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Online course pushing method based on big data

A technology of big data and courses, applied in data processing applications, electronic digital data processing, digital data information retrieval, etc., can solve the problems of inability to analyze the trend of users' selection of courses, and reduce the success rate of pushing courses, so as to improve the success rate. , the effect of improving work efficiency

Inactive Publication Date: 2021-04-30
任杰
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, in the existing technology, it is impossible to analyze the user's selection trend of courses, which leads to a decrease in the success rate of pushing courses

Method used

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  • Online course pushing method based on big data

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Embodiment Construction

[0050] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0051] Such as figure 1 As shown, an online course push method based on big data, the specific steps of the online course push method are as follows:

[0052] Step T1. Users and managers register through the registration and login unit. After successful registration, they log in to the cloud management platform through the mobile terminal, and then obtain the push courses through the course acquisition unit, and send the push courses to the cloud management platform. course analysis;

[0053] Step T2, analyzing and screen...

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Abstract

The invention discloses an online course pushing method based on big data, relates to the technical field of online course pushing, and solves the technical problem that the success rate of course pushing is reduced due to the fact that the course selection trend of a user cannot be analyzed in the prior art. The method comprises the steps of obtaining online courses through a course obtaining unit, then analyzing pushed course popularity data, screening recommended courses, obtaining the pushed course popularity data, obtaining a popularity analysis coefficient Xi of the recommended courses through a formula, and if the popularity analysis coefficient Xi of the recommended courses is greater than or equal to a popularity analysis threshold, marking the corresponding recommended courses as selected recommended courses, after the cloud management platform receives the selected recommended courses, sorting the selected recommended courses according to the descending order of the popularity analysis coefficients, and marking the selected recommended courses ranked the first as pushed courses; primarily screening the pushed courses, analyzing the course selection trend of the user so that the success rate of course pushing is improved.

Description

technical field [0001] The invention relates to the technical field of online course push, in particular to an online course push method based on big data. Background technique [0002] Network education is a modern manifestation of distance education. Based on network technology and combined with excellent educational resources of colleges and universities, the best teachers and best teaching achievements of colleges and universities are spread to all directions. And a certain computer operation ability can learn knowledge. Online education learning is not limited by time and space. Students can learn anytime and anywhere, and they can learn whichever course they want. Online education generally combines online tutoring and face-to-face teaching. Communicate through the platform, answer questions, complete homework, exams, etc. [0003] However, in the prior art, it is impossible to analyze the user's selection trend of courses, which leads to a decrease in the success ra...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06Q10/06G06Q50/20
CPCG06F16/9535G06Q10/06395G06Q50/205
Inventor 任杰
Owner 任杰
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