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- W3043023780 abstract "The decision making process is important for variety of real time applications. The uncertain graph isused in bio-informatics, social media, and data analytics process. This paper provides the problem of changes in subgraph mining using uncertain graphs. The probabilistic and semantic mining is applied for efficient mining. Thefrequent patterns are collected and solve using semantics. The P-Complete approximation is applied for evaluationof algorithm and give guarantee to achieve mining performance. A single uncertain graph is taken for probabilisticsemantics and accuracy can be achieved using devise computation method. The frequent patterns are devised andgenerated uncertain graph for computations. This algorithm provides better result and achieves efficient mining. Theunexpected results are removed by semantic and checkpoint is used for validation. The experiments results are testedin real time dataset and results are compared with various models." @default.
- W3043023780 created "2020-07-23" @default.
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- W3043023780 date "2020-01-01" @default.
- W3043023780 modified "2023-09-26" @default.
- W3043023780 title "PARALLEL AND LOAD BALANCING APPROACH FOR MINING FREQUENT PATTERN ON UNCERTAINGRAPHS USING SPARK FRAMEWORK" @default.
- W3043023780 hasPublicationYear "2020" @default.
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