Comprehensive evaluation management method for campus
By generating a comprehensive campus evaluation through account verification and weighted evaluation information, and combining preference factors and highlighted course information, the system solves the problems of time-consuming and distorted evaluation generation in the existing system, and achieves efficient and accurate personalized evaluation management.
Patent Information
- Application Number
- CN202510275505.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-10
- Publication Date
- 2025-11-18
AI Technical Summary
In the existing campus comprehensive evaluation system, manually generating evaluation forms is time-consuming and prone to errors, while automatic generation by the system leads to distorted evaluation results and a lack of personalization and accuracy.
Trustworthy target users are identified through account information and password verification. The best comprehensive evaluation is generated by combining weighted evaluation information, preference factors, and information on outstanding projects and courses. Bias compensation and repetition rate screening strategies are adopted to ensure the accuracy and personalization of the evaluation.
It improves the efficiency and accuracy of evaluation generation, reduces operational errors, ensures that evaluation results meet personalized needs, and avoids distortion of evaluation results.
Smart Images
Figure CN120975592A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of campus comprehensive evaluation management, in particular to a comprehensive evaluation management method for a campus. BACKGROUND
[0002] Campus course evaluation is a crucial link in the education system, which aims to ensure the effectiveness and quality of courses through systematic and comprehensive evaluation to meet the learning needs of students and promote their all-round development. In the process of campus teaching, in order to facilitate management personnel to master the teaching level of teachers, at the end of the semester, a comprehensive evaluation form is used to let students fill in the evaluation to reflect the teaching level of teachers. Courses should conform to the laws of students' physical and mental development, discipline laws, and have comprehensiveness, scientificity, interest, and meet the requirements of society for talents.
[0003] The existing campus comprehensive evaluation is mostly manually selected by personnel to generate a campus comprehensive evaluation form. Personnel manually generate a large amount of time, and it is easy to cause data errors due to too much data. If the system automatically generates a campus comprehensive evaluation form, it is easy to cause the campus comprehensive evaluation form generated by each person to be the same, resulting in the problem of distorted evaluation results.
[0004] In view of the existing problems, it is necessary to innovate on the basis of the original. SUMMARY
[0005] The purpose of the present application is to provide a comprehensive evaluation management method for a campus to solve the problem of the existing campus comprehensive evaluation in the background art, which is mostly manually selected by personnel to generate a campus comprehensive evaluation form. Personnel manually generate a large amount of time, and it is easy to cause data errors due to too much data. If the system automatically generates a campus comprehensive evaluation form, it is easy to cause the campus comprehensive evaluation form generated by each person to be the same, resulting in the problem of distorted evaluation results.
[0006] To achieve the above purpose, the present application provides the following technical scheme: a comprehensive evaluation management method for a campus, obtaining account information and password information of a target user, determining a trusted target user according to the account information and the password information;
[0007] Obtaining weight evaluation information, preference factor and prominent project course information of the trusted target user in a storage device;
[0008] Generating a best comprehensive evaluation according to the weight evaluation information, the preference factor and the prominent project course information, and executing a deviation compensation strategy;
[0009] The deviation compensation strategy includes:
[0010] The best comprehensive evaluation information and the supplementary correction evaluation information submitted by the trusted target user are obtained, and the best comprehensive evaluation information after the supplementary correction evaluation information is named as optimal comprehensive evaluation information;
[0011] The supplementary correction evaluation information submitted by the trusted target user is obtained, and the content of the supplementary correction evaluation information submitted by the trusted target user is filled into the preference factor to determine the preference factor of the trusted target user.
[0012] As an optional solution of the comprehensive evaluation management method for the campus, the determination of the trusted target user comprises:
[0013] The account code information and the password code information input by the target user into the client terminal are obtained.
[0014] The target user account code information is transmitted to the client terminal storage device, and all the account code information in the client terminal storage device is obtained, and all the account code information is set as a set A, and each piece of account code information in the account code is named as {A1, A2, A3, …, A4}, and the target user account code information is named as B.
[0015] Whether there is the same code information as B in the set A is compared piece by piece.
[0016] If there is the same code information as B in the set A, the code corresponding to the set B in the set A is named as access code information.
[0017] The corresponding access password code information in the access code information is obtained.
[0018] The target user input password code information is compared with the access password code information, and if they are the same, the target user is a trusted target user, and the access to the background storage device is allowed.
[0019] If the target user input password code information is different from the access password code information, at this time, the initial page is returned and the account password error is reminded.
[0020] When there is no account code information the same as B in the set A, at this time, the initial page is returned and the illegal user is reminded.
[0021] As an optional solution of the comprehensive evaluation management method for the campus, the determination of the trusted target user comprises:
[0022] According to the account information of the trusted target user, all the user course information in the storage device in the past i years is obtained.
