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Multiple pattern detection is needed in applications like disease analysis over gene networks, bug detection in program flow networks. This paper takes pattern detection to investigate the evaluation and optimization of multiple jobs in existing distributed graph processing frameworks. The evaluation plan for multiple pattern detection should be parallelizable and can capture and reuse the shared...
This paper studies continuous pattern detection over large evolving graphs, which plays an important role in monitoring-related applications. The problem is challenging due to the large size and dynamic updates of graphs, the massive search space of pattern detection and inconsistent query results on dynamic graphs. This paper first introduces a snapshot isolation requirement, which ensures that the...
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