Multifunctional processing method and device for academic journals of ministry of education discipline classification

Abstract

This invention discloses a multi-functional processing method and apparatus for academic journals classified by the Ministry of Education's subject categories. Belonging to the field of multi-functional processing technology for journal classification, it incorporates several evaluation parameters, including full-text views, journal impact factor, citation rate, and number of publications, comprehensively reflecting various aspects of the journal. Parameter pre-processing and standardization utilize logical pre-processing and standardization methods to ensure the accuracy and synchronicity of the values. Distinguishing factor calculation: by calculating the variation of each parameter and the distinguishing factor, the distinguishing factors of the journal are numerically analyzed. Global score presentation: based on the distinguishing factors and keyness, a global score is calculated to present the journal's quality status. In summary, this invention's multi-functional processing method for academic journals classified by the Ministry of Education's subject categories can significantly improve the logic and efficiency of journal management within the subject classification subsystem, providing multi-functional support for the subject classification subsystem in complex journal application environments.

Description

Technical Field

[0001] This invention belongs to the field of multifunctional processing technology for journal classification, specifically relating to a multifunctional processing method and apparatus for academic journals classified by the Ministry of Education. Background Technology

[0002] As mentioned in the prior art solution with patent publication number "CN112989070B", its subject classification subsystem is used to classify journals in the basic database according to different subjects of the Ministry of Education, so as to achieve the goal of subject alignment.

[0003] As can be seen from the above, current subject classification subsystems are generally only used for classifying journals with a single function. They lack the ability to analyze all evaluation parameters for several types of journals and lack efficient parameter preprocessing and standardization methods. As a result, journal quality is not easily guaranteed, which is not conducive to the accuracy of subsequent analysis and planning. At present, subject classification subsystems also lack flexible estimation parameter frameworks and differential factor calculation methods, making it difficult to reflect the overall quality status of journals in a global and accurate manner. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a multifunctional processing method and apparatus for academic journals classified by the Ministry of Education's subject categories. It incorporates several evaluation parameters, including full-text views, journal impact factor, citation rate, and publication volume, comprehensively reflecting various aspects of the journal. Parameter preprocessing and standardization utilize logical preprocessing and standardization methods to ensure numerical accuracy and synchronicity. Distinguishing factor calculation quantifies the journal's distinguishing qualities by calculating the variations in various parameters and distinguishing factors. Global score presentation displays the journal's quality status based on a global score calculated using distinguishing factors and keyness. In summary, this invention's multifunctional processing method for academic journals classified by the Ministry of Education's subject categories significantly improves the logic and efficiency of journal management within the subject classification subsystem, providing multifunctional support for the subsystem in complex journal application environments.

[0005] The present invention employs the following technical solution.

[0006] A multi-functional processing method for academic journals based on the Ministry of Education's subject classification includes:

[0007] The subject classification subsystem categorizes journals in the basic database according to different subjects of the Ministry of Education, achieving the goal of subject alignment;

[0008] The multi-functional processing method for academic journals based on the Ministry of Education's subject classification also includes:

[0009] Step 1: Collect the numerical values ​​of the evaluation parameters for each type of journal;

[0010] Step 2: Perform preprocessing and standardization on the values ​​collected in Step 1;

[0011] Step 3: Calculate the change in each evaluation parameter based on its historical values ​​for the specified time period. And change into a distinguishing factor ;

[0012] Step 4, differentiate the parameters by their distinguishing factors. Corresponding keyness Multiply to obtain the overall estimated score. ;

[0013] Step 5: Use the obtained global assessment score to characterize the overall quality status of the journal.

[0014] Furthermore, in Step 1, the evaluation parameters include a set of values ​​formed by the journal's full-text views, journal impact factor, citation rate, and number of publications.

[0015] Furthermore, in Step 2, normalization is performed using the following equations:

[0016] Here, For the source value, The mean of the set of values ​​is . The variance of the numerical group, This is the normalized value.

[0017] Furthermore, in Step 2, the equation Inside:

[0018] Source values The values ​​collected within the value group;

[0019] mean This is the mean of all values ​​within the data set;

[0020] variance To reflect the dispersion of the values, the mean value represents the magnitude of the deviation of the values ​​from the mean.

[0021] Furthermore, in Step 3, the change is transformed into a distinguishing factor. The operational equation is: and Here, and These are the parameter values ​​for the current time period and the previous time period, respectively. It is a pattern that associates changes with distinguishing factors.

