorio: | Repositorio Institucional del INAOE |
| Idioma: | inglés |
| OAI Identifier: | oai:inaoe.repositorioinstitucional.mx:1009/1395 |
| Acceso en línea: | http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1395 |
| Access Level: | acceso abierto |
| Palabra clave: | info:eu-repo/classification/Data mining/Data mining info:eu-repo/classification/Graph mining/Graph mining info:eu-repo/classification/Frequent subgraphs/Frequent subgraphs info:eu-repo/classification/Labeled graphs/Labeled graphs info:eu-repo/classification/Canonical adjacency matrices/Canonical adjacency matrices info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/12 info:eu-repo/classification/cti/1203 |
| Sumario: | Most of the Frequent Connected Subgraph Mining (FCSM) algorithms have been focused on detecting duplicate candidates using canonical form (CF) tests. CF tests have high computational complexity, which affects the efficiency of graph miners. In this paper, we introduce novel properties of the canonical adjacency matrices for reducing the number of CF tests in FCSM. Based on these properties, a new algorithm for frequent connected subgraph mining called grCAM is proposed. The experiments on real world datasets show the impact of the proposed properties in FCSM. Besides, the performance of our algorithm is compared against some other reported algorithms. |
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