Automatic learning resource recommendation method based on mobile learning

A technology for learning resources and recommending methods, applied in instruments, data processing applications, business, etc., and can solve problems such as insufficient research

Active Publication Date: 2018-03-09
EAST INNER MONGOLIA ELECTRIC POWER COMPANY +2
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  • Application Information

AI Technical Summary

Problems solved by technology

[0008] Aiming at the problems that the mobile learning platform recommends different learning resources to different users, the effect is not good, and the current related technology research is not deep enough, etc., the technical solution of the present invention is a method for automatically recommending learning resources based on mobile learning, including the following steps:

Method used

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  • Automatic learning resource recommendation method based on mobile learning
  • Automatic learning resource recommendation method based on mobile learning
  • Automatic learning resource recommendation method based on mobile learning

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Embodiment Construction

[0066] In specific implementation, the technical solution provided by the present invention can be used by a person skilled in the art to implement an automatic operation process using computer software technology. The technical solution of the present invention will be described in detail below with reference to the drawings and embodiments.

[0067] Such as figure 1 As shown, the data of the mobile learning platform mainly includes the four elements of user, resource, time, and location, and these four elements will constantly change with time, location, and user. At the same time, users' interests are also affected by personal family background, education level, occupation, geographic location, mood, friends, colleagues and other factors, and their preferences for different learning resources are also very different. In order to dig out these invisible attributes and analyze their influence on interest preferences, it is necessary to establish user attributes, resource attrib...

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Abstract

The invention belongs to the research category of learning resource recommendation in interest recommendation research systems in social networks and relates to an automatic learning resource recommendation method based on mobile learning. The user learning interest discovery problem of a mobile user learning platform is solved by establishing models, the user learning interest problem is regardedas a track feature discovery problem of user learning recourses in time and position dimensions, users with the same resource interest are regarded as a resource user group, the next resource that users may learn is predicted in the perspectives of user learning tracks and learning characteristics of resource user groups, and the learning interests of the users can be discovered.

Description

Technical field [0001] The present invention belongs to the research category of interest recommendation, and relates to technical fields such as collaborative filtering recommendation, content-based recommendation, and context-aware recommendation. In particular, a method for automatically recommending learning resources based on mobile learning is proposed. Background technique [0002] Baidu Encyclopedia: Personalized recommendation is to recommend information and products that users are interested in based on the user's interest characteristics and purchase behavior. With the continuous expansion of the scale of e-commerce, the number and types of products have grown rapidly, and customers need to spend a lot of time to find the products they want to buy. This process of browsing a large amount of irrelevant information and products will undoubtedly cause the loss of consumers who are drowning in the problem of information overload. In order to solve these problems, a person...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q30/06
CPCG06F16/9535G06F16/9537G06Q30/0631
Inventor 姜国义刘海波杨倩倩李文震康凯龚庆武乔卉
Owner EAST INNER MONGOLIA ELECTRIC POWER COMPANY
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