Method for constructing user space-time portrait array based on big data algorithm
The invention discloses a method for constructing a user space-time portrait array based on a big data algorithm. The method comprises the following steps: collecting all-day operation behavior data of different platforms and different users in different systems; preprocessing the collected data to...
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creator | XIAO LINGSHENG CAI BIN ANG RAN LIN CHAOPENG ZHANG QIUQUAN HUANG XIAOBIN |
description | The invention discloses a method for constructing a user space-time portrait array based on a big data algorithm. The method comprises the following steps: collecting all-day operation behavior data of different platforms and different users in different systems; preprocessing the collected data to extract user behavior characteristics; establishing user behavior preference labels according to the user behavior characteristics, and performing multi-level division processing; defining user behavior preferences of different time dimensions in a fixed period by using a label attenuation algorithm; analyzing the operation behaviors of multiple users at different time points in batches, and extracting the same service operation behaviors of different users in the same time window; and constructing a service-related user space-time portrait array. According to the method, the time factor and the space factor of the user behavior are comprehensively considered, a dynamic and high-dimensional user space-time portrait |
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The method comprises the following steps: collecting all-day operation behavior data of different platforms and different users in different systems; preprocessing the collected data to extract user behavior characteristics; establishing user behavior preference labels according to the user behavior characteristics, and performing multi-level division processing; defining user behavior preferences of different time dimensions in a fixed period by using a label attenuation algorithm; analyzing the operation behaviors of multiple users at different time points in batches, and extracting the same service operation behaviors of different users in the same time window; and constructing a service-related user space-time portrait array. 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The method comprises the following steps: collecting all-day operation behavior data of different platforms and different users in different systems; preprocessing the collected data to extract user behavior characteristics; establishing user behavior preference labels according to the user behavior characteristics, and performing multi-level division processing; defining user behavior preferences of different time dimensions in a fixed period by using a label attenuation algorithm; analyzing the operation behaviors of multiple users at different time points in batches, and extracting the same service operation behaviors of different users in the same time window; and constructing a service-related user space-time portrait array. According to the method, the time factor and the space factor of the user behavior are comprehensively considered, a dynamic and high-dimensional user space-time portrait</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 | Method for constructing user space-time portrait array based on big data algorithm |
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