Titlebook: Advanced Data Mining and Applications; 14th International C Guojun Gan,Bohan Li,Shuliang Wang Conference proceedings 2018 Springer Nature S

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Berichte zur Lebensmittelsicherheit 2014oit possibilistic networks (PN) and a multi-terminology in order to extract and disambiguate terms and then to retrieve documents. The two measures of possibility and necessity were used to select the relevant concept of an ambiguous term. Thus, the user query and unstructured documents are describe

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Berichte zur Lebensmittelsicherheit 2014o identify outliers embedded in subspaces. The existing technique, mainly using genetic algorithm (GA) to carry out the subspace search, is generally slow due to its expensive fitness evaluation and long solution encoding scheme. In this paper, we propose a novel technique to improve the performance

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Berichte zur Lebensmittelsicherheit 2014or steady-state visual evoked potentials (SSVEPs) frequency recognition is proposed in this paper to enhance the performance of SSVEP-based brain-computer interface (BCI). As a type of electroencephalogram (EEG) signals, SSVEPs generated from underlying brain sources is different from other activiti

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Berichte zur Resistenzmonitoringstudie 2009 not be suitable for the detecting image and the transform matrix fails to combine the low-level features of the image. In this paper, we propose a novel salient object detection model that combines sparse and low-rank matrix recovery (SLRR) with the adaptive background template. Our SLRR model usin

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Berichte zur Resistenzmonitoringstudie 2009any indication. In order to solve this problem, a new SDC vulnerability prediction method based on deep learning model is proposed. Our method predicts the SDC vulnerability of each instruction in the program based on the inherent and dependent features of each instruction in the Lower Level Virtual

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