Method and System for Mining Positive and Negative Patterns of Courses Based on Item Weighting and Item Set Correlation Degree
A technology of pattern mining and correlation degree, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of not considering the importance of different courses, not solving the problem of matrix weighted negative correlation pattern mining, and the large number of correlation patterns And other issues
Inactive Publication Date: 2017-06-13
GUANGXI COLLEGE OF EDUCATION
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The characteristic of this method is that each project is treated in an equal and consistent manner, and only the frequency of the project is considered. Its defect is that it only considers the elective relationship of courses when mining, and does not consider the different importance of courses, let alone the electives of students. Post-course teaching effects (i.e. course test scores)
The defect of the weighted association rule mining method for educational data is that it only considers the importance between courses, and does not consider the influence of course test scores.
The defect of the existing fully weighted association rule mining method for educational data is: the existing method can only mine the fully weighted positive association rule pattern, and does not solve the problem of matrix weighted negative association pattern mining. In addition, the association pattern mined by the existing method The number is still huge, which increases the difficulty for users to choose the desired mode. There are still many boring, false and invalid association modes, and it is difficult to raise its technology to the application level
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[0114]Example: Table 1 is an example of a course item library, and Table 2 is an example of a student course information database for students' elective courses, that is, there are 5 course items, 5 student information records, and the achievement weights of each course item, where the achievement weights have been Perform normalization processing so that it is between 0 and 1, the grade of courses without electives is 0, and the grade of courses with full marks is 1.
[0115]
[0116] Adopt the mining method of the present invention to this course information data instance excavation matrix weighted curriculum positive and negative correlation pattern, its mining process is as follows (ms=0.50, mc=0.35, mFr=0.5, mNr=0.6, mi=0.25, β=0.15):
[0117] 1. Mining matrix weighted feature words frequent 1_itemset L 1 , as shown in Table 1, where n=5.
[0118] C 1
w(C 1 )
mwS(C 1 )
(i 1 )
3.24 0.648 (i 2 )
3.27 0.654 (i 3 )
2.92 0.58...
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The invention discloses a course positive and negative mode excavation method and a course positive and negative mode excavation system based on item weighing and item set association degree. The method comprises the steps of preprocessing educational administration data through an educational administration preprocessing module; generating a course candidate item set through a course item set mode generation module, calculating the supporting degree of the course candidate item set to obtain a course frequent item set and a negative item set, and performing item set cutting according to the association degree of the course frequent item set and the negative item set so as to obtain an interesting course frequent item set and a negative item set; calculating a course association rule interesting degree and a confidence coefficient through a course positive and negative association rule mode generation module, and excavating a matrix weighing course high positive and negative association rule from the course frequent item set and the negative item set; displaying a course mode to a user through a course positive and negative association mode display module for analysis and use by the user. According to the method disclosed by the invention, the course candidate item sets and the excavation time are obviously reduced, so that appearance of ineffective course association modes is avoided, and the excavation efficiency is greatly improved; the mode supplies a scientific basis to educational administration management, decision making and educational reformation.
Description
technical field [0001] The invention belongs to the field of educational data mining, specifically a method and system for mining positive and negative patterns of courses based on item weighting and item set correlation degree, which is applicable to the discovery of positive and negative correlation patterns of educational data courses, and its pattern can be used for teaching reform and education management , Decisions provide a scientific basis. The invention is applied to the educational affairs management system of colleges and universities, and can expand the educational affairs management function, and its association mode can help teachers improve and adjust methods, improve teaching quality, and at the same time, can help students improve learning effects. Background technique [0002] The unweighted association pattern mining method of educational data, the weighted association rule mining method of educational data and the weighted association rule mining method ...
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IPC IPC(8): G06F17/30G06Q50/20
CPCG06F16/2462G06Q50/205
Inventor 黄名选韦吉锋
Owner GUANGXI COLLEGE OF EDUCATION