An adaptive allocation method for online classes based on member portraits

Abstract

The present invention relates to the technical field of online adaptive allocation, and discloses an Internet online classroom adaptive allocation method based on member portraits, comprising: obtaining target data of a target person, forming allocation data through a course screening strategy to determine an online course to be pushed to the target person, pushing target exercises to the target person according to the allocation data, and determining the target person's adaptability to the target course. The Internet online classroom adaptive allocation method based on member portraits preliminarily screens the corresponding online courses according to the age of the target person, and judges the target person's adaptability to different teaching styles according to the target person's answer accuracy rate and corresponding score ranking of the target pushed exercises corresponding to online courses with different teaching styles, so that the target person can find a teaching style that suits him / her, so as to accurately push online courses to the target person, thereby improving learning efficiency and enhancing learning effects.

Description

Technical Field

[0001] The present invention relates to the technical field of online adaptive allocation, and in particular to an Internet online classroom adaptive allocation method based on member portraits. Background Art

[0002] The adaptive allocation method of online classes on the Internet based on member portraits refers to the use of Internet technology to achieve intelligent allocation and personalized recommendation of online class resources and teaching content based on students' individual characteristics and learning needs. This method provides students with the most appropriate and effective learning content and resources by analyzing multi-dimensional data such as students' personal information, learning habits, interests, hobbies, and knowledge levels. It usually includes individual information collection, data analysis and model construction, personalized resource matching, and real-time feedback and adjustment. It can help students learn more effectively, improve learning effects and interest, and reduce the teaching burden of teachers to achieve personalized education.

[0003] The existing member portrait-based adaptive allocation method for Internet online classes cannot preliminarily screen the corresponding online courses according to the age of the target person through the different age groups to which the age belongs, thereby narrowing the scope of online courses so as to accurately push online courses to the target person. It cannot judge the target person's adaptability to the first target pushed course and make adjustments based on the target person's correct answer rate to the target pushed exercises. It cannot judge the target person's adaptability to different teaching styles based on the target person's answer to the target pushed exercises corresponding to online courses with different teaching styles, so that the target person can find a teaching style that suits him / her, thereby improving learning efficiency and learning effects. Its practicality also has certain limitations. Summary of the invention

[0004] The present invention provides an Internet online classroom adaptive allocation method based on member portraits, which is used to promote the solution of the problems raised in the background technology.

[0005] The present invention provides the following technical solution: an Internet online classroom adaptive allocation method based on member portraits, comprising:

[0006] Get the target data of the target person;

[0007] The target data includes the age of the target person, and the corresponding online courses are preliminarily screened according to the different age groups to which the age belongs;

[0008] Based on the target data, the course screening strategy is used to form allocation data to determine the online courses to be pushed to the target person;

[0009] According to the distribution data, push target exercises to the target person to determine the target person's adaptability to the target course.

[0010] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, the course screening strategy specifically includes:

[0011] Get the age of the target person and set it as the target age;

[0012] Get the online course type;

[0013] Get the age group corresponding to each online course type;

[0014] Get the course type selected by the target person and set it as the target course type;

[0015] If the target age belongs to the first age group, the first course set is extracted;

[0016] Extracting a first type subset corresponding to the target course type in the first course set, and defining it as the target type subset;

[0017] If the target age belongs to the second age group, extract the second course set;

[0018] Extracting a second type subset corresponding to the target course type in the second course set, and defining it as the target type subset;

[0019] If the target age belongs to the third age group, the third course set is extracted;

[0020] Extracting the third type subset corresponding to the target course type in the third course set, and defining it as the target type subset;

[0021] Get the number of views of all online courses in the target type subset, denoted as G;

[0022] Extract the views of any two online courses in turn and compare them, denoted as G1 and G2 respectively;

[0023] If the pageviews G1>the pageviews G2, the pageviews G1 is set as the first pageviews and the pageviews G2 is set as the second pageviews;

[0024] The online course corresponding to the first number of views finally determined is set as the first target push course;

[0025] Extract the first target push course and push it to the target person.

[0026] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, the method of obtaining the type of online courses specifically includes:

[0027] Get all online courses;

[0028] Extract the test points of each online course and set them as target test points, denoted as C;

[0029] Set the first age group, denoted as (A1, B1);

[0030] Set the second age group, denoted as (A2, B2);

[0031] Set the third age group, recorded as (A3, B3);

[0032] The test points of the first age group, the second age group, and the third age group are obtained respectively, and a first course set, a second course set, and a third course set are formed accordingly; according to the test points of the age group to which the target test points belong, the online courses corresponding to the target test points are included in the course set formed corresponding to the test points of the age group.

[0033] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, wherein: the obtaining of online course types further includes:

[0034] The first course set includes two first type subsets, which are respectively denoted as D1 and D2;

[0035] Sequentially extract any two target test points from the target test points of all online courses in the first course set for comparison, and record them as C11 and C12 respectively;

[0036] If the target test point C11 = the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively;

[0037] Compare the target test point C11 with the first type subset D1 and the first type subset D2;

[0038] List the online courses corresponding to the target test sites C11 and C12 into the first type subset D1 or D2 corresponding to the test sites of the first type subset to which the target test site C11 belongs;

[0039] If the target test point C11≠the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively;

[0040] Compare the target test point C11 and the target test point C12 with the first type subset D1 and the first type subset D2 respectively;

[0041] The online courses corresponding to the target test point C11 are included in the first type subset D1 or D2 corresponding to the test points of the first type subset to which the target test point C11 belongs; the online courses corresponding to the target test point C12 are included in the first type subset D2 or D1 corresponding to the test points of the first type subset to which the target test point C12 belongs.

[0042] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, wherein: the obtaining of online course types further includes:

[0043] The second course set includes two second type subsets, which are respectively denoted as E1 and E2;

[0044] Sequentially extract any two target test points from the target test points of all online courses in the second course set for comparison, and record them as C21 and C22 respectively;

[0045] If the target test point C21 = the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively;

[0046] Compare the target test point C21 with the second type subset E1 and the second type subset E2;

[0047] List the online courses corresponding to the target test sites C21 and C22 into the second type subset E1 or E2 corresponding to the test sites of the second type subset to which the target test site C21 belongs;

[0048] If the target test point C21≠the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively;

[0049] Compare the target test point C21 and the target test point C22 with the second type subset E1 and the second type subset E2 respectively;

[0050] The online courses corresponding to the target test point C21 are included in the second type subset E1 or E2 corresponding to the test points of the second type subset to which the target test point C21 belongs; the online courses corresponding to the target test point C22 are included in the second type subset E2 or E1 corresponding to the test points of the second type subset to which the target test point C22 belongs.

[0051] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, wherein: the obtaining of online course types further includes:

[0052] The third course set includes two third type subsets, which are respectively denoted as F1 and F2;

[0053] Sequentially extract any two target test points from the target test points of all online courses in the third course set for comparison, and record them as C31 and C32 respectively;

[0054] If the target test point C31 = the target test point C32, then all test points under the third type subset F1 and the third type subset F2 are obtained respectively;

[0055] Compare the target test point C31 with the third type subset F1 and the third type subset F2;

[0056] List the online courses corresponding to the target test sites C31 and C32 into the third type subset F1 or F2 corresponding to the test sites of the third type subset to which the target test site C31 belongs;

[0057] If the target test point C31≠the target test point C32, then all the test points under the third type subset F1 and the third type subset F2 are obtained respectively;

[0058] Compare the target test point C31 and the target test point C32 with the third type subset F1 and the third type subset F2 respectively;

[0059] The online courses corresponding to the target test point C31 are included in the third type subset F1 or F2 corresponding to the test points of the third type subset to which the target test point C31 belongs; the online courses corresponding to the target test point C32 are included in the third type subset F2 or F1 corresponding to the test points of the third type subset to which the target test point C32 belongs.

[0060] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, the method of pushing target exercises to target persons according to the allocation data and determining the adaptability of the target persons to the target courses is specifically as follows:

[0061] S1, obtaining the time point when the target person opens the first target pushed course, which is set as the initial time point, recorded as T1;

[0062] S2, obtaining the time point when the target person closes the first target push course, and setting it as the termination time point, recorded as T2;

[0063] S3, obtaining the duration of the first target pushed course, setting it as the target duration, recorded as T3;

[0064] S4. If the initial time point T1 + target duration T3 > the end time point T2, then execute the course replacement strategy;

[0065] S5. If the initial time point T1+the target duration T3=the end time point T2, then obtain the test question bank;

[0066] S6, obtaining the target test point corresponding to the first target pushed course and setting it as the target test point;

[0067] S7, extracting all exercises containing target test points in the test question bank and defining them as target exercises;

[0068] S8, obtaining the number of target test points included in each target exercise, recorded as H;

[0069] S9, setting the judgment value;

[0070] S10, if the number H = the judgment value, then the target exercise is determined as the target push exercise;

[0071] S11, extracting all target push exercises from the target exercises to form a target push exercise set;

[0072] S12, setting the push quantity;

[0073] S13, extracting a push quantity of target push exercises from the target push exercise set and pushing them to a target person so that the target person can practice;

[0074] S14, obtaining the score of each target pushed exercise, recorded as I1;

[0075] S15, obtaining the answer score of the target person for each target pushed exercise, recorded as I2;

[0076] S16, setting the score determination value;

[0077] S17. If the score I1 - the answer score I2 = the score determination value, then the answer is determined to be correct;

[0078] S18, if the score I1 - the answer score I2> the score judgment value, then the answer is judged to be wrong;

[0079] S19, obtaining the number of target pushed exercises that are judged to be answered correctly, recorded as J;

[0080] S20, if the number J ÷ the number of pushes is less than 60%, it is determined that the target person has low adaptability to the first target push course;

[0081] S21. Implement course replacement strategy;

[0082] S22. If the number J ÷ the number of pushes > 60%, it is determined that the target person has a high adaptability to the first target push course;

[0083] S23, obtaining the teaching style of the first target pushed course and setting it as the target teaching style;

[0084] S24, obtaining the teaching styles of all online courses in the target type subset;

[0085] S25, extracting online courses with the same teaching style as the target teaching style and setting them as the first target courses;

[0086] S26, continue to push the first target course to the target person for learning;

[0087] S27. Execute S1-S26.

[0088] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, the course replacement strategy is specifically as follows:

[0089] Obtain target teaching style;

[0090] Get the teaching styles of all online courses in the target type subset;

[0091] Extract all first target courses in the target type subset;

[0092] Extract the target test points corresponding to the first target push course and set them as target screening test points;

[0093] The target type subset excluding all first target courses and target screening test points is defined as the target push set;

[0094] Get the number of views of all online courses in the target push set, denoted as K;

[0095] The page views K of all online courses in the target push set are sorted from large to small according to the page views value, and the online course corresponding to the largest page views value is set as the second target push course;

[0096] Extract the second target push course and push it to the target person;

[0097] At this time, the second target pushed course is transformed into the first target pushed course, and S1-S27 are executed.

[0098] As an optional solution of the method for adaptively allocating Internet online classes based on member portraits of the present invention, wherein: according to the allocation data, the target exercises are pushed to the target person, and the adaptability of the target person to the target course is determined, and further includes:

[0099] Execute S1-S19;

[0100] Calculate the total score of the target person's answers to the target push exercises of the first target push course, recorded as L1, the total score L1 = ∑(I2 1-1 +I2 2-1 +...+I2 J-1 );

[0101] Calculate the total score of the target person's answers to the target push exercises of the second target push course, recorded as L2, the total score L2 = ∑(I2 1-2 +I2 2-2 +...+I2 J-2 );

[0102] The lecturer who gets the first target course push will be designated as the first lecturer;

[0103] Get the lecturer of the second target course and set him as the second lecturer;

[0104] If the total score L1 - the total score L2 > the score determination value, it is determined that the target person has a high adaptability to the first target push course;

[0105] Execute S23-S27;

[0106] If the total score L1 - total score L2 < the score judgment value, it is judged that the target person has a high adaptability to the second target push course;

[0107] At this time, the second target push course is transformed into the first target push course, and S23-S27 are executed;

[0108] If the total score L1 - the total score L2 = the score determination value, then the number of students who study the first target push course under the first lecturer and the number of students who study the second target push course under the second lecturer are obtained, which are recorded as N1 and N2 respectively, where the number N1 and the number N2 are both the number of students including the target person;

[0109] Get the total score L1 of each student of the first lecturer on the target push exercises of the first target push course;

[0110] According to the value of each total score L1, sort them from large to small to form the first ranking order;

[0111] Extract the target person's total score L1 in the first ranking order and set it as the first place, recorded as P1;

[0112] Get the total score L2 of each student of the second lecturer on the target push exercises of the second target push course;

[0113] According to the value of each total score L2, sort them from large to small to form a second ranking order;

[0114] Extract the target person's total score L2 in the second ranking order and set it as the second place, recorded as P2;

[0115] If the first ranking P1 is lower than the second ranking P2, it is determined that the target person has a high adaptability to the first target push course;

[0116] Execute S23-S27;

[0117] If the first ranking P1> the second ranking P2, it is determined that the target person has a high adaptability to the second target push course;

[0118] At this time, the second target pushed course is transformed into the first target pushed course, and S23-S27 are executed.

[0119] The present invention has the following beneficial effects:

[0120] 1. The method for adaptively allocating online courses on the Internet based on member portraits preliminarily screens the corresponding online courses according to the age of the target person and the different age groups to which the person belongs, thereby narrowing the scope of online courses so as to accurately push online courses to the target person.

[0121] 2. The member portrait-based adaptive allocation method for online Internet classes determines the target person's adaptability to the first target pushed course and makes adaptive adjustments according to the target person's correct answer rate to the target pushed exercises, so that the target person can find a teaching style that suits him / her, thereby improving learning efficiency and enhancing learning effects.

[0122] 3. The method for adaptively allocating Internet online classes based on member portraits pushes online courses with different teaching styles to the target person when the target person chooses different test sites for study, and pushes corresponding target push exercises after class. At the same time, the scores of the lecturers of each online course and all students studying the lecturer's online course are obtained respectively. The score ranking is obtained according to the target person's answer scores for the target push exercises of different test sites, so as to judge the target person's adaptability to different teaching styles and make adaptive adjustments, so that the target person can find a teaching style that suits him / her, thereby improving learning efficiency and improving learning effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0123] Figure 1 It is a block diagram of the method for adaptively allocating Internet online classes based on member portraits of the present invention;

[0124] Figure 2 It is a schematic diagram of the first course set, the second course set, and the third course set of the present invention. DETAILED DESCRIPTION

[0125] Embodiment 1, an adaptive allocation method for an Internet online class based on member portraits, see Figure 1 ,include:

[0126] Get the target data of the target person;

[0127] The target data includes the age of the target person, and the corresponding online courses are preliminarily screened according to the different age groups to which the age belongs;

[0128] Based on the target data, the course screening strategy is used to form allocation data to determine the online courses to be pushed to the target person;

[0129] According to the distribution data, push target exercises to the target person to determine the target person's adaptability to the target course.

[0130] Through the above method, the corresponding online courses are preliminarily screened according to the different age groups to which the target person belongs, thereby narrowing the scope of online courses, and judging the target person's adaptability to different teaching styles according to the target person's correct answer rate of the target pushed exercises corresponding to the online courses with different teaching styles, and the corresponding grade ranking, so that the target person can find a teaching style that suits him / her, and make adaptive adjustments, so as to accurately push online courses to the target person, and at the same time, improve learning efficiency and enhance learning effects.

[0131] Embodiment 2: This embodiment is an improvement made on the basis of embodiment 1. Figure 2 , the method for adaptively allocating Internet online classes based on member portraits, the course screening strategy specifically includes:

[0132] Get the age of the target person and set it as the target age;

[0133] Get the online course type;

[0134] Get the age group corresponding to each online course type;

[0135] Get the course type selected by the target person and set it as the target course type;

[0136] If the target age belongs to the first age group, the first course set is extracted;

[0137] Extracting a first type subset corresponding to the target course type in the first course set, and defining it as the target type subset;

[0138] If the target age belongs to the second age group, extract the second course set;

[0139] Extracting a second type subset corresponding to the target course type in the second course set, and defining it as the target type subset;

[0140] If the target age belongs to the third age group, the third course set is extracted;

[0141] Extracting the third type subset corresponding to the target course type in the third course set, and defining it as the target type subset;

[0142] Get the number of views of all online courses in the target type subset, denoted as G;

[0143] Extract the views of any two online courses in turn and compare them, denoted as G1 and G2 respectively;

[0144] If the pageviews G1>the pageviews G2, the pageviews G1 is set as the first pageviews and the pageviews G2 is set as the second pageviews;

[0145] The online course corresponding to the first number of views finally determined is set as the first target push course;

[0146] Extract the first target push course and push it to the target person.

[0147] The obtaining of online course types specifically includes:

[0148] Get all online courses;

[0149] Extract the test points of each online course and set them as target test points, denoted as C;

[0150] Set the first age group, denoted as (A1, B1), the first age group is 12-18 years old, that is, the age group of students receiving secondary education;

[0151] Set the second age group, denoted as (A2, B2), the second age group is 18-22 years old, that is, the age group of students receiving higher education;

[0152] Set the third age group, recorded as (A3, B3), the third age group is over 22 years old, that is, the age group of people who have participated in work;

[0153] The test points of the first age group, the second age group, and the third age group are obtained respectively, and a first course set, a second course set, and a third course set are formed accordingly; according to the test point of the age group to which the target test point belongs, the online course corresponding to the target test point is included in the course set formed corresponding to the test point of the age group; the first course set is a set of explanations or extension courses on the test points that students of the first age group need to master for the purpose of further studies; the second course set is a set of explanations or extension courses on the professional theoretical knowledge test points that students of the second age group need to master for the purpose of completing the course; the third course set is a set of explanations or extension courses on the professional skill knowledge test points that people of the third age group need to master for the purpose of career advancement.

[0154] Wherein, obtaining the online course type also includes:

[0155] The first course set includes two first type subsets, which are respectively denoted as D1 and D2;

[0156] Sequentially extract any two target test points from the target test points of all online courses in the first course set for comparison, and record them as C11 and C12 respectively;

[0157] If the target test point C11 = the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively;

[0158] Compare the target test point C11 with the first type subset D1 and the first type subset D2;

[0159] The online courses corresponding to the target test sites C11 and C12 are included in the first type subset D1 or D2 corresponding to the test sites of the first type subset to which the target test site C11 belongs. If the target test site C11 belongs to the test sites of the first type subset D1, the online courses corresponding to the target test sites C11 and C12 are included in the first type subset D1.

[0160] If the target test point C11≠the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively;

[0161] Compare the target test point C11 and the target test point C12 with the first type subset D1 and the first type subset D2 respectively;

[0162] The online courses corresponding to the target test point C11 are included in the first type subset D1 or D2 corresponding to the test points of the first type subset to which the target test point C11 belongs, and the online courses corresponding to the target test point C12 are included in the first type subset D2 or D1 corresponding to the test points of the first type subset to which the target test point C12 belongs. If the target test point C11 belongs to the test points of the first type subset D1 and the target test point C12 belongs to the test points of the first type subset D2, then the online courses corresponding to the target test point C11 are included in the first type subset D1, and the online courses corresponding to the target test point C12 are included in the first type subset D2.

[0163] Wherein, obtaining the online course type also includes:

[0164] The second course set includes two second type subsets, which are respectively denoted as E1 and E2;

[0165] Sequentially extract any two target test points from the target test points of all online courses in the second course set for comparison, and record them as C21 and C22 respectively;

[0166] If the target test point C21 = the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively;

[0167] Compare the target test point C21 with the second type subset E1 and the second type subset E2;

[0168] The online courses corresponding to the target test sites C21 and C22 are included in the second type subset E1 or E2 corresponding to the test sites of the second type subset to which the target test site C21 belongs. If the target test site C21 belongs to the test site of the second type subset E1, the online courses corresponding to the target test sites C21 and C22 are included in the second type subset E1;

[0169] If the target test point C21≠the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively;

[0170] Compare the target test point C21 and the target test point C22 with the second type subset E1 and the second type subset E2 respectively;

[0171] The online courses corresponding to the target test point C21 are included in the second type subset E1 or E2 corresponding to the test points of the second type subset to which the target test point C21 belongs, and the online courses corresponding to the target test point C22 are included in the second type subset E2 or E1 corresponding to the test points of the second type subset to which the target test point C22 belongs. If the target test point C21 belongs to the test point of the second type subset E1 and the target test point C22 belongs to the test point of the second type subset E2, then the online courses corresponding to the target test point C21 are included in the second type subset E1, and the online courses corresponding to the target test point C22 are included in the second type subset E2.

[0172] Wherein, obtaining the online course type also includes:

[0173] The third course set includes two third type subsets, which are respectively denoted as F1 and F2;

[0174] Sequentially extract any two target test points from the target test points of all online courses in the third course set for comparison, and record them as C31 and C32 respectively;

[0175] If the target test point C31 = the target test point C32, then all test points under the third type subset F1 and the third type subset F2 are obtained respectively;

[0176] Compare the target test point C31 with the third type subset F1 and the third type subset F2;

[0177] The online courses corresponding to the target test sites C31 and C32 are included in the third type subset F1 or F2 corresponding to the test sites of the third type subset to which the target test site C31 belongs. If the target test site C31 belongs to the test sites of the third type subset F1, the online courses corresponding to the target test sites C31 and C32 are included in the third type subset F1.

[0178] If the target test point C31≠the target test point C32, then all the test points under the third type subset F1 and the third type subset F2 are obtained respectively;

[0179] Compare the target test point C31 and the target test point C32 with the third type subset F1 and the third type subset F2 respectively;

[0180] The online courses corresponding to the target test point C31 are included in the third type subset F1 or F2 corresponding to the test points of the third type subset to which the target test point C31 belongs, and the online courses corresponding to the target test point C32 are included in the third type subset F2 or F1 corresponding to the test points of the third type subset to which the target test point C32 belongs. If the target test point C31 belongs to the test point of the third type subset F1 and the target test point C32 belongs to the test point of the third type subset F2, then the online courses corresponding to the target test point C31 are included in the third type subset F1, and the online courses corresponding to the target test point C32 are included in the third type subset F2.

[0181] Embodiment 3: This embodiment is an improvement made on the basis of embodiment 2. In this embodiment, according to the allocation data, the target exercises are pushed to the target person, and the adaptability of the target person to the target course is determined, specifically:

[0182] S1, obtaining the time point when the target person opens the first target pushed course, which is set as the initial time point, recorded as T1;

[0183] S2, obtaining the time point when the target person closes the first target push course, and setting it as the termination time point, recorded as T2;

[0184] S3, obtaining the duration of the first target pushed course, setting it as the target duration, recorded as T3;

[0185] S4. If the initial time point T1 + target duration T3 > the end time point T2, then execute the course replacement strategy;

[0186] S5. If the initial time point T1+the target duration T3=the end time point T2, then obtain a test question bank, which is used to determine the target person's mastery of the test points explained or expanded by the first target push course, and the target person's adaptability to the progress explained by the first target push course;

[0187] S6, obtaining the target test point corresponding to the first target pushed course and setting it as the target test point;

[0188] S7, extracting all exercises containing target test points in the test question bank and defining them as target exercises;

[0189] S8, obtaining the number of target test points included in each target exercise, recorded as H;

[0190] S9, setting a determination value, wherein the determination value is 1, for determining whether the target exercise is a question for practicing the target test point, that is, determining whether the target exercise is an exercise that only includes the target test point;

[0191] S10, if the number H = the judgment value, then the target exercise is determined as the target push exercise;

[0192] S11, extracting all target push exercises from the target exercises to form a target push exercise set;

[0193] S12, setting the push quantity, which is the push quantity of after-class exercises set by the target user according to his / her own learning situation;

[0194] S13, extracting a push quantity of target push exercises from the target push exercise set and pushing them to a target person so that the target person can practice;

[0195] S14, obtaining the score of each target pushed exercise, recorded as I1;

[0196] S15, obtaining the answer score of the target person for each target pushed exercise, recorded as I2;

[0197] S16, setting a score determination value, wherein the score determination value is 0, for determining whether the target person's answer to the target pushed exercise is correct;

[0198] S17. If the score I1 - the answer score I2 = the score determination value, then the answer is determined to be correct;

[0199] S18, if the score I1 - the answer score I2> the score judgment value, then the answer is judged to be wrong;

[0200] S19, obtaining the number of target pushed exercises that are judged to be answered correctly, recorded as J;

[0201] S20, if the number J ÷ the number of pushes is less than 60%, it is determined that the target person has low adaptability to the first target push course;

[0202] S21. Implement course replacement strategy;

[0203] S22. If the number J ÷ the number of pushes > 60%, it is determined that the target person has a high adaptability to the first target push course;

[0204] S23, obtaining the teaching style of the first target pushed course and setting it as the target teaching style;

[0205] S24, obtaining the teaching styles of all online courses in the target type subset;

[0206] S25, extracting online courses with the same teaching style as the target teaching style and setting them as the first target courses;

[0207] S26, continue to push the first target course to the target person for learning;

[0208] S27. Execute S1-S26.

[0209] This embodiment also provides that the course replacement strategy is specifically:

[0210] Obtain target teaching style;

[0211] Get the teaching styles of all online courses in the target type subset;

[0212] Extract all first target courses in the target type subset;

[0213] Extract the target test points corresponding to the first target push course and set them as target screening test points;

[0214] The target type subset excluding all first target courses and target screening test points is defined as the target push set;

[0215] Get the number of views of all online courses in the target push set, denoted as K;

[0216] The page views K of all online courses in the target push set are sorted from large to small according to the page views value, and the online course corresponding to the largest page views value is set as the second target push course;

[0217] Extract the second target push course and push it to the target person;

[0218] At this time, the second target pushed course is transformed into the first target pushed course, and S1-S27 are executed.

[0219] This embodiment also provides that, according to the allocation data, the target exercises are pushed to the target person, and the adaptability of the target person to the target course is determined, further comprising:

[0220] Execute S1-S19;

[0221] Calculate the total score of the target person's answers to the target push exercises of the first target push course, recorded as L1, the total score L1 = ∑(I2 1-1 +I2 2-1 +...+I2 J-1 );

[0222] Calculate the total score of the target person's answers to the target push exercises of the second target push course, recorded as L2, the total score L2 = ∑(I2 1-2 +I2 2-2+...+I2 J-2 );

[0223] The lecturer who gets the first target course push will be designated as the first lecturer;

[0224] Get the lecturer of the second target course and set him as the second lecturer;

[0225] If the total score L1 - the total score L2 > the score determination value, it is determined that the target person has a high adaptability to the first target push course;

[0226] Execute S23-S27;

[0227] If the total score L1 - total score L2 < the score judgment value, it is judged that the target person has a high adaptability to the second target push course;

[0228] At this time, the second target push course is transformed into the first target push course, and S23-S27 are executed;

[0229] If the total score L1 - the total score L2 = the score determination value, then the number of students who study the first target push course under the first lecturer and the number of students who study the second target push course under the second lecturer are obtained, which are recorded as N1 and N2 respectively, where the number N1 and the number N2 are both the number of students including the target person;

[0230] Get the total score L1 of each student of the first lecturer on the target push exercises of the first target push course;

[0231] According to the value of each total score L1, sort them from large to small to form the first ranking order;

[0232] Extract the target person's total score L1 in the first ranking order and set it as the first place, recorded as P1;

[0233] Get the total score L2 of each student of the second lecturer on the target push exercises of the second target push course;

[0234] According to the value of each total score L2, sort them from large to small to form a second ranking order;

[0235] Extract the target person's total score L2 in the second ranking order and set it as the second place, recorded as P2;

[0236] If the first ranking P1 is less than the second ranking P2, it is determined that the target person has a high adaptability to the first target pushed course, that is, the value of the first ranking P1 is less than the value of the second ranking P2. If the first ranking is the first, then the first ranking P1 is 1, and the second ranking is the fifth, then the second ranking P2 is 5, which means that the target person has a high adaptability to the teaching style of the first target pushed course, that is, the target person is more suitable for the teaching style of the first target pushed course, and then the online course with the same or similar teaching style as the first target pushed course will be pushed later;

[0237] Execute S23-S27;

[0238] If the first ranking P1> the second ranking P2, it is determined that the target person has a high adaptability to the second target push course, that is, the value of the first ranking P1 is greater than the value of the second ranking P2. For example, if the first ranking is the fifth, the first ranking P1 is 5, and if the second ranking is the first, the second ranking P2 is 1, which means that the target person has a high adaptability to the teaching style of the second target push course, that is, the target person is more suitable for the teaching style of the second target push course, and then the online course with the same or similar teaching style as the second target push course will be pushed later;

[0239] At this time, the second target pushed course is transformed into the first target pushed course, and S23-S27 are executed.

[0240] In this embodiment, the corresponding online courses are preliminarily screened according to the different age groups to which the target person belongs, thereby narrowing the scope of the online courses, and judging the adaptability of the target person to different teaching styles according to the target push exercises' answer accuracy rate and the corresponding grade ranking corresponding to the online courses with different teaching styles, so that the target person can find a teaching style that suits him / her, and thus make adaptive adjustments, so as to accurately push online courses to the target person, and at the same time, improve learning efficiency and enhance learning effects.

Claims

1. An adaptive allocation method for online classes based on member portraits, characterized by: include: Get the target data of the target person; The target data includes the age of the target person, and the corresponding online courses are preliminarily screened according to the different age groups to which the age belongs; Based on the target data, the course screening strategy is used to form allocation data to determine the online courses to be pushed to the target person; According to the distribution data, push exercises to the target person to determine the target person's adaptability to the target course; The course selection strategy specifically includes: Get the age of the target person and set it as the target age; Get the online course type; Get the age group corresponding to each online course type; Get the course type selected by the target person and set it as the target course type; If the target age belongs to the first age group, extract the first course set; Extracting a first type subset corresponding to the target course type in the first course set, and defining it as the target type subset; If the target age belongs to the second age group, extract the second course set; Extracting a second type subset corresponding to the target course type in the second course set, and defining it as the target type subset; If the target age belongs to the third age group, the third course set is extracted; Extracting the third type subset corresponding to the target course type in the third course set, and defining it as the target type subset; Get the number of views of all online courses in the target type subset, denoted as G; Extract the views of any two online courses in turn and compare them, denoted as G1 and G2 respectively; If the pageviews G1>the pageviews G2, the pageviews G1 is set as the first pageviews and the pageviews G2 is set as the second pageviews; The online course corresponding to the first number of views finally determined is set as the first target push course; Extract the first target push course and push it to the target person; The online course types obtained specifically include: Get all online courses; Extract the test points of each online course and set them as target test points, denoted as C; Set the first age group, denoted as (A1, B1); Set the second age group, denoted as (A2, B2); Set the third age group, recorded as (A3, B3); The test points of the first age group, the second age group, and the third age group are obtained respectively, and a first course set, a second course set, and a third course set are formed accordingly; according to the test points of the age group to which the target test points belong, the online courses corresponding to the target test points are included in the course set formed corresponding to the test points of the age group.

2. The method for adaptively allocating Internet online classes based on member portraits according to claim 1 is characterized by: The obtaining of online course types also includes: The first course set includes two first type subsets, which are respectively denoted as D1 and D2; Sequentially extract any two target test points from the target test points of all online courses in the first course set for comparison, and record them as C11 and C12 respectively; If the target test point C11 = the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively; Compare the target test point C11 with the first type subset D1 and the first type subset D2; List the online courses corresponding to the target test sites C11 and C12 into the first type subset D1 or D2 corresponding to the test sites of the first type subset to which the target test site C11 belongs; If the target test point C11≠the target test point C12, then all test points under the first type subset D1 and the first type subset D2 are obtained respectively; Compare the target test point C11 and the target test point C12 with the first type subset D1 and the first type subset D2 respectively; The online courses corresponding to the target test point C11 are included in the first type subset D1 or D2 corresponding to the test points of the first type subset to which the target test point C11 belongs; the online courses corresponding to the target test point C12 are included in the first type subset D2 or D1 corresponding to the test points of the first type subset to which the target test point C12 belongs.

3. The method for adaptively allocating Internet online classes based on member portraits according to claim 2 is characterized by: The obtaining of online course types also includes: The second course set includes two second type subsets, which are respectively denoted as E1 and E2; Sequentially extract any two target test points from the target test points of all online courses in the second course set for comparison, and record them as C21 and C22 respectively; If the target test point C21 = the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively; Compare the target test point C21 with the second type subset E1 and the second type subset E2; List the online courses corresponding to the target test sites C21 and C22 into the second type subset E1 or E2 corresponding to the test sites of the second type subset to which the target test site C21 belongs; If the target test point C21≠the target test point C22, then all test points under the second type subset E1 and the second type subset E2 are obtained respectively; Compare the target test point C21 and the target test point C22 with the second type subset E1 and the second type subset E2 respectively; The online courses corresponding to the target test point C21 are included in the second type subset E1 or E2 corresponding to the test points of the second type subset to which the target test point C21 belongs; the online courses corresponding to the target test point C22 are included in the second type subset E2 or E1 corresponding to the test points of the second type subset to which the target test point C22 belongs.

4. The method for adaptively allocating Internet online classes based on member portraits according to claim 3 is characterized by: The obtaining of online course types also includes: The third course set includes two third type subsets, which are respectively denoted as F1 and F2; Sequentially extract any two target test points from the target test points of all online courses in the third course set for comparison, and record them as C31 and C32 respectively; If the target test point C31 = the target test point C32, then all test points under the third type subset F1 and the third type subset F2 are obtained respectively; Compare the target test point C31 with the third type subset F1 and the third type subset F2; List the online courses corresponding to the target test sites C31 and C32 into the third type subset F1 or F2 corresponding to the test sites of the third type subset to which the target test site C31 belongs; If the target test point C31≠the target test point C32, then all the test points under the third type subset F1 and the third type subset F2 are obtained respectively; Compare the target test point C31 and the target test point C32 with the third type subset F1 and the third type subset F2 respectively; The online courses corresponding to the target test point C31 are included in the third type subset F1 or F2 corresponding to the test points of the third type subset to which the target test point C31 belongs; the online courses corresponding to the target test point C32 are included in the third type subset F2 or F1 corresponding to the test points of the third type subset to which the target test point C32 belongs.

5. The method for adaptively allocating Internet online classes based on member portraits according to claim 1 is characterized by: The method of pushing target exercises to the target person based on the assigned data and determining the adaptability of the target person to the target course is as follows: S1, obtaining the time point when the target person opens the first target pushed course, which is set as the initial time point, recorded as T1; S2, obtaining the time point when the target person closes the first target push course, and setting it as the termination time point, recorded as T2; S3, obtaining the duration of the first target pushed course, setting it as the target duration, recorded as T3; S4, if the initial time point T1 + target duration T3 > end time point T2, then implement the course replacement strategy; S5. If the initial time point T1 + the target duration T3 = the end time point T2, then obtain the test question bank; S6, obtaining the target test point corresponding to the first target pushed course and setting it as the target test point; S7, extracting all exercises containing target test points in the test question bank and defining them as target exercises; S8, obtaining the number of target test points included in each target exercise, recorded as H; S9, setting the judgment value; S10, if the number H = the judgment value, then the target exercise is determined as the target push exercise; S11, extracting all target push exercises from the target exercises to form a target push exercise set; S12, setting the push quantity; S13, extracting a push quantity of target push exercises from the target push exercise set and pushing them to a target person so that the target person can practice; S14, obtaining the score of each target pushed exercise, recorded as I1; S15, obtaining the answer score of the target person for each target pushed exercise, recorded as I2; S16, setting the score determination value; S17. If the score I1 - the answer score I2 = the score determination value, then the answer is determined to be correct; S18, if the score I1 - the answer score I2> the score judgment value, then the answer is judged to be wrong; S19, obtaining the number of target pushed exercises that are judged to be answered correctly, recorded as J; S20, if the number J ÷ the number of pushes is less than 60%, it is determined that the target person has low adaptability to the first target push course; S21. Implement course replacement strategy; S22. If the number J ÷ the number of pushes is greater than 60%, it is determined that the target person has a high degree of adaptability to the first target push course; S23, obtaining the teaching style of the first target pushed course and setting it as the target teaching style; S24, obtaining the teaching styles of all online courses in the target type subset; S25, extracting online courses with the same teaching style as the target teaching style and setting them as the first target courses; S26, continue to push the first target course to the target person for learning; S27. Execute S1-S26.

6. The method for adaptively allocating Internet online classes based on member portraits according to claim 5 is characterized by: The implementation of the course replacement strategy is specifically as follows: Obtain target teaching style; Get the teaching styles of all online courses in the target type subset; Extract all first target courses in the target type subset; Extract the target test points corresponding to the first target push course and set them as target screening test points; The target type subset excluding all first target courses and target screening test points is defined as the target push set; Get the number of views of all online courses in the target push set, denoted as K; The page views K of all online courses in the target push set are sorted from large to small according to the page views value, and the online course corresponding to the largest page views value is set as the second target push course; Extract the second target push course and push it to the target person; At this time, the second target pushed course is transformed into the first target pushed course, and S1-S27 are executed.

7. The method for adaptively allocating Internet online classes based on member portraits according to claim 6 is characterized by: The method of pushing target exercises to the target person according to the assigned data and determining the adaptability of the target person to the target course also includes: Execute S1-S19; Calculate the total score of the target person's answers to the target push exercises of the first target push course, recorded as L1, the total score L1 = ∑ (I2 1-1 +I2 2-1 +...+I2 J-1 ), the I2 1-1 The answer score of the first question of the first target push course exercise, the I2 2-1 The answer score of the second question of the target push exercise for the first target push course, the I2 J-1 The answer score of the Jth question of the target pushed exercise for the first target pushed course, that is, the total score L1 is the sum of the answer scores I2 of all target pushed exercises of the first target pushed course for the target person; Calculate the total score of the target person's answers to the target push exercises of the second target push course, recorded as L2, the total score L2 = ∑ (I2 1-2 +I2 2-2 +...+I2 J-2 ), the I2 1-2 The answer score of the first question of the target push exercise for the second target push course, the I2 2-2 The answer score of the second question of the target push exercise for the second target push course, the I2 J-2 The answer score of the Jth question of the target push exercise for the second target push course, that is, the total score L2 is the sum of the answer scores I2 of all target push exercises of the second target push course for the target person; The lecturer who gets the first target course push will be designated as the first lecturer; Get the lecturer of the second target course and set him as the second lecturer; If the total score L1 - the total score L2 > the score determination value, it is determined that the target person has a high adaptability to the first target push course; Execute S23-S27; If the total score L1 - total score L2 < the score judgment value, it is judged that the target person has a high adaptability to the second target push course; At this time, the second target push course is transformed into the first target push course, and S23-S27 are executed; If the total score L1 - the total score L2 = the score determination value, then the number of students who study the first target push course under the first lecturer and the number of students who study the second target push course under the second lecturer are obtained, which are recorded as N1 and N2 respectively, where the number N1 and the number N2 are both the number of students including the target person; Get the total score L1 of each student of the first lecturer on the target push exercises of the first target push course; According to the value of each total score L1, sort them from large to small to form the first ranking order; Extract the target person's total score L1 in the first ranking order and set it as the first place, recorded as P1; Get the total score L2 of each student of the second lecturer on the target push exercises of the second target push course; According to the value of each total score L2, sort them from large to small to form a second ranking order; Extract the target person's total score L2 in the second ranking order and set it as the second place, recorded as P2; If the first ranking P1 is lower than the second ranking P2, it is determined that the target person has a high adaptability to the first target push course; Execute S23-S27; If the first ranking P1> the second ranking P2, it is determined that the target person has a high adaptability to the second target push course; At this time, the second target pushed course is transformed into the first target pushed course, and S23-S27 are executed.

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