Algorithms for Frequent Subgraph Mining

Abstract: Due to increasing number of complex objects, Data mining algorithms are facing the challenges. To model such complex object, Graph a natural data structure is used. Graph mining is an important research area within the domain of data mining. A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph data base is difficult task than mining pattern from data set, sequences or tree, because graph related operations, such as subgraph testing, generally have higher time complexity. This paper gives the comparative study of frequent subgraph mining algorithms. In this paper different issues are discussed like graph representation, searching strategy, and Graph Summarization.

Keywords: Data mining, graph mining, pattern summarization.