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Titlebook: Data Science; Third International Beiji Zou,Min Li,Zeguang Lu Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017 Data ana

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An Extended Model of Literary Literacyed method in practice. It solves the problem of occupying large storage and low analysis efficiency in areas like the storage of the massive XDR bill, pretreatment, aggregation. It provides valuable references for telecommunication-related researchers and engineering practitioner in respect of using the big data technology.
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Mónika Réti,Edit Lippai,Márk Nemesnce availability is whether the important data keep original value in a composite graph. We analysis the properties of important data of k triangle count, and provide a new method for synthesis graph publication. We show the application of this method in k triangle count, and the experimental results proved the accuracy of the method.
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https://doi.org/10.1007/978-3-540-78973-4ine-grained emotion analysis method. Combined with TF-IDF and variance statistics, we realized a method of calculating multi-class feature selection. We judge the text whether it is positive or negative first, then choose the fine-grained emotional tendency. And we get good result with the test usin
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Practical Modulation Calorimetry was used to reduce the dimension of target features to 1-D, so that PCA output 1-D data can be used as label of support vector machine (SVM). Thus on the premise of not losing the prediction correctness, one model can detect the fault of 2 to 4 features, largely reduce the complexity of model build
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https://doi.org/10.1007/978-1-4615-3286-6fication framework, thus in low efficiency. Modern GPU has much higher parallelism as well as memory bandwidth than CPU and can be used to accelerate T-overlap query. In this paper, we use hash segmentation to divide inverted lists into segments, then design an efficient inverted index called GHSII
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https://doi.org/10.1007/978-1-4615-3286-6y and efficiently. Considering the characteristics of multivariate hydrological time series, the continuity and global features of variables, we proposed a pattern matching method, PP-DTW, which is based on dynamic time warping. In this method, the multivariate time series is firstly segmented, and
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