CN112989070B - Core periodical quantitative evaluation system and method based on computer system - Google Patents

Core periodical quantitative evaluation system and method based on computer system Download PDF

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CN112989070B
CN112989070B CN202110563766.0A CN202110563766A CN112989070B CN 112989070 B CN112989070 B CN 112989070B CN 202110563766 A CN202110563766 A CN 202110563766A CN 112989070 B CN112989070 B CN 112989070B
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subsystem
standard
journal
periodicals
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CN112989070A (en
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黄晨
徐海燕
韩松涛
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Zhejiang University ZJU
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/38—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management

Abstract

The invention discloses a core periodical quantitative evaluation system and method based on a computer system, wherein the evaluation system specifically comprises: a basic database, a subject classification subsystem, a standard subsystem and an evaluation subsystem; the basic database comprises academic information data including papers and periodicals; the subject classification subsystem is used for classifying the periodicals in the basic database according to different subjects to achieve the aim of subject alignment; the standard subsystem is used as a standard body for evaluating academic quality; the evaluation subsystem is used for calculating the academic quality of each journal to which the subject belongs; and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal. The method can avoid subjective interference, change an evaluation system based on SCI citation, and effectively improve the evaluation quantification level of subject literature quality.

Description

Core periodical quantitative evaluation system and method based on computer system
Technical Field
The invention relates to the field of computer technology, literature metrology and subject evaluation, in particular to a core journal quantitative evaluation system and method based on a computer system.
Background
The current academic journal evaluation system is almost based on citation data, and the mainstream academic journal evaluation method is based on citation analysis of WOS database (Web of Science) created by Garfield. The WOS database is divided into three sub-libraries, SCI (scientific citation index), SSCI (social scientific citation index), a & HCI (art and human citation index). For citation ranking evaluation of periodicals, the WOS database provides JCR (journal citation report) and is released once a year to rank the periodicals that are imported from the WOS database, thereby determining core periodicals. The core journal was evaluated in the JCR report mainly by the method of "influencing factor" (IF). The definition of "influencing factor" is: the year impact factor is equal to the total number of citations for a journal in the last two years divided by the total number of papers published in the previous two years. IF = a/B (a = total number of citations to the journal in the first two years for a certain year; B = total number of postings to the journal in the first two years) is formulated.
JCR only involves two sub-libraries of SCI and SSCI, namely, there are citation reports for science and technology journals and social journals, while for art and human fields journals (A & HCI sub-libraries), there is no citation report for journals provided by WOS database. The prior art has two problems for periodical evaluation:
one is the citation evaluation mode taking the 'influence factor' as the main mode, the evaluation of the citation evaluation mode is not universally suitable for all subjects, and the artistic and human subjects cannot be evaluated in the 'influence factor' mode.
The A & HCI sublibraries (the art and human literature fields) in the WOS database are of periodical reference conditions, but the reference quantity is very small and can be almost ignored compared with the scientific and social science fields. Therefore, the WOS database builder does not finally provide a periodical reference report, which indicates that they know the uniqueness of the art and human fields due to their disciplines, for example, the achievement in the art and human fields is original and not necessarily based on other achievements, and the like, and it is inappropriate to use the citation to evaluate the periodical, that is, the citation is defective in the method for evaluating the periodical, and the citation evaluation method is not suitable for the periodical in the art and human disciplines.
Second, core journal evaluation in the art and humanity fields is missing with regard to foreign language journals.
Because the only core periodical evaluation mode for foreign language periodicals is the evaluation mode of 'influence factors', and the mode can not be used for the subjects of art and humanity, the foreign language periodicals of the subjects of art and humanity have no corresponding core periodical evaluation method.
At present, there is no core journal evaluation method that is independent of citations and can evaluate all subject journals.
Disclosure of Invention
Based on the defects in the prior art, the invention aims to provide a core periodical quantitative evaluation system and method based on a computer system, change the traditional periodical evaluation mode based on the quotation data of a WOS database, avoid subjective interference and evaluate the quality of documents in a scientific mode.
The invention provides a core periodical quantitative evaluation system based on a computer system, which comprises a basic database, a subject classification subsystem, a standard subsystem and an evaluation subsystem, wherein:
the basic database is used for constructing all subject information databases including academic information data including papers and periodicals;
the subject classification subsystem is used for classifying the periodicals in the basic database according to different subjects to achieve the aim of subject alignment;
the standard subsystem is used as a standard body for evaluating academic quality; incorporating a paper set of a particular academic institution for a particular time period into the standard subsystem based on the subject ranking and/or the results of the subject evaluation;
the evaluation subsystem is used for calculating the academic quality of each journal to which the subject belongs; and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal.
Preferably, the basic database comprises a complete paper set, a complete journal set, a classification list, a subject list and a complete academic institution set.
Preferably, the quality evaluation index of the journal is obtained by weighting the absolute number of the texts of the journal in the standard subsystem and the proportion of the texts in a specific period.
Preferably, the weighting operation method is as follows:
(1) setting total number K of published papers of periodicals: the total number of the issued documents of the periodical in the time period corresponding to the hit numerical value;