[0023] The determination of i comprises:
[0024] Obtain all user course information recruitment years, and name all user course information recruitment years as i1, i2, i3, …, in;
[0025] Sort i1, i2, i3, …, in, and remove the maximum value and the minimum value in i1, i2, i3, …, in, name the data of i1, i2, i3, …, in after removing the maximum value and the minimum value as x1, x2, x3, …, and determine the recruitment years x;
[0026]
[0027] Wherein, r is the total number of the maximum value and the minimum value in i1, i2, i3, …, in;
[0028] Before calculating the recruitment years x, the deviation compensation strategy is preferentially executed;
[0029] If, the recruitment years x is normally calculated, and the calculated recruitment years x value is inputted into i;
[0030] If, the sorted i1, i2, i3, …, in is obtained, the maximum value y of the course information recruitment years repetition times is determined, and the maximum value y of the course information recruitment years repetition times is inputted into i;
[0031] According to the course information in the recent i years, the repetition rate P screening strategy is executed;
[0032] The information data not in the repetition rate P range in the course information in the recent i years is removed, and the initial weight evaluation information is obtained;
[0033] According to the initial weight evaluation information, the bias factor determination strategy is executed:
[0034] If there is a bias factor in the initial weight evaluation information, the name of the initial weight evaluation information is changed to weight evaluation information and outputted;
[0035] If there is no bias factor in the initial weight evaluation information, the bias factor determination strategy is executed.
[0036] As an optional solution of the comprehensive evaluation management method for the campus, wherein the bias factor determination strategy comprises:
[0037] Obtain the bias factor information and the bias factor information number T of the trusted target user, and the bias factor information is the evaluation information additionally added by the target user;
[0038] If the bias factor information number T>0, the bias factor information is inputted into the initial weight evaluation information at this time, and the weight evaluation information is obtained;
[0039] If the number of preference factor information entries T = 0, then obtain the preference factor information of all target users and execute the preference factor screening strategy for all target users.
[0040] As an optional solution to the comprehensive evaluation and management method for campuses described in this invention, the screening strategy for all target user preference factors includes:
[0041] Obtain all target user preference factor information and name them D1, D2, D3...Dr respectively;
[0042] The occurrence counts of all target user preference factor information are recorded in D1, D2, D3...Dr, and the repetition counts c1, c2, c3...ct of D1, D2, D3...Dr are obtained.
[0043] By sorting the occurrence frequency of c1, c2, c3...ct, and finally selecting the S most frequently occurring preference factors from c1, c2, c3...ct, and inputting the S most frequently occurring preference factors into the initial weight evaluation information, the separated weight evaluation information is obtained.
[0044] The determination of S includes:
[0045] Obtain D1, D2, D3...Dr, and calculate the screening preference factor V;
[0046]
[0047] Obtain the calculated selection preference factor V and perform integer judgment:
[0048] If the calculated selection preference factor V is an integer, then input the value of V into S;
[0049] If the calculated selection preference factor V is not an integer, then the value of V after rounding to the nearest integer is entered into S.
[0050] Based on the separation weight evaluation information, a separation decision strategy is executed.
[0051] As an optional solution to the comprehensive evaluation and management method for campuses described in this invention, the separation and judgment strategy includes:
[0052] Obtain the separation weight evaluation information and the highlighted project course information, and perform a consistency determination based on the separation weight evaluation information and the highlighted project course information;
[0053] If there is prominent project course information in the separated weight evaluation information, and the proportion of prominent project course information in the separated weight evaluation information exceeds 15%, then the name of the separated weight evaluation information will be changed to weight evaluation information and output.
[0054] If there is prominent project course information in the separation weight evaluation information, and the proportion of prominent project course information in the separation weight evaluation information does not exceed 15%, then the prominent project course information entry judgment will be executed.
[0055] If there is no prominent project course information in the separated weight evaluation information, then the prominent project course information entry strategy will be implemented.
[0056] As an optional solution to the comprehensive evaluation management method for campuses described in this invention, the strategy for emphasizing project course information entry includes:
[0057] Obtain information on outstanding program courses, which includes: first outstanding course information, second outstanding course information, third outstanding course information, and fourth outstanding course information;
[0058] The first, second, third, and fourth highlighted course information are named F1, F2, F3, and F4, respectively, and the ratio of F1, F2, F3, and F4 in the highlighted course information is 1:2:3:4.
[0059] Obtain the first, second, third, and fourth most prominent course information from all target user information;
[0060] And implement the target user key project information filtering strategy according to the proportion of F1, F2, F3 and F4.
[0061] As an optional solution to the comprehensive evaluation and management method for campuses described in this invention, the target user key project screening strategy includes:
[0062] Obtain the first, second, third, and fourth most prominent course information from all target user information;
[0063] The first, second, third, and fourth prominent course information from all the acquired target user information is counted and sorted.
[0064] The first, second, third, and fourth most important course information from all target user information are selected according to the proportions of F1, F2, F3, and F4, and the most important project course information for the target user is finally determined.
[0065] The target user's highlighted project course information is integrated into the separated weight evaluation information to obtain the corrected separated weight evaluation information, and a corrected compensation strategy is implemented.
[0066] As an optional solution to the comprehensive evaluation and management method for campuses described in this invention, the correction and compensation strategy includes:
[0067] Obtain the corrected separation weight evaluation information, and based on the corrected separation weight evaluation information, obtain the target user key project information Q and separation weight evaluation information N from the corrected separation weight evaluation information, and calculate the corrected percentage H;
[0068]
[0069] If the calculated correction ratio H > 0.2, then change the name of the corrected separation weight evaluation information to weight evaluation information and output it.
[0070] If the calculated correction ratio H < 0.2, then obtain the separation weight evaluation information N, calculate and sort the frequency of each evaluation information in the separation weight evaluation information N among all target users, and delete each evaluation information in the separation weight evaluation information N one by one according to the deletion strategy from low to high until H > 0.2, and then change the name of the modified separation weight evaluation information to weight evaluation information and output it.
[0071] As an optional solution to the comprehensive evaluation and management method for campuses described in this invention, the determination of the repetition rate P includes:
[0072] Get the maximum value F of the number of times the course information enrollment years are repeated in the sorted i1, i2, i3...in, and determine the corresponding user course enrollment information content k1, k2, k3...ke based on the maximum value F of the number of times the course information enrollment years are repeated.
[0073] After segmenting the contents of k1, k2, k3...ke and extracting their features, they are denoted as u1, u2, u3...ue respectively;
[0074] Set k1 as the initial comparison template, and calculate the coefficient factors q1, q2, q3...q1 with k1 for each of k2, k3...ke. e-1 And determine the equilibrium coefficient factor Q;
[0075]
[0076] in,
[0077] Obtain the balance coefficient factor Q, and determine the repetition rate P based on the balance coefficient factor Q, where Q≤P≤100%.
[0078] Compared with the prior art, the beneficial effects of the present invention are:
[0079] 1. This comprehensive evaluation management method for campuses identifies whether a target user is trustworthy by matching the target user's account information and password information, and grants trustworthy target users corresponding permissions, thereby improving security. Furthermore, it uses a repetition rate P-screening strategy to remove evaluation information with low usage frequency, thereby reducing the number of times trustworthy target users need to be added or deleted, improving operational efficiency, and effectively avoiding operational errors caused by repeated manual additions or deletions.
[0080] 2. This comprehensive evaluation management method for campuses adopts a separation judgment strategy to assess the proportion of prominent project course information in the separated weight evaluation information. When the proportion is low, it can be intelligently added according to needs, effectively avoiding the generation of comprehensive evaluations that lack prominent project course information, thus preventing evaluation distortion. At the same time, by acquiring the preference factor information of all target users, it effectively avoids generating evaluation information without referring to preference factors, which can easily lead to poor evaluation information accuracy.
[0081] 3. This comprehensive evaluation management method for campuses adopts a screening strategy based on the preferences of all target users to obtain frequently added evaluation information from all target users. This effectively avoids the addition of evaluation information that cannot be intelligently generated in the evaluation management process and has a low usage frequency. Furthermore, it utilizes a separation judgment strategy to evaluate the proportion of prominent project course information in the separated weight evaluation information. When the proportion is low, it can be intelligently added according to needs, effectively preventing the generated comprehensive evaluation from lacking evaluations of prominent project courses. Attached Figure Description
[0082] Figure 1 This is a flowchart of the intelligent evaluation management process of the present invention. Detailed Implementation
[0083] Various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.
[0084] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.
[0085] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.
[0086] Example 1, please refer to the example for details. Figure 1 The present invention provides a technical solution: a comprehensive evaluation management method for campuses, comprising the following steps: obtaining the account information and password information of a target user, and determining a trustworthy target user based on the account information and password information; the account information is a campus comprehensive evaluation management login account, and the password information is a password matching the login account;
[0087] Retrieve weighted evaluation information, preference factors, and highlighted course information of trusted target users from the storage device; trusted target users are those whose login account and password information match; preference factors are evaluation information added by trusted target users; weighted evaluation information is the evaluation information used most frequently by all target users; highlighted course information can be divided into first highlighted course information, second highlighted course information, third highlighted course information, and fourth highlighted course information.
[0088] Based on the weighted evaluation information, the best comprehensive evaluation is generated using preference factors and highlighted project course information, and a bias compensation strategy is implemented.
[0089] Deviation compensation strategies include:
[0090] Obtain the best overall evaluation information and the supplementary evaluation information submitted by trusted target users. Name the best overall evaluation information after supplementing and correcting the evaluation information as the optimal overall evaluation information. The supplementary evaluation information is the additional evaluation information added by trusted target users after they see the best overall evaluation.
[0091] Obtain the correction evaluation information submitted by trusted target users, fill the correction evaluation information submitted by trusted target users into the preference factor, and determine the preference factor of trusted target users.
[0092] The identification of trustworthy target users includes:
[0093] Obtain the account and password encoding information entered into the client terminal by the target user. The encoding information is converted into a computer-recognizable programming language by the computer.
[0094] The target user account code information is transmitted to the client terminal storage device, and all account code information in the client terminal storage device is obtained. All account code information is set as set A, and each account code information in all account codes is named {A1, A2, A3...A4}. The target user account code information is named B.
[0095] Compare each item in set A to see if it contains the same encoded information as B;
[0096] If set A contains the same encoding information as set B, then the encoding information in set A that corresponds to set B is named the access encoding information.
[0097] Retrieve the corresponding access password encoding information from the access encoding information;
[0098] The system compares the target user's entered password encoding information with the access password encoding information. If the two are the same, the target user is a trusted target user and access to the backend storage device is allowed.
[0099] If the password information entered by the target user is different from the access password information, the user is returned to the initial page and a message is displayed indicating that the account or password is incorrect.
[0100] If set A does not contain account code information that is the same as that stored in B, then return to the initial page and alert the unauthorized user.
[0101] By utilizing a mechanism that matches account information and password information, the ease of implementation of comprehensive evaluation management can be effectively improved. When internal data is deleted or modified, it is possible to effectively trace the source. At the same time, it can also record the historical records of evaluation information entered by different users, which makes it easier to intelligently generate personalized evaluation information based on the historical records.
[0102] Obtaining weighted evaluation information of trustworthy target users includes:
[0103] Based on the account information of trusted target users, retrieve the course information of all users for the past i years from the storage device.
[0104] Determining i includes:
[0105] Retrieve the enrollment years of all user course information and name them i1, i2, i3...in, where the enrollment years of user course information is the number of times a single user submits their course information for enrollment using the evaluation management system.
[0106] Sort the values i1, i2, i3...in, and remove the maximum and minimum values from each set. Name the resulting sets of i1, i2, i3...in as x1, x2, x3...x (n-r)The number of years of employment, x, is determined by removing the largest and smallest values from i1, i2, i3...in to reduce the impact of excessive and small data on the calculated number of years of employment. The final number of years of employment, x, is the average number of years of employment, thereby improving the accuracy of the data calculation.
[0107]
[0108] Where r is the total number of the maximum and minimum values in i1, i2, i3...in. Since course evaluation information is entered every year, users using the evaluation management system at the same time may have the same number of evaluations, resulting in multiple users having the same maximum and minimum values.
[0109] Before calculating the number of years of employment (x), the deviation compensation strategy should be implemented first.
[0110] like Calculate the number of years of employment x normally, and input the calculated number of years of employment x into i;
[0111] like Get the sorted i1, i2, i3...in, determine the maximum value y of the number of times the course information enrollment years are repeated in the sorted i1, i2, i3...in, and input the maximum value y of the number of times the course information enrollment years are repeated into i. The course information can be sports. The number of years the user's course information is enrolled is the number of times the course information is entered. This comprehensive evaluation is entered once a year. If it is entered multiple times a year, just divide the calculated data by the number of entries. By executing the deviation compensation strategy before calculating the number of years x, the deviation compensation strategy is used to avoid the removal of the maximum and minimum values when calculating the average enrollment years x, which would result in a large total number of values being removed, thus causing the calculated enrollment years x data to be distorted.
[0112] When removing the maximum and minimum values results in a large total number of removals, in order to avoid data distortion, we select the value y with the largest number of repeated enrollment years of course information in the sorted i1, i2, i3...in to determine i. By adopting this method, we can better reflect the data, avoid extreme effects, and improve the accuracy of the final determined i.
[0113] Based on course information from the past i years, a repetition rate P screening strategy was implemented.
[0114] Remove data from the course information of the past i years that are not within the repetition rate P range to obtain the initial weight evaluation information;
[0115] Based on the initial weight evaluation information, the preference factor determination strategy is executed:
[0116] If there is a preference factor in the initial weight evaluation information, change the name of the initial weight evaluation information to weight evaluation information and output it;
[0117] If there is no preference factor in the initial weight evaluation information, execute the preference factor determination strategy;
[0118] By matching the target user's account information and password information, it is possible to identify whether the target user is a trustworthy user. When the target user is a trustworthy user, the corresponding permissions are granted, such as the ability to add or modify the content and number of evaluation information entries. All users refer to all trustworthy user information recorded in the comprehensive evaluation management system. By utilizing weighted evaluation information, when a trustworthy user needs to use comprehensive evaluation information, it can intelligently select from the evaluation information records of all users and then use a repetition rate P-filtering strategy to remove evaluation information with low usage frequency. This reduces the number of times trustworthy users are added or deleted, improves operational efficiency, and effectively avoids operational errors caused by multiple manual additions or deletions.
[0119] Simultaneously, a preference factor determination strategy is used to determine preference factors. It should be noted that the preference factors of each trusted target user are different. By utilizing preference factors, the accuracy and personalization of the generated evaluation information are increased, effectively avoiding the situation where the evaluation information generated by each trusted target user is the same. It should also be noted that the course information in this technical solution can be set into different first-level and second-level directories according to different courses. For example, sports can be set as the first-level directory, which includes basketball, table tennis, and tennis, and basketball, table tennis, and tennis can be set as second-level targets. This method facilitates later viewing, scoring, and management.
[0120] The various units or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.
[0121] Example 2, please refer to the example for details. Figure 1 Strategies for determining preference factors include:
[0122] Obtain the preference factor information and the number T of preference factor information entries for trusted target users. Preference factor information is additional evaluation information added by the target user, and the number T of preference factor information entries is the number of information entries recorded in the preference factor.
[0123] If the number of preference factor information items T>0, then the preference factor information is input into the initial weight evaluation information to obtain the weight evaluation information;
[0124] If the number of preference factor information entries T = 0, then obtain the preference factor information of all target users and execute the preference factor screening strategy for all target users.
[0125] By employing a preference factor determination strategy, it's possible to identify whether a trusted target user possesses a preference factor. When a target user exhibits a preference factor, personalized evaluation information can be generated based on that factor. However, if the trusted target user is a new user, the preference factor is not present. By acquiring preference factor information from all target users and using it to replace a preferred user when they lack a preference factor, this approach effectively avoids the problem of generating evaluation information without considering preference factors. This avoids the high risk of inaccurate evaluations that often necessitate significant additions or removals of trusted target users, increasing the frequency of user interactions.
[0126] The target user preference factor screening strategy includes:
[0127] Obtain all target user preference factor information and name them D1, D2, D3...Dr respectively;
[0128] The occurrence counts of all target user preference factor information are recorded in D1, D2, D3...Dr, and the repetition counts c1, c2, c3...ct of D1, D2, D3...Dr are obtained.
[0129] By sorting the occurrence frequency of c1, c2, c3...ct, and finally selecting the S most frequently occurring preference factors from c1, c2, c3...ct, and inputting the S most frequently occurring preference factors into the initial weight evaluation information, the separated weight evaluation information is obtained.
[0130] The determination of S includes:
[0131] Obtain D1, D2, D3...Dr, and calculate the screening preference factor V;
[0132]
[0133] Obtain the calculated selection preference factor V and perform integer judgment:
[0134] If the calculated selection preference factor V is an integer, then input the value of V into S;
[0135] If the calculated selection preference factor V is not an integer, then the value of V after rounding to the nearest integer is entered into S.
[0136] By using preference factors to count the frequency of preference factors among all target users, and then determining the selection number S through these preference factors, the selection process is further refined. The number of preference factors is determined by selecting the most frequently repeated preference factors. This effectively avoids selecting infrequently used preference factors, making the final comprehensive evaluation management system more accurate. The preference factor V is the number of preference factors to be selected.
[0137] The weighted evaluation information is the sum of the S most frequently occurring preference factors input into the initial weighted evaluation information;
[0138] By employing a screening strategy based on the preferences of all target users, we can obtain frequently added evaluation information from all target users. This effectively avoids adding evaluation information that is not frequently used in evaluation management. This screening method effectively increases the probability that the provided evaluation information is usable. Furthermore, it effectively avoids the situation where too much personalized evaluation information is added, which could lead to inaccurate final evaluation information. It should be noted that a certain number of evaluation information records can be set in the preference factor. When the number of records exceeds a certain limit, they can be deleted by trusted target users, thereby ensuring the accuracy of the preference factor.
[0139] Based on the separation weight evaluation information, the separation determination strategy is executed;
[0140] Separation decision strategies include:
[0141] Obtain the separation weight evaluation information and the highlighted project course information, and perform a consistency determination based on the separation weight evaluation information and the highlighted project course information;
[0142] If there is prominent project course information in the separated weight evaluation information, and the proportion of prominent project course information in the separated weight evaluation information exceeds 15%, then the name of the separated weight evaluation information will be changed to weight evaluation information and output.
[0143] If there is prominent project course information in the separation weight evaluation information, and the proportion of prominent project course information in the separation weight evaluation information does not exceed 15%, then the prominent project course information entry judgment will be executed.
[0144] If there is no prominent project course information in the separated weight evaluation information, then the prominent project course information entry strategy will be implemented.
[0145] The highlighted project course information refers to courses that are necessary in the near future, and courses that students focus on developing in a specific semester. For example, in physical education, soccer would be a highlighted project course. However, because the highlighted project course information varies from year to year, the number of evaluation items for highlighted project courses in the comprehensive evaluation information is relatively small. By adopting a separation judgment strategy, the proportion of highlighted project course information in the separated weight evaluation information is judged. When the proportion is small, it can be intelligently added according to needs, effectively avoiding the situation where the generated comprehensive evaluation lacks the evaluation of highlighted project courses, resulting in evaluation distortion. It should be noted that those skilled in the art can select the proportion of highlighted project course information in the separated weight evaluation information according to actual needs.
[0146] Those skilled in the art should understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the control methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium can also include combinations of the above types of memory.
[0147] Example 3, please refer to the example for details. Figure 1 The key strategies for entering project course information include:
[0148] Obtain information on key projects and courses, which includes: first key project information, second key project information, third key project information, and fourth key project information. Key projects are those that will be emphasized for development in the near future. For example, football will be added to the teaching in the near future, and football will be the key project. The first key project information, second key project information, third key project information, and fourth key project information are school key projects, district key projects, city key projects, and provincial key projects, respectively. This classification is used to avoid situations where school key sports projects, district key sports projects, city key sports projects, and provincial key sports projects are different.
[0149] The first, second, third, and fourth highlighted course information are named F1, F2, F3, and F4, respectively, and the ratio of F1, F2, F3, and F4 in the highlighted course information is 1:2:3:4. The ratio of F1, F2, F3, and F4 can be selected by those skilled in the art according to actual needs.
[0150] Obtain information on key school projects, key district projects, key municipal projects, and key provincial projects from all target user information;
[0151] And implement a target user key project information filtering strategy based on the proportions of F1, F2, F3, and F4;
[0152] Target user key project selection strategies include:
[0153] The first, second, third, and fourth prominent course information are obtained from all target user information. Here, the first, second, third, and fourth prominent course information are evaluation information.
[0154] The first, second, third, and fourth prominent course information from all the acquired target user information is counted and sorted according to the frequency of occurrence of the evaluation content information.
[0155] The first, second, third, and fourth most prominent course information from all target user information are selected according to the proportions of F1, F2, F3, and F4, and the most prominent course information for the target user is finally determined. The selection method is to select the courses based on their frequency of occurrence from high to low.
[0156] By adopting a target user key project screening strategy, the evaluation information that appears frequently is selected from the comprehensive evaluation information, thereby avoiding the situation where the selected evaluation information appears infrequently, which would lead to poor accuracy of the subsequent comprehensive evaluation.
[0157] The target user's highlighted project course information is integrated into the separated weight evaluation information to obtain the corrected separated weight evaluation information, and a corrected compensation strategy is executed.
[0158] The revised compensation strategy includes:
[0159] Obtain the corrected separation weight evaluation information, and based on the corrected separation weight evaluation information, obtain the target user key project information Q and separation weight evaluation information N from the corrected separation weight evaluation information, and calculate the correction ratio H, which is the ratio of the target user key project information to the separation weight evaluation information.
[0160]
[0161] If the calculated correction ratio H > 0.2, then change the name of the corrected separation weight evaluation information to weight evaluation information and output it.
[0162] If the calculated correction ratio H < 0.2, then obtain the separation weight evaluation information N, calculate and sort the frequency of each evaluation information in the separation weight evaluation information N among all target users, and delete each evaluation information in the separation weight evaluation information N one by one according to the deletion strategy from low to high until H > 0.2, and then change the name of the modified separation weight evaluation information to weight evaluation information and output it.
[0163] By employing a correction and compensation strategy to determine the proportion of key project information Q for target users, the generated comprehensive evaluation information is made less likely to have a low proportion of key projects, thus avoiding situations where trusted target users would need to manually add more information. This approach effectively improves the accuracy of the generated comprehensive evaluation information, reduces the number of times trusted target users need to manually add and delete evaluation information, and consequently reduces the number of operations required by trusted target users, thereby improving efficiency and reducing the error rate. It should be noted that after the correction calculation, there may be cases where each trusted target user generates a different number of comprehensive evaluation information entries. Trusted target users can simply adjust the score of each evaluation information entry according to their needs to achieve the same total score.
