rectocele
发表于 2025-3-30 10:06:29
Time-Based Trajectory Data Partitioning for Efficient Range Querysed hash strategy to ensure both the partition balancing and less partitioning time. Especially, existing trajectory data are not required to be repartitioned when new data arrive. Extensive experiments on three real data sets demonstrated that the performance of the proposed technique outperformed other partitioning techniques.
使人烦燥
发表于 2025-3-30 15:21:10
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left-ventricle
发表于 2025-3-30 18:05:39
Secure Computation of Pearson Correlation Coefficients for High-Quality Data Analyticsnts. For the secure Pearson correlation computation, we first propose an advanced solution by exploiting the secure scalar product. We then present an approximate solution by adopting the lower-dimensional transformation. We finally empirically show that the proposed solutions are practical methods in terms of execution time and data quality.
Pert敏捷
发表于 2025-3-30 23:51:31
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宏伟
发表于 2025-3-31 01:25:49
Extracting Schemas from Large Graphs with Utility Function and Parallelizationation cost. In this paper, we propose a schema extraction algorithm based on (a) a novel utility function called local utility function and (b) parallelization. Experimental results show that our algorithm can extract schemas from graphs more efficiently without losing quality of schemas.
后退
发表于 2025-3-31 07:41:27
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并排上下
发表于 2025-3-31 12:53:45
Convolutional Neural Networks for Text Classification with Multi-size Convolution and Multi-type Pootakes too much time and energy to extract features of data, but only obtains poor performance. Recently, deep learning methods are widely used in text classification and result in good performance. In this paper, we propose a Convolutional Neural Network (CNN) with multi-size convolution and multi-t