(2) the absolute number of publications G in the standard subsystem of the journal: the number of papers hit in the standard subsystem in a specific time;
(3) reduced TOP university release amount r:
Figure 920468DEST_PATH_IMAGE001
，
Figure 275093DEST_PATH_IMAGE002
mean value of K
(4) G and r are normalized and then added with weights, and finally the weight is determined as w after a plurality of different weight operations1And w2Namely: integrated quantization evaluation value = w1*G+w2*r。
Preferably, the subject classification subsystem is based on a preset subject classification standard, and if the input subject information is the same as the subject in the preset subject classification standard, the input subject information is kept unchanged; and if the input subject information is different from the subjects in the preset subject classification standard, performing subject mapping by using a subjective method and/or an objective method.
Preferably, the subjective method is that the expert in the taxonomy of the library analyzes the extensive connotations of different disciplines and performs the discipline mapping work.
Preferably, the objective method is to set subject periodicals by subject experts of different institutions, or comprehensively analyze the subject periodicals set by subjects of different systems by different institutions, and determine the relationship between the subjects according to the content such as the proportion of the contained same periodicals.
Preferably, the preset discipline classification standard is an educational department classification standard.
Preferably, the specific academic institutions of the standard subsystem are a certain number of academic institutions with specific ranking in the preset subject classification standard, and the certain number of academic institutions with preceding ranking is taken as the preference.
Preferably, the standard subsystem is constructed in the following manner:
(1) inputting a specific academic institution set corresponding to the subject;
(2) randomly selecting a paper from a basic database corresponding to the subject, judging whether an author organization is in a specific academic organization set, and if so, adding the paper into a standard subsystem; if not, removing the thesis from the corpus of the thesis;
(3) and outputting a standard subsystem corresponding to the subject after traversing the complete paper set corresponding to the subject in the basic database.
Preferably, the paper hit rate in the standard subsystem is calculated in the following manner:
(1) inputting a standard subsystem corresponding to the subject;
(2) the hit rate of all periodicals in a subject journal set corresponding to a preset subject in the basic database is 0;
(3) randomly selecting a journal from a subject journal set corresponding to a subject, randomly selecting a paper from a standard subsystem, judging whether the paper is published in the selected journal, if so, adding 1 to the hit rate of the journal, and removing the paper from the standard subsystem; if not, directly removing the paper from the standard subsystem;
(4) after traversing the standard subsystems corresponding to the disciplines, removing the corresponding periodicals from the basic database;
(5) and outputting the paper hit rate of the standard subsystem corresponding to the subject after traversing the basic database corresponding to the subject.
Preferably, the subject list includes at least any one of a human subject, a social subject, and a scientific subject.
Preferably, the selection evaluation results of the subject journal sets are arranged in descending order according to the comprehensive quantitative evaluation value.
In addition, the invention also discloses a core periodical quantitative evaluation method based on the computer system, which comprises the following steps:
(1) constructing a basic database including academic information data including papers and periodicals;
(2) classifying the periodicals in the basic database according to different disciplines to achieve the aim of discipline alignment;
(3) according to the result of the subject ranking and/or subject evaluation, bringing a paper set of a specific academic institution in a specific period into a standard subsystem as a standard body for evaluating academic quality;
(4) and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal.
Preferably, the basic database comprises a paper corpus, a journal corpus, a classification list, a subject list and an academic institution corpus.
Preferably, the quality evaluation index of the journal is obtained by weighting the absolute number of the texts of the journal in the standard subsystem and the proportion of the texts in a specific period.
Preferably, the weighting operation method is as follows:
(1) setting total number K of published papers of periodicals: the total number of the issued documents of the periodical in the time period corresponding to the hit numerical value;
(2) the absolute number of publications G in the standard subsystem of the journal: the number of papers hit in the standard subsystem of the periodical in a specific time;
(3) reduced TOP university release amount r:
Figure 851568DEST_PATH_IMAGE001
，
Figure 918881DEST_PATH_IMAGE002
means an average value of K
(4) G and r are normalized and then added with weights, and finally the weight is determined as w after a plurality of different weight operations1And w2Namely: integrated quantitative evaluation value = w1*G+w2*r。
Preferably, the subject classification is based on a preset subject classification standard, and if the input subject information is the same as the subject in the preset subject classification standard, the input subject information is kept unchanged; if the input subject information is different from the subjects in the preset subject classification standard, subject mapping is carried out by using a subjective method and/or an objective method, and the aim of subject alignment is achieved.
Preferably, the subjective method is that the expert in the taxonomy of the library analyzes the extensive connotations of different disciplines and performs the discipline mapping work.
Preferably, the objective method is to set subject journals by subject experts of different institutions or comprehensively analyze the subject journals set by subjects of different systems by different institutions, and determine the relationship among the subjects according to the contents such as the proportion of the contained same journals.
Preferably, the preset discipline classification standard is an education department discipline classification standard.
Preferably, the specific academic institutions of the standard subsystem are a certain number of academic institutions with specific ranking in the preset subject classification standard, and the certain number of academic institutions with preceding ranking is taken as the preference.
Preferably, the standard subsystem is constructed in the following manner:
(1) inputting a specific academic institution set corresponding to the subject;
(2) randomly selecting a paper from a basic database corresponding to the subject, judging whether an author organization is in a specific academic organization set, and if so, adding the paper into a standