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This paper addresses the identification problem of causal variables for the system anomaly. In real-world complicated systems, even experts often fail to specify causal factors, thus they attempt to detect the anomaly with exploratory heuristics. Our goal is to offer further information that supports anomaly cause analysis using the incomplete empirical knowledge. Proposed technique discovers responsible...
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an administrator. Often administrators must then manually investigate events to figure out the source of a problem. Stream processing engines (SPEs) are general purpose data management systems for monitoring applications. They provide...
Map generalization is used to derive maps for secondary scales and/or specific goals. This operation greatly benefits spatial decision support systems as it can provide a global and simplified representation of a phenomenon discarding irrelevant information. The recent popularity of OLAP systems for various application domains has generated much interest for the development of spatial OLAP (SOLAP)...
In this paper a new algorithm, called CStar, for document clustering is presented. This algorithm improves recently developed algorithms like generalized star (GStar) and ACONS algorithms, originally proposed for reducing some drawbacks presented in previous Star-like algorithms.The CStar algorithm uses the condensed star-shaped sub-graph concept defined by ACONS, but defines a new heuristic that...
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