Matrix transformation and decomposition commodity recommendation method based on point cut set graph segmentation
The invention discloses a matrix transformation and decomposition commodity recommendation method based onpoint cut set graph segmentation. The method comprises the following steps: 1) acquiring basic data, and constructing an original scoring matrix; 2) converting the original scoring matrix into a...
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| creator | MAO YIJUN GU WANRONG HE YICHEN LIANG ZAOQING |
| description | The invention discloses a matrix transformation and decomposition commodity recommendation method based onpoint cut set graph segmentation. The method comprises the following steps: 1) acquiring basic data, and constructing an original scoring matrix; 2) converting the original scoring matrix into a bilateral block diagonal matrix by using a cut set graph segmentation algorithm based on community discovery, and splicing bilateral and diagonal blocks of the bilateral block diagonal matrix into a block diagonal matrix containing a plurality of sub-matrixes; 3) based on sub-matrixes in the spliced block diagonal matrix, executing a matrix decomposition algorithm to obtain a set of decomposition results; 4) predicting a blank score according to a set of decomposition results to obtain an approximate matrix of the original matrix; and 5) carrying out personalized commodity recommendation on the user according to the approximate matrix. According to the method, a matrix decomposition method based on a bilateral blo |
| format | Patent |
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The method comprises the following steps: 1) acquiring basic data, and constructing an original scoring matrix; 2) converting the original scoring matrix into a bilateral block diagonal matrix by using a cut set graph segmentation algorithm based on community discovery, and splicing bilateral and diagonal blocks of the bilateral block diagonal matrix into a block diagonal matrix containing a plurality of sub-matrixes; 3) based on sub-matrixes in the spliced block diagonal matrix, executing a matrix decomposition algorithm to obtain a set of decomposition results; 4) predicting a blank score according to a set of decomposition results to obtain an approximate matrix of the original matrix; and 5) carrying out personalized commodity recommendation on the user according to the approximate matrix. 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The method comprises the following steps: 1) acquiring basic data, and constructing an original scoring matrix; 2) converting the original scoring matrix into a bilateral block diagonal matrix by using a cut set graph segmentation algorithm based on community discovery, and splicing bilateral and diagonal blocks of the bilateral block diagonal matrix into a block diagonal matrix containing a plurality of sub-matrixes; 3) based on sub-matrixes in the spliced block diagonal matrix, executing a matrix decomposition algorithm to obtain a set of decomposition results; 4) predicting a blank score according to a set of decomposition results to obtain an approximate matrix of the original matrix; and 5) carrying out personalized commodity recommendation on the user according to the approximate matrix. 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The method comprises the following steps: 1) acquiring basic data, and constructing an original scoring matrix; 2) converting the original scoring matrix into a bilateral block diagonal matrix by using a cut set graph segmentation algorithm based on community discovery, and splicing bilateral and diagonal blocks of the bilateral block diagonal matrix into a block diagonal matrix containing a plurality of sub-matrixes; 3) based on sub-matrixes in the spliced block diagonal matrix, executing a matrix decomposition algorithm to obtain a set of decomposition results; 4) predicting a blank score according to a set of decomposition results to obtain an approximate matrix of the original matrix; and 5) carrying out personalized commodity recommendation on the user according to the approximate matrix. According to the method, a matrix decomposition method based on a bilateral blo</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Matrix transformation and decomposition commodity recommendation method based on point cut set graph segmentation |
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