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A Recommendation Method for Serialization of Learning Process

A recommendation method and sequence technology, applied in the field of serialized recommendation in the learning process, can solve the problems of low efficiency and low recommendation accuracy, and achieve the effect of improving accuracy, improving recommendation accuracy, and improving accuracy.

Active Publication Date: 2018-11-02
HUAZHONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the above problems and deficiencies, provide a learning process sequence recommendation and its optimization method, set weights for the characteristics of the learning process sequence elements, perform personalized learning process recommendation according to sequence feature constraints, and solve the problem of learning process recommendation Technical problems such as low precision and low efficiency

Method used

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Embodiment Construction

[0018] The present invention will be further described below in conjunction with specific embodiments.

[0019] This embodiment provides a learning process sequence recommendation method, and the specific implementation steps are as follows:

[0020] The first step is to generate a recommendation learning process sequence

[0021] Assume that n is the number of potential learning process feature points, m is the learning process sequence that constitutes the activity graph, that is, the number of edges in the activity graph, and k is the number of active point traversal sequences.

[0022] Specific steps are as follows:

[0023] First, generate learning process feature point information. Generate a potential learning process feature point set C, using points to represent feature points, C contains n potential feature points c i . The elements in the set C are all feature points {c 1 , c 2 , c 3 , c 4 ,...,c n}, 1≤i≤n.

[0024] Second, generate utilization probability i...

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Abstract

The present invention relates to the field of information recommendation, and provides a method for serialized information recommendation, including the following steps: (1) generating sequence element feature points; (2) using historical data as a sample set, generating sequence element feature point utilization probabilities as recommended The basic index of sequence evaluation; (3) generate sequence information, (4) calculate the expected value of potential empty-load sequence distance in the sequence activity diagram, and select the one with the smallest potential empty-load distance expected value as the optimal recommended sequence. The method of the invention sets weights for the characteristics of the sequence elements, performs personalized recommendation according to the constraints of the sequence characteristics, and solves technical problems such as low accuracy and low efficiency of serialized information recommendation.

Description

technical field [0001] The invention relates to the field of information recommendation, in particular to a method for serialization recommendation of a learning process and an optimization method thereof, which support information recommendation for a learning process with serialization features. Background technique [0002] With the socialization of information, social informatization, information production has promoted the rapid development of the education industry and educational technology, the Internet has become an important source of knowledge for people to acquire and learn. However, the rapid growth of Internet learning community scale and knowledge information resources has brought about the problem of educational information and knowledge overload. It has become a new application direction to analyze, process and screen, and make practical and personalized learning process recommendations to users. [0003] The learning process is mostly presented in the form...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/9537G06F18/23213
Inventor 叶俊民陈曙李超王继新左明章
Owner HUAZHONG NORMAL UNIV