4/7/2024 0 Comments Finite state automata adalahGraph-based data mining has two major approaches: frequent subgraph mining and graph relational data. The graph depiction that set of nodes and links between nodes allow practice of mining algorithm. Graph mining denotes a group of algorithms for mining the relational aspects of data represented as a graph. The graph mining has been raped sudden increase in the data mining. Using Vectors of Features for Finite State Automata Dataset Reduction. Using Vectors of Features for Finite State Automata Dataset ReductionĪl-assadi T. KEYWORDS:ĭata reduction essential machines FSM graph mining machine matching vectors of featuresĪl-assadi T. 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. 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.
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