[0022] Furthermore, in Step 3, the equation and Inside:

[0023] The parameter value is for the current time period; The parameter value is from the previous time period;

[0024] Change This represents the change between two consecutive points in time; it indicates the magnitude of the change in the parameter value of the current period relative to the change in the previous period, expressed as a change in magnitude. A ratio is obtained, where a ratio higher than zero represents an increase, a ratio lower than zero represents a decrease, or a ratio of zero represents a constant.

[0025] A pattern used to represent changes Associated with the distinguishing factor This factor is used to compare the relative strengths of different parameters.

[0026] Furthermore, in Step 4, the equation for estimating the score is: Here, The number of parameters;

[0027] Equation for estimating scores Inside:

[0028] The differential factor for each parameter represents the magnitude of the effect of the change in that parameter on the overall differential value of the journal.

[0029] criticality This demonstrates the critical importance of each parameter in the overall estimation;

[0030] Accumulated amount of criticality It is one.

[0031] Furthermore, in Step 5, the obtained global estimation score of the journal is... The value is parsed, and if it is less than a predefined threshold... When this happens, the journal will be displayed as low-quality on the subject classification subsystem's screen, and the journal can be removed from its classification category or marked as low-quality.

[0032] Furthermore, Step 5 also includes: obtaining the Pearson coefficient. ,use The value is used to determine the level of influence of each parameter, here It is the first The Pearson coefficient of each parameter and the global estimated score;

[0033] Correlation coefficient Representing the The correlation between each parameter and the global estimated score;

[0034] Furthermore, in Step 3, the variation is correlated with the pattern of the distinguishing factor. This is a segmentation mode that divides the variable into different ranges based on whether the variable is above or below zero and its modulus, and assigns a unique distinguishing factor value to each range; specifically:

[0035] Change States that are higher than zero or lower than zero:

[0036] Positive change: represents an increase in the parameter;

[0037] Negative change: represents a decrease in the parameter;

[0038] Modulus of the variable High or low: based on the modulus of the change. , and divide it into different ranges;

[0039] Changes Divided into several ranges;

[0040] Set a dedicated differentiation factor for each range from low to high.

[0041] An optimized processing device for electronic information includes:

[0042] Subject classification subsystem: The subject classification subsystem classifies journals in the basic database according to different subjects of the Ministry of Education, so as to achieve the goal of subject alignment;

[0043] The subject classification subsystem also includes;

[0044] The aggregation module is used to aggregate the values ​​of evaluation parameters for various types of journals;

[0045] The standardization module is used to perform preprocessing and standardization on the collected data;

[0046] The calculation module is used to calculate the change in each evaluation parameter based on its historical values ​​over a set time period. And change into a distinguishing factor ;

[0047] The estimation module is used to calculate the distinguishing factors of each parameter. Corresponding keyness Multiply to obtain the overall estimated score. ;

[0048] The quality module is used to characterize the overall quality status of journals based on the obtained global estimated scores.

[0049] The beneficial effects of the present invention are as follows: Compared with the prior art, the technical effects of the present invention include:

[0050] Several evaluation parameters are collected, including full-text views, journal impact factor, citation rate, and number of publications, comprehensively reflecting various aspects of the journal. Parameter preprocessing and standardization: Logical preprocessing and standardization methods ensure the accuracy and synchronicity of the values. Distinguishing factor calculation: By calculating the changes in each parameter and the distinguishing factor, the distinguishing factors of the journal are numerically analyzed. Global score presentation: The journal's quality status is presented based on a global score calculated according to the distinguishing factors and keyness. In summary, this invention's multi-functional processing method for academic journals in the Ministry of Education's subject classification system can significantly improve the logic and efficiency of journal management within the subject classification subsystem, providing multi-functional support for the subject classification subsystem in complex journal application environments. Attached Figure Description

[0051] Figure 1 This is a partial flowchart of the multi-functional processing method for academic journals based on the Ministry of Education's subject classification, as described in this invention.

[0052] Figure 2 This is a partial structural schematic diagram of the multifunctional processing device for academic journals based on the Ministry of Education's subject classification, as described in this invention. Detailed Implementation

[0053] Currently, subject classification subsystems are generally only used for classifying journals with a single function. They lack the ability to analyze all evaluation parameters for several types of journals and lack efficient parameter preprocessing and standardization methods. As a result, it is not easy to guarantee the quality of journals and it is not conducive to the accuracy of subsequent analysis and planning. At present, subject classification subsystems also lack flexible estimation parameter frameworks and differential factor calculation methods, making it difficult to reflect the overall quality status of journals in a global and accurate manner.

