Personalized recommendation method and system based on connection matrix
The invention belongs to the technical field of personalized recommendation, and particularly relates to a personalized recommendation method and system based on a connection matrix, and the method comprises the steps: constructing a user relation network and a commodity relation network according t...
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creator | XU JINMAO PENG SHUAIHENG DU SHAOYONG GONG DAOFU TAO RONGHUA LIU FENG WANG YIWEI LI ZHENYU WANG YILONG ZHANG LIXIAO TAN LEI LU HAOYU LIU FENLIN |
description | The invention belongs to the technical field of personalized recommendation, and particularly relates to a personalized recommendation method and system based on a connection matrix, and the method comprises the steps: constructing a user relation network and a commodity relation network according to user social data, commodity category data and the decibel of user-to-commodity score data; obtaining a user feature representation vector and a commodity feature representation vector in the user relation network and the commodity relation network by using a network representation learning algorithm; constructing a score prediction model, taking a user feature representation vector and a commodity feature representation vector as model input, fitting the user feature representation vector and the commodity feature representation vector through a connection matrix, taking an inner product of the three as a prediction score output by the model, and training the model by a stochastic gradient descent algorithm; and |
format | Patent |
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obtaining a user feature representation vector and a commodity feature representation vector in the user relation network and the commodity relation network by using a network representation learning algorithm; constructing a score prediction model, taking a user feature representation vector and a commodity feature representation vector as model input, fitting the user feature representation vector and the commodity feature representation vector through a connection matrix, taking an inner product of the three as a prediction score output by the model, and training the model by a stochastic gradient descent algorithm; and</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 | Personalized recommendation method and system based on connection matrix |
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