[0164] The determination of the repetition rate P includes:
[0165] The maximum value F of the number of times the course information enrollment years are repeated is obtained from i1, i2, i3...in. The median of i1, i2, i3...in is determined by the maximum value F of the number of times the enrollment years are repeated. Since the evaluation management is entered every year and different course instructors will also enter at the same time, the maximum number of years of comprehensive evaluation is selected by the above method. For example, if i1, i2, i3...in is 1, 1, 2, 3, 3, 3, 3, 4, then F is 3. The corresponding user course enrollment information content k1, k2, k3...ke is determined by the maximum value F of the number of times the course information enrollment years are repeated. In this way, as many data as possible are selected in the same year to ensure the accuracy of the subsequent calculation of the repetition rate.
[0166] After segmenting the contents of k1, k2, k3...ke and extracting their features, they are denoted as u1, u2, u3...ue respectively;
[0167] Set k1 as the initial comparison template, and calculate the coefficient factors q1, q2, q3...q1 with k1 for each of k2, k3...ke. e-1And determine the balance coefficient factor Q, where coefficient factor q1 is the repetition rate of k2 and k1, coefficient factor q2 is the repetition rate of k3 and k1, and the balance coefficient factor Q is q1, q2, q3...q e-1 The average similarity;
[0168]
[0169] in, Let k2 be the cosine similarity between k1 and k2. The cosine similarity between k3 and k1 is used to determine the repetition rate p, which facilitates rapid data filtering using the repetition rate P.
[0170] Obtain the balance coefficient factor Q, and determine the repetition rate P based on the balance coefficient factor Q, where Q≤P≤100%.
[0171] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.
[0172] The various units or steps of this invention can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this invention is not limited to any particular combination of hardware and software.
[0173] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.
Claims
1. A comprehensive evaluation and management method for campuses, characterized in that, Includes the following steps: Obtain the target user's account information and password information, and determine the trustworthy target users based on the account information and password information; Obtain weighted evaluation information of trusted target users in storage devices, including preference factors and highlighted project course information; Based on the weighted evaluation information, the best comprehensive evaluation is generated using preference factors and highlighted project course information, and a bias compensation strategy is implemented. Deviation compensation strategies include: Obtain the best comprehensive evaluation information and the corrected evaluation information submitted by trusted target users, and name the best comprehensive evaluation information after supplementing and correcting the evaluation information as the optimal comprehensive evaluation information; Obtain the correction evaluation information submitted by trusted target users, fill the content of the correction evaluation information submitted by trusted target users into the preference factor, and determine the preference factor of trusted target users.
2. The comprehensive evaluation management method for campuses according to claim 1, characterized in that: The identification of trustworthy target users includes: Obtain the account code information and password code information entered by the target user into the client terminal; The target user account code information is transmitted to the client terminal storage device, and all account code information in the client terminal storage device is obtained. All account code information is set as set A, and each account code information in all account codes is named {A1, A2, A3...A4}. The target user account code information is named B. Compare each item in set A to see if it contains the same encoded information as B; If set A contains the same encoding information as set B, then the encoding information in set A that corresponds to set B is named the access encoding information. Retrieve the corresponding access password encoding information from the access encoding information; The system compares the target user's entered password encoding information with the access password encoding information. If the two are the same, the target user is a trusted target user and access to the backend storage device is allowed. If the password information entered by the target user is different from the access password information, the user will be returned to the initial page and a message will be displayed indicating that the account or password is incorrect. If set A does not contain account code information that is the same as that stored in B, the system returns to the initial page and alerts the unauthorized user.
3. The comprehensive evaluation management method for campuses according to claim 2, characterized in that: Obtaining weighted evaluation information of trustworthy target users includes: Based on the account information of trusted target users, obtain the course information of all users for the past i years from the storage device; Determining i includes: Retrieve the enrollment years of all user course information and name them i1, i2, i3...in; Sort the values i1, i2, i3...in, and remove the maximum and minimum values from each set. Name the resulting sets of i1, i2, i3...in as x1, x2, x3...x n-r Determine the number of years of employment, x; Where r is the total number of the maximum and minimum values in i1, i2, i3...in; Before calculating the number of years of employment (x), the deviation compensation strategy should be implemented first. like Calculate the number of years of employment x normally, and input the calculated number of years of employment x into i; like Get the sorted i1, i2, i3...in, determine the maximum value y of the number of times the course information enrollment years are repeated in the sorted i1, i2, i3...in, and input the maximum value y of the number of times the course information enrollment years are repeated into i; Based on course information from the past i years, a repetition rate P screening strategy was implemented. Remove data from the course information of the past i years that are not within the repetition rate P range to obtain the initial weight evaluation information; Based on the initial weight evaluation information, the preference factor determination strategy is executed: If there is a preference factor in the initial weight evaluation information, change the name of the initial weight evaluation information to weight evaluation information and output it; If there is no preference factor in the initial weight evaluation information, execute the preference factor determination strategy.
