Course recommendation method and system based on students' attributes

A recommendation method and recommendation system technology, applied in the field of course recommendation method and system based on student attributes, can solve problems such as unrealistic course recommendation, achieve accurate course recommendation, high recall rate and coverage rate, and weaken the effect of importance

Inactive Publication Date: 2015-06-03
PEKING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0012] The purpose of the present invention is to provide a course recommendation method and system based on student attributes, which can effective...

Method used

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  • Course recommendation method and system based on students' attributes
  • Course recommendation method and system based on students' attributes
  • Course recommendation method and system based on students' attributes

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0055] Embodiment 1 of the present invention: a course recommendation method based on student attributes, such as Figure 5 shown, including the following steps:

[0056] S1, assuming that students with the same attributes have similar preferences for courses, and students with similar grades of completed courses have similar strengths; classify students according to attributes (including professional characteristics, grades of completed courses, and categories of courses). Clustering processing; determine the class to which the target student belongs, and calculate the similarity between the target student and other students in the class, and find the "neighbor" student set similar to the target student's course selection preferences; among them, the improved cosine similarity formula is used Calculate the similarity between the target student u and other students v in the class:

[0057]

[0058] Among them, w uv Represents the similarity between student u and student v...

Embodiment 2

[0070] Example 2: A course recommendation method based on student attributes, such as Figure 5 shown, including the following steps:

[0071] S1, according to the student's attributes, calculate the similarity between the target student and other students, and find the set of "neighbor" students who are similar to the target student's course selection preferences; among them, use the improved cosine similarity formula to calculate the target student u and other students v The similarity between:

[0072]

[0073] Among them, w uv Represents the similarity between student u and student v, N(u) and N(v) respectively represent the set of courses that student u and student v have taken, and the factor 1 / (log1+|N(i)|) is used to reduce the student The impact of professional courses on the similarity in the list of courses of common interest between u and student v, N(i) represents the set of all students who have chosen course i;

[0074] S2, Find the course i that the targe...

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PUM

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Abstract

The invention discloses a course recommendation method based on students' attributes. The course recommendation method comprises the following steps: S1, calculating the similarity between target students and other students according to the students' attributes and finding out a 'neighbor' student collection similar to the target students in elective hobby; S2, finding out courses which are not elected by the target students but elected by 'neighbor' students to recommend. According to the course recommendation method, based on students' attribute data, more accurate course recommendation can be realized, and meanwhile, higher recall rate and coverage rate are obtained.

Description

technical field [0001] The invention relates to a recommendation method and system, in particular to a course recommendation method and system based on student attributes. Background technique [0002] With the rapid development of Internet technology, the problem of information overload needs to be solved urgently. Users hope to quickly and accurately obtain the required information from massive amounts of information, while information creators hope that their information can be quickly discovered and applied in massive amounts of data. In this case, Internet technology has developed rapidly in e-commerce from the initial classification directory to search engine and then to recommendation engine. Among them, recommendation engine has been the focus of academic and industrial research in recent years. Recommendation engine has realized Active interaction between users and information, "guessing" the content that users are interested in and recommending through user behavi...

Claims

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Application Information

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IPC IPC(8): G06Q50/20G06F17/30
CPCG06Q50/205
Inventor 沈苗
Owner PEKING UNIV
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