PARALLEL AND LOAD BALANCING APPROACH FOR MINING FREQUENT PATTERN ON UNCERTAINGRAPHS USING SPARK FRAMEWORK
Dr.A.Clementking B.Uma · Journal of Critical Reviews · 2020
The decision making process is important for variety of real time applications. The uncertain graph is used in bio-informatics, social media, and data analytics process. This paper provides the problem of changes in sub graph mining using uncertain graphs. The probabilistic and semantic mining is applied for efficient mining. The frequent patterns are collected and solve using semantics. The P-Complete approximation is applied for evaluation of algorithm and give guarantee to achieve mining performance. A single uncertain graph is taken for probabilistic semantics and accuracy can be achieved using devise computation method. The frequent patterns are devised and generated uncertain graph for computations. This algorithm provides better result and achieves efficient mining. The unexpected results are removed by semantic and checkpoint is used for validation. The experiments results are tested in real time dataset and results are compared with various models.