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Frequent Subgraph Mining Algorithms – A Survey

Publication Type : Journal Article

Publisher : Elsevier

Source : Procedia Computer Science – Elsevier, Vol.47, pp: 197-204., Indexed: Scopus, Impact Factor: 1.26

Url :,based%20upon%20the%20domain%20expectations.

Campus : Coimbatore

School : School of Computing

Department : Computer Science and Engineering

Year : 2015

Abstract : Graphs are common data structures used to represent / model real-world systems. Graph Mining is one of the arms of Data mining in which voluminous complex data are represented in the form of graphs and mining is done to infer knowledge from them. Frequent sub graph mining is a sub section of graph mining domain which is extensively used for graph classification, building indices and graph clustering purposes. The frequent sub graph mining is addressed from various perspectives and viewed in different directions based upon the domain expectations. In this paper, a survey is done on the approaches in targeting frequent sub graphs and various scalable techniques to find them.

Cite this Research Publication : T. Ramraj, R. Prabhakar,Frequent Subgraph Mining Algorithms – A Survey,Procedia Computer Science,Volume 47,2015,Pages 197-204,ISSN 1877-0509

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