[0054] Therefore, the efficient multi-functional processing method for academic journals based on the Ministry of Education's subject classification of this invention can perform all the aggregation, preprocessing, standardization and analysis of the evaluation parameters of various types of journals, and through the estimation parameter framework and differential factor calculation of several types, it can provide accurate journal quality estimation, which is beneficial to the accuracy of subsequent analysis and planning. This multi-functional processing method for academic journals based on the Ministry of Education's subject classification can improve the efficiency and accuracy of parameter processing.

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, any other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0056] like Figure 1 As shown, the multi-functional processing method for academic journals based on the Ministry of Education's subject classification, as described in this invention, includes:

[0057] The subject classification subsystem categorizes journals in the basic database according to different subjects of the Ministry of Education, achieving the goal of subject alignment;

[0058] The multi-functional processing method for academic journals based on the Ministry of Education's subject classification also includes:

[0059] Step 1: Collect the numerical values ​​of the evaluation parameters for each type of journal;

[0060] In a preferred but non-limiting embodiment of the present invention, in Step 1, the values ​​of the evaluation parameters include a set of values ​​formed by the journal's full-text views, journal impact factor, citation rate, and number of publications.

[0061] By using a basic database, corresponding values ​​can be obtained from a set of values, including the journal's full-text views, impact factor, citation rate, and number of publications, ensuring the completeness and accuracy of the data.

[0062] Step 2: Perform preprocessing and standardization on the values ​​collected in Step 1;

[0063] In a preferred but non-limiting embodiment of the present invention, in Step 2, normalization is performed using the following equation:

[0064] Here, For the source value, The mean of the set of values ​​is . The variance of the numerical group, This is the normalized value.

[0065] In a preferred but non-limiting embodiment of the present invention, in Step 2, the equation Inside:

[0066] Source values This refers to the numerical values ​​collected within a numerical group, much like the full-text views of a journal article.

[0067] mean It is the mean of all values ​​in the value group, representing the trend of the midpoint of the values;

[0068] variance To reflect the dispersion of the values, the mean value represents the magnitude of the deviation of the values ​​from the mean.

[0069] Normalization is achieved by subtracting the mean from the source value and then dividing by the variance, thus transforming the source value into a bell-shaped curve with a mean of zero and a variance of one.

[0070] After normalization, each value is represented as the variance increment corresponding to the mean, allowing values ​​with different attributes to be analyzed and compared under the same scale, removing the interference of their respective units of measurement.

[0071] Based on the characteristics and specific requirements of the journal, several types of estimation parameter frameworks are set up, including four types: full-text views, journal impact factor, citation rate, and number of publications.

[0072] Step 3: Calculate the change in each evaluation parameter based on its historical values ​​for the specified time period. And change into a distinguishing factor ;

[0073] In a preferred but non-limiting embodiment of the present invention, in Step 3, the change is transformed into a distinguishing factor. The operational equation is: and Here, and These are the parameter values ​​for the current time period and the previous time period, respectively. It is a pattern that associates changes with distinguishing factors;

[0074] In a preferred but non-limiting embodiment of the present invention, in Step 3, the equation and Inside:

[0075] The parameter value is for the current time period; for example, if the parameter value being parsed now is for the current time period, it is usually the full text views of the last three months.

[0076] This represents the parameter value for the previous period; for example, the full-text views for the three months prior to the most recent three months.

[0077] Change The equation calculates the change between two consecutive time points; it represents the magnitude of the change in the parameter value of the current time period corresponding to the change in the previous time period, expressed as a change in magnitude. The equation can yield a proportion, where a proportion higher than zero represents an increase, a proportion lower than zero represents a decrease, or a proportion of zero represents a constant.

[0078] A pattern used to represent changes Associated with the distinguishing factor This factor can be used to compare the effects of different parameters and help identify which type of factor has the greatest effect on changes in the journal.

[0079] Change It provides a concise and straightforward parameter to measure a type of change; the distinguishing factor then quantifies this type of change into its impact on the overall assessment, enabling companies to more accurately identify and manage key change factors in the journal.

[0080] Step 4, differentiate the parameters by their distinguishing factors. Corresponding keyness Multiply to obtain the overall estimated score. ;

[0081] In a preferred but non-limiting embodiment of the present invention, in Step 4, the calculation equation for estimating the score is: Here, The number of parameters;

[0082] Equation for estimating scores Inside:

[0083] The differential factor for each parameter represents the magnitude of the effect of the parameter's change on the journal's overall differential value; and it is obtained through the calculation in Step 3.

[0084] criticality This reflects the criticality of each parameter in the overall estimation; the setting of criticality is often determined based on the specific needs and emphasis of the subject classification subsystem.

[0085] Accumulated amount of criticality It is one. This ensures the accuracy of the estimated scores.

