Open AccessEnsemble Distributed Search-FSGM-CRD Compressed Cache Algorithm for Large Datasets
Author(s) -
M. Sailaja
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i2.2317
Subject(s) - computer science , graph , cache , theoretical computer science , data mining , graph database , parallel computing
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