Data encoding system and method based on dual data decomposition
A data encoding and data technology, applied in the field of data encoding, can solve problems such as limited improvement in encoding efficiency, low data encoding efficiency, and resource consumption.
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Embodiment 1
[0027] Such as figure 1 As shown, the data encoding system based on double data decomposition, the system includes: a data preprocessing unit, a data decomposition unit, a data encoding unit, a data encryption unit and a data combination unit: the data preprocessing unit is configured to Processing data to perform data preprocessing to obtain preprocessed data; the data preprocessing process at least includes: removing unique attributes, processing missing values, data specification and outlier detection and processing; the data decomposition unit is configured to preprocess The data is decomposed into threshold data and extra-threshold data based on a preset threshold; the data encoding unit is configured to perform data encoding on the decomposed threshold data to obtain encoded data; the data encryption unit is configured to Data encryption is performed on the decomposed extrathreshold data to obtain encrypted data; the data combination unit is configured to perform data co...
Embodiment 2
[0030] On the basis of the previous embodiment, the data preprocessing unit includes: a subunit for removing unique attributes, a subunit for processing missing values, a subunit for data reduction, and an outlier detection and processing subunit; the subunit for removing unique data, The configuration is used to remove the unique attribute of the data to be processed; the processing missing value subunit is configured to process the missing value in the data to be processed; the data specification subunit is configured to perform data specification processing on the data to be processed; outlier detection and processing The subunit is configured to detect abnormal values in the data to be processed, and process the detected abnormal values.
[0031] Specifically, for small or medium-sized datasets, general data preprocessing steps are sufficient. But for really large datasets, it is more likely to take an intermediate, extra step—data reduction—before applying data mining t...
Embodiment 3
[0034] On the basis of the previous embodiment, the method for the data reduction subunit to perform data reduction processing on tempered data includes: removing the average value, calculating the covariance matrix, calculating the eigenvalues and eigenvectors of the covariance matrix, and calculating the eigenvalues Sort from large to small, retain the largest eigenvector, and convert the data into a new space constructed by the eigenvector; finally, the new processed data is obtained. These data are irrelevant to each other, but maintain the original information.
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