Abstract
Data mining has a long history, which has a strong attention from researchers in many different fields including database design, statistics, pattern recognition, machine learning, and data visualization. Data mining is the process of finding projective models from the given data. In this paper we overviewed graph mining tasks and the tools which are used for the mining of data represented as graphs.
Highlights
Data mining is the process of the discovery of knowledge from the data
Graph mining has become an important topic of research recently because of numerous applications to a wide variety of data mining problems in biology, chemistry, management, business and communication networking[3]
As the name suggests, are sub graphs that occur frequently in data represented as graphs[1]
Summary
Data mining is the process of the discovery of knowledge from the data. It is a emerging research field of computer science, is defined as the significant process of identifying suitable, prospectively useful, and crucially understandable patterns in data. Graph mining is the process of gathering and analyzing the data represented as graphs[4]. Graph Mining is a relatively new area of research which has a solid base in classic graph theory, computational cost considerations, and sociological concepts such how individuals interrelate, group together and follow one another.
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