4. The comprehensive evaluation management method for campuses according to claim 3, characterized in that: Strategies for determining preference factors include: Obtain information on the preference factors of trusted target users and the number of preference factor entries T; If the number of preference factor information items T>0, then the preference factor information is input into the initial weight evaluation information to obtain the weight evaluation information; If the number of preference factor information entries T = 0, then obtain the preference factor information of all target users and execute the preference factor screening strategy for all target users.
5. The comprehensive evaluation management method for campuses according to claim 4, characterized in that: The target user preference factor screening strategy includes: Obtain all target user preference factor information and name them D1, D2, D3...Dr respectively; The occurrence counts of all target user preference factor information are recorded in D1, D2, D3...Dr, and the repetition counts c1, c2, c3...ct of D1, D2, D3...Dr are obtained. By sorting the occurrence frequency of c1, c2, c3...ct, and finally selecting the S most frequently occurring preference factors from c1, c2, c3...ct, and inputting the S most frequently occurring preference factors into the initial weight evaluation information, the separated weight evaluation information is obtained. The determination of S includes: Obtain D1, D2, D3...Dr, and calculate the screening preference factor V; Obtain the calculated selection preference factor V and perform integer judgment: If the calculated selection preference factor V is an integer, then input the value of V into S; If the calculated selection preference factor V is not an integer, then the value of V after rounding to the nearest integer is entered into S. Based on the separation weight evaluation information, a separation decision strategy is executed.
6. The comprehensive evaluation management method for campuses according to claim 5, characterized in that: Separation decision strategies include: Obtain the separation weight evaluation information and the highlighted project course information, and perform a consistency determination based on the separation weight evaluation information and the highlighted project course information; If there is prominent project course information in the separated weight evaluation information, and the proportion of prominent project course information in the separated weight evaluation information exceeds 15%, then the name of the separated weight evaluation information will be changed to weight evaluation information and output. If there is prominent project course information in the separation weight evaluation information, and the proportion of prominent project course information in the separation weight evaluation information does not exceed 15%, then the prominent project course information entry judgment will be executed. If there is no prominent project course information in the separated weight evaluation information, then the prominent project course information entry strategy will be implemented.
7. The comprehensive evaluation management method for campuses according to claim 6, characterized in that: The key strategies for entering project course information include: Obtain information on outstanding program courses, which includes: first outstanding course information, second outstanding course information, third outstanding course information, and fourth outstanding course information; The first, second, third, and fourth highlighted course information are named F1, F2, F3, and F4, respectively, and the ratio of F1, F2, F3, and F4 in the highlighted course information is 1:2:3:
4. Obtain the first, second, third, and fourth most prominent course information from all target user information; And implement the target user key project information filtering strategy according to the proportion of F1, F2, F3 and F4.
8. The comprehensive evaluation management method for campuses according to claim 7, characterized in that: Target user key project selection strategies include: Obtain the first, second, third, and fourth most prominent course information from all target user information; The first, second, third, and fourth prominent course information from all the acquired target user information is counted and sorted. The first, second, third, and fourth most important course information from all target user information are selected according to the proportions of F1, F1, F3, and F4, and the most important course information for the target user is finally determined. The target user's highlighted project course information is integrated into the separated weight evaluation information to obtain the corrected separated weight evaluation information, and a corrected compensation strategy is implemented.
9. The comprehensive evaluation management method for campuses according to claim 8, characterized in that: The revised compensation strategy includes: Obtain the corrected separation weight evaluation information, and based on the corrected separation weight evaluation information, obtain the target user key project information Q and separation weight evaluation information N from the corrected separation weight evaluation information, and calculate the corrected percentage H; If the calculated correction ratio H > 0.2, then change the name of the corrected separation weight evaluation information to weight evaluation information and output it. If the calculated correction ratio H < 0.2, then obtain the separation weight evaluation information N, calculate and sort the frequency of each evaluation information in the separation weight evaluation information N among all target users, and delete each evaluation information in the separation weight evaluation information N one by one according to the deletion strategy from low to high until H > 0.2, and then change the name of the modified separation weight evaluation information to weight evaluation information and output it.
10. The comprehensive evaluation management method for campuses according to claim 3, characterized in that: The determination of the repetition rate P includes: Get the maximum value F of the number of times the course information enrollment years are repeated in the sorted i1, i2, i3...in, and determine the corresponding user course enrollment information content k1, k2, k3...ke based on the maximum value F of the number of times the course information enrollment years are repeated. After segmenting the contents of k1, k2, k3...ke and extracting their features, they are denoted as u1, u2, u3...ue respectively; Set k1 as the initial comparison template, and calculate the coefficient factors q1, q2, q3...q1 with k1 for each of k2, k3...ke. e-1 And determine the equilibrium coefficient factor Q; in, Obtain the balance coefficient factor Q, and determine the repetition rate P based on the balance coefficient factor Q, where Q≤P≤100%.