Recommended content determination method and device and storage medium
A technology for recommending content and determining methods, applied in biological neural network models, marketing, advertising, etc., can solve problems such as inability to personalize recommendations for new content and new users, modeling of new content and new users
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[0024] Example 1
[0025] According to an embodiment of the present invention, a method for determining recommended content is provided, such as figure 1 As shown, the method includes:
[0026] S102, according to the prediction neural network model, determine the predicted click probability corresponding to the multiple content to be recommended corresponding to the user, wherein the prediction neural network model is obtained by training according to the user's user characteristics, the user's historical browsing content and the content to be recommended;
[0027] S104 , sort a plurality of to-be-recommended contents according to the predicted click probability to determine target recommended contents.
[0028] In the related art, there are generally a plurality of contents to be recommended for a user, which are located in the to-be-recommended contents library, and are ready to be recommended for the user. For example, content that is displayed for the user when the user ...
Example Embodiment
[0048] Example 2
[0049] According to an embodiment of the present invention, there is also provided a recommended content determination device for implementing the above recommended content determination method, such as Figure 4 As shown, the device includes:
[0050] 1) A determination unit 40, configured to determine the respective predicted click probabilities corresponding to a plurality of contents to be recommended corresponding to the user according to the predicted neural network model, wherein the predicted neural network model is based on the user characteristics of the user, the user's The historical browsing content and the content to be recommended are obtained from training;
[0051] 2) The processing unit 42, configured to sort the plurality of contents to be recommended according to the predicted click probability to determine the target recommended contents.
[0052] Optionally, in this embodiment, it also includes:
[0053] 1) a first acquiring unit, co...
Example Embodiment
[0058] Example 3
[0059] Embodiments of the present invention also provide a storage medium. Optionally, a storage medium, the storage medium includes a stored program, wherein when the program runs, the above-mentioned method for determining recommended content is executed.
[0060] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps:
[0061] S1, according to the prediction neural network model to determine the respective predicted click probabilities corresponding to the multiple contents to be recommended corresponding to the user, wherein the predicted neural network model is based on the user characteristics of the user, the user's historical browsing content and the to-be-recommended content content training;
[0062] S2 sorts the plurality of contents to be recommended according to the predicted click probability to determine the target recommended contents.
[0063] Optionally, in this embodimen...
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