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Titlebook: Web-Age Information Management; 12th International C Haixun Wang,Shijun Li,Tieyun Qian Conference proceedings 2011 The Editor(s) (if applic

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楼主: 神像之光环
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Getting Critical Categories of a Data Set categories can be treated as a probabilistic data set. In this paper, we devise a novel method to handle this issue. Analysis in theorem and experimental results show the effectiveness and efficiency of the proposed method.
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QuerySem: Deriving Query Semantics Based on Multiple Ontologiesed by multiple large-scale general-purpose ontologies to derive the semantic aspects of the user’s query. In addition, we utilize statistical-based semantic relatedness measures to compensate for missing background knowledge in the exploited ontologies. Experimental instantiation of the proposed system validates our proposal.
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MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Datasetenerates a weighted undirected relational graph firstly. Then all the maximal fault-tolerant biclusters would be mined by using pattern-growth method in above graph. The experimental results show our algorithm is more efficiently than traditional ones.
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MFCluster: Mining Maximal Fault-Tolerant Constant Row Biclusters in Microarray Datasetenerates a weighted undirected relational graph firstly. Then all the maximal fault-tolerant biclusters would be mined by using pattern-growth method in above graph. The experimental results show our algorithm is more efficiently than traditional ones.
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Probabilistic Threshold Join over Distributed Uncertain Dataery with communication efficiency. Furthermore, we provide theoretical analysis of the network cost of our algorithm and demonstrate it by simulation. The experiment results show that our algorithm can save network cost efficiently by comparing to original Bloomjoin algorithm in most scenarios.
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