E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium
The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-comm...
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creator | DING JIAWEI BAO BINGKUN LU GUANMING YU PENGHANG |
description | The invention discloses an e-commerce session recommendation method and system based on multi-behavior feature fusion. The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. The multi-behavior characteristics in the session are fused by using the e-com |
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The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. 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The method comprises the following steps of: obtaining four session behavior data of clicking, collecting, purchasing and adding shopping carts of a user on commodities in an e-commerce database; an electronic commerce session recommendation model based on multi-behavior feature fusion is constructed, and the model comprises a behavior feature extraction module, a commodity feature extraction module, a commodity high-order feature extraction module, a session feature extraction module and a commodity recommendation module; four kinds of session behavior data in an e-commerce database are used for training the e-commerce session recommendation model; and utilizing the trained e-commerce session recommendation model to carry out commodity recommendation on users in the session, and outputting a recommendation result. 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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS 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 | E-commerce session recommendation method, system and device based on multi-behavior feature fusion and medium |
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