[0086] The estimated score is a global score used to reflect the overall quality status of the journal within a specified period; it is calculated by producting the distinguishing factors of each parameter with their relevance and summing the results. It can reflect the global impact of each parameter on the overall quality of the journal.

[0087] This equation allows the subject classification subsystem to aggregate several types of parameters into a single score, thereby simplifying complex journal analysis. The estimated score can be used as a basis for the planning of the subject classification subsystem, helping to identify aspects that need attention and improvement. By adjusting the criticality, the subject classification subsystem can flexibly adjust the focus of the estimation according to different planning priorities and changes in journal needs. The estimated score can also be used for comparative analysis under different time periods or different plans, helping the subject classification subsystem track improvement effects and improvement plans.

[0088] Step 5: Use the obtained global assessment score to characterize the overall quality status of the journal.

[0089] In a preferred but non-limiting embodiment of the present invention, in Step 5, the obtained global estimation score of the journal is... The value is parsed, and if it is less than a predefined threshold... When this happens, the journal will be displayed as low-quality on the subject classification subsystem's screen, and the journal can be removed from its classification category or marked as low-quality.

[0090] In a preferred but non-limiting embodiment of the present invention, Step 5 further includes: analyzing the specific variation amplitude of each parameter to obtain the Pearson coefficient. ,use The value is used to determine the level of influence of each parameter, here It is the first The Pearson coefficient of each parameter and the global estimated score;

[0091] Correlation coefficient Representing the The correlation between each parameter and the global estimated score;

[0092] Its value is - Within the interval, positive one represents a comprehensive positive correlation, negative one represents a comprehensive inverse correlation, and zero represents no correlation.

[0093] use To determine the level of influence of each parameter; The higher the value, the greater the influence of this parameter on the overall estimated score; through comparison... By observing the magnitude of the parameter, we can identify the parameter that has the greatest impact on the overall estimated score.

[0094] In a preferred but non-limiting embodiment of the present invention, in Step 3, the variation is associated with a pattern of distinguishing factors. This is a segmented mode that divides the variable into different ranges based on whether the variable is above or below zero and its modulus, and assigns a dedicated distinguishing factor value to each range to more accurately reflect the impact of the magnitude and trend of parameter changes on the overall distinguishing value of the journal; specifically:

[0095] Change States that are higher than zero or lower than zero:

[0096] Positive change: represents an increase in the parameter;

[0097] Negative change: represents a decrease in the parameter;

[0098] Modulus of the variable High or low: based on the modulus of the change. Divide it into different ranges; just as the modulus of the variable is divided. The range is divided into three areas from low to high, which are defined as low volume fluctuation, medium volume fluctuation, and high volume fluctuation, respectively.

[0099] Changes Divided into several ranges, as follows: ; and Differentiate different fluctuation ranges based on predefined threshold values;

[0100] Set a dedicated differentiation factor for each range from low to high.

[0101] The segmented mode provides detailed control over the levels and trends of variables, more accurately reflecting their impact on global differential quantities. It allows for flexible adjustment of range segmentation and factors based on specific needs, making it suitable for different analytical environments.

[0102] like Figure 2 As shown, the optimized processing device for electronic information according to the present invention includes:

[0103] Subject classification subsystem: The subject classification subsystem classifies journals in the basic database according to different subjects of the Ministry of Education, so as to achieve the goal of subject alignment;

[0104] The subject classification subsystem also includes;

[0105] The aggregation module is used to aggregate the values ​​of evaluation parameters for various types of journals;

[0106] The standardization module is used to perform preprocessing and standardization on the collected data;

[0107] The calculation module is used to calculate the change in each evaluation parameter based on its historical values ​​over a set time period. And change into a distinguishing factor ;

[0108] The estimation module is used to calculate the distinguishing factors of each parameter. Corresponding keyness Multiply to obtain the overall estimated score. ;

[0109] The quality module characterizes the overall quality status of journals based on the obtained global estimated scores. The subject classification subsystem can be computer-based.

[0110] The beneficial effects of the present invention are as follows: Compared with the prior art, the technical effects of the present invention include:

[0111] Several evaluation parameters are collected, including full-text views, journal impact factor, citation rate, and number of publications, comprehensively reflecting various aspects of the journal. Parameter preprocessing and standardization: Logical preprocessing and standardization methods ensure the accuracy and synchronicity of the values. Distinguishing factor calculation: By calculating the changes in each parameter and the distinguishing factor, the distinguishing factors of the journal are numerically analyzed. Global score presentation: The journal's quality status is presented based on a global score calculated according to the distinguishing factors and keyness. In summary, this invention's multi-functional processing method for academic journals in the Ministry of Education's subject classification system can significantly improve the logic and efficiency of journal management within the subject classification subsystem, providing multi-functional support for the subject classification subsystem in complex journal application environments.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention. All such modifications or equivalent substitutions should be covered within the scope of protection of the claims of the present invention.

