Agricultural course optimization method and device, electronic equipment and computer program product

Abstract

The invention is suitable for the technical field of agriculture, and provides an agricultural course optimization method and device, electronic equipment and a computer program product, and the method comprises the steps: obtaining learning information corresponding to a to-be-recommended target user, and the learning information comprises behavior information and / or feedback information when the target user carries out the learning according to an agricultural course; determining agricultural information to be recommended according to the learning information; and pushing the agricultural information to be recommended to the target user. The agricultural course learning effect of the user can be improved.

Claims

1. A method for optimizing agricultural courses, characterized in that: include: Acquire learning information corresponding to the target user to be recommended, wherein the learning information includes behavior information and / or feedback information of the target user when learning according to the agricultural course; Determining agricultural information to be recommended based on the learning information; The agricultural information to be recommended is pushed to the target user.

2. The agricultural course optimization method according to claim 1, characterized in that: The step of determining the agricultural information to be recommended according to the learning information comprises: Determining a target recommendation type, where the target recommendation type is determined according to the learning information and is used to reflect the type of agricultural information whose attention degree of the target user is greater than or equal to an attention threshold; The agricultural information to be recommended is determined according to the target recommendation type.

3. The agricultural course optimization method according to claim 2, characterized in that: The step of determining the agricultural information to be recommended according to the target recommendation type includes: The agricultural information to be recommended is determined according to the target recommendation type and the user information of the target user.

4. The agricultural course optimization method according to any one of claims 1 to 3, characterized in that: The step of determining the agricultural information to be recommended according to the learning information comprises: The learning information is used as the input of a pre-trained recommendation model to obtain the agricultural information to be recommended output by the recommendation model. The recommendation model is used to determine the agricultural information whose matching degree with the target user is greater than or equal to a matching threshold based on the learning information to obtain the agricultural information to be recommended.

5. The agricultural course optimization method according to claim 4, characterized in that: After the agricultural information to be recommended is pushed to the target user, the method further includes: Obtaining recommendation feedback information of the target user for the agricultural information to be recommended; The recommendation model is fine-tuned according to the recommendation feedback information and the corresponding agricultural information to be recommended to obtain the fine-tuned recommendation model.

6. An agricultural course optimization device, characterized in that: include: A learning information acquisition module, used to acquire learning information corresponding to the target user to be recommended, wherein the learning information includes behavior information and / or feedback information of the target user when learning according to the agricultural course; A module for determining agricultural information to be recommended, used for determining agricultural information to be recommended according to the learning information; A push module is used to push the agricultural information to be recommended to the target user.

7. The agricultural course optimization device according to claim 6, characterized in that: The module for determining the agricultural information to be recommended includes: a type determination unit, used to determine a target recommendation type, wherein the target recommendation type is determined according to the learning information and is used to reflect the type of agricultural information whose attention degree of the target user is greater than or equal to an attention threshold; An information determination unit is used to determine the agricultural information to be recommended according to the target recommendation type.

8. The agricultural course optimization device according to claim 6 or 7, characterized in that: The module for determining the agricultural information to be recommended includes: A model prediction unit is used to use the learning information as an input of a pre-trained recommendation model to obtain the agricultural information to be recommended output by the recommendation model. The recommendation model is used to determine the agricultural information whose matching degree with the target user is greater than or equal to a matching threshold based on the learning information to obtain the agricultural information to be recommended.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

10. A computer program product, characterized in that When the computer program product runs on an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 5.

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