Commodity recommendation method and system, equipment and storage medium
The invention discloses a commodity recommendation method and system, equipment and a storage medium. The method comprises the steps of: obtaining latest behavior log data generated when a user browses or purchases a commodity; processing the latest behavior log data by adopting a preset preference...
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| creator | CHEN QIHAN WEI XINYU ZHANG PAN CHEN LUNGUANG CHEN WEIJIAN LIN PEIQI |
| description | The invention discloses a commodity recommendation method and system, equipment and a storage medium. The method comprises the steps of: obtaining latest behavior log data generated when a user browses or purchases a commodity; processing the latest behavior log data by adopting a preset preference model group to generate a commodity preference vector of the user; processing the latest behavior log data by adopting a preset entity relationship model to generate a commodity vector; and calculating a recommendation probability of the commodity according to the commodity preference vector and thecommodity vector, and recommending the commodity according to the recommendation probability. With the commodity recommendation method and system, equipment and storage medium of the invention adopted, the problem that a recommendation algorithm adopted by an existing shopping network to recommend commodities to users is inaccurate in recommendation precision and hard to meet actual requirementsof the users is solved, ti |
| format | Patent |
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The method comprises the steps of: obtaining latest behavior log data generated when a user browses or purchases a commodity; processing the latest behavior log data by adopting a preset preference model group to generate a commodity preference vector of the user; processing the latest behavior log data by adopting a preset entity relationship model to generate a commodity vector; and calculating a recommendation probability of the commodity according to the commodity preference vector and thecommodity vector, and recommending the commodity according to the recommendation probability. 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The method comprises the steps of: obtaining latest behavior log data generated when a user browses or purchases a commodity; processing the latest behavior log data by adopting a preset preference model group to generate a commodity preference vector of the user; processing the latest behavior log data by adopting a preset entity relationship model to generate a commodity vector; and calculating a recommendation probability of the commodity according to the commodity preference vector and thecommodity vector, and recommending the commodity according to the recommendation probability. With the commodity recommendation method and system, equipment and storage medium of the invention adopted, the problem that a recommendation algorithm adopted by an existing shopping network to recommend commodities to users is inaccurate in recommendation precision and hard to meet actual requirementsof the users is solved, ti</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 PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Commodity recommendation method and system, equipment and storage medium |
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