Claims

1. A multi-functional processing method for academic journals based on the Ministry of Education's subject classification, characterized in that: include: The subject classification subsystem categorizes journals in the basic database according to different subjects of the Ministry of Education, achieving the goal of subject alignment; The multi-functional processing method for academic journals based on the Ministry of Education's subject classification also includes: Step 1: Collect the numerical values ​​of the evaluation parameters for each type of journal; Step 2: Perform preprocessing and standardization on the values ​​collected in Step 1; Step 3: Calculate the change in each evaluation parameter based on its historical values ​​for the specified time period. And change into a distinguishing factor ; Step 4, differentiate the parameters by their distinguishing factors. Corresponding keyness Multiply to obtain the overall estimated score. ; Step 5: Use the obtained global estimation score to characterize the overall quality status of the journal. In Step 3, the change is transformed into a distinguishing factor. The operational equation is: and Here, and These are the parameter values ​​for the current time period and the previous time period, respectively. It is a pattern that associates changes with distinguishing factors; In Step 3, the equation and Inside: The parameter value is for the current time period; The parameter value is from the previous time period; Change This represents the change between two consecutive points in time; it indicates the magnitude of the change in the parameter value of the current period relative to the change in the previous period, expressed as a change in magnitude. A ratio is obtained, where a ratio higher than zero represents an increase, a ratio lower than zero represents a decrease, or a ratio of zero represents a constant. A pattern used to represent changes Associated with the distinguishing factor This factor is used to compare the relative strengths of different parameters.

2. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 1, characterized in that, In Step 1, the evaluation parameters include a set of values ​​formed by the journal's full-text views, journal impact factor, citation rate, and number of publications.

3. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 2, characterized in that, In Step 2, the normalization process is performed using the following equations: Here, For the source value, The mean of the set of values ​​is . The variance of the numerical group, The value is the normalized value; In Step 2, the equation Inside: Source values The values ​​collected within the value group; mean This is the mean of all values ​​within the data set; variance To reflect the dispersion of the values, the mean value represents the magnitude of the deviation of the values ​​from the mean.

4. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 3, characterized in that, In Step 4, the equation for estimating the score is: Here, The number of parameters; Equation for estimating scores Inside: The differential factor for each parameter represents the magnitude of the effect of the change in that parameter on the overall differential value of the journal. criticality This demonstrates the critical importance of each parameter in the overall estimation; Accumulated amount of criticality It is one.

5. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 4, characterized in that, In Step 5, the global estimated score of the obtained journals is calculated. The value is parsed, and if it is less than a predefined threshold... When this happens, the journal will be displayed as low-quality on the subject classification subsystem's screen, and the journal can be removed from its classification category or marked as low-quality.

6. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 5, characterized in that, Step 5 also includes: obtaining the Pearson coefficient. ,use The value is used to determine the level of influence of each parameter, here It is the first The Pearson coefficient of each parameter and the global estimated score; Correlation coefficient Representing the The correlation between each parameter and the global estimated score.

7. The multi-functional processing method for academic journals based on the Ministry of Education's subject classification as described in claim 6, characterized in that, In Step 3, the patterns of variation are linked to the distinguishing factors. This is a segmentation mode that divides the variable into different ranges based on whether the variable is above or below zero and its modulus, and assigns a unique distinguishing factor value to each range; specifically: Change States that are higher than zero or lower than zero: Positive change: represents an increase in the parameter; Negative change: represents a decrease in the parameter; Modulus of the variable High or low: based on the modulus of the change. , and divide it into different ranges; Changes Divided into several ranges; Set a dedicated differentiation factor for each range from low to high.

8. An apparatus for a multi-functional processing method of academic journals according to the subject classification of the Ministry of Education as described in claim 1, characterized in that, include: Subject classification subsystem; The subject classification subsystem categorizes journals in the basic database according to different subjects of the Ministry of Education, achieving the goal of subject alignment; The subject classification subsystem also includes; The aggregation module is used to aggregate the values ​​of evaluation parameters for various types of journals; The standardization module is used to perform preprocessing and standardization on the collected data; The calculation module is used to calculate the change in each evaluation parameter based on its historical values ​​over a set time period. And change into a distinguishing factor ; The estimation module is used to calculate the distinguishing factors of each parameter. Corresponding keyness Multiply to obtain the overall estimated score. ; The quality module is used to characterize the overall quality status of journals based on the obtained global estimated scores.

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