Using Vectors of Features for Finite State Automata Dataset Reduction

A finite state automata is the most important type of graphs ,which is called conceptual graphs, while the expansion of using the graphs in the process of data mining, the use of FSM is still limited because of the difficulty in processing in databases, therefore in order to find methods that make it easier to deal with large groups of machines, as a database, is encourage to use of this type of representation in this paper of graph mining . This paper present a method using vectors of features for find machines matching, which is one task of mining graph data , which are frequently found in a single environment or similar environments, thereby reducing the number of records and increase efficiency of mining tasks.