Ensemble Distributed Search-FSGM-CRD Compressed Cache Algorithm for Large Datasets
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Abstract
Frequent sub-graph mining (FSM) is a alternative of frequent pattern mining where patterns are graphs. Among the entities, graph based representation is utilized to effectively represent the complex relationships. Various graph mining techniques are developed from the past many years, most the challenging tasks in graph mining is frequent sub-graph mining (FSM). In FSM many of the existing algorithms consider only graph based structure, the relationships based on entities involved and strength is not considered. It is very important to handle the complex and huge data. There is very huge demand in distributed computational approaches. In this paper, An Ensemble Distributed Search-FSGM-CRD Compressed Cache Algorithm is developed and implemented to find frequent sub graphs.
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