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Titlebook: Big Data Analytics and Knowledge Discovery; 17th International C Sanjay Madria,Takahiro Hara Conference proceedings 2015 Springer Internati

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Balancing Tree Size and Accuracy in Fast Mining of Uncertain Frequent Patternse algorithm. Our experimental results reveal a diminishing return on performance as the bound is increasingly tightened, allowing us to make a recommendation on the most effective use of extra storage towards increasing the efficiency of the algorithm.
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A New Relevance Measure for Heterogeneous Networks to be measured. In order to validate the effectiveness of the proposed measure, we compared its performance with existing relevance measures which are semi-metric and applicable to heterogeneous networks. To show the viability and the effectiveness of the proposed measure, experiments were performe
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Introducing Foreign Models for Developmentobjects in dimensions in linear time. Our algorithm exploits the ordered neighborhoods in order to find both the similar objects and the dimensions in which these objects show high similarity. Evaluation results show that our method is scalable with both database size and dimensionality and enhances
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Composing Functions Using Pipelininge algorithm. Our experimental results reveal a diminishing return on performance as the bound is increasingly tightened, allowing us to make a recommendation on the most effective use of extra storage towards increasing the efficiency of the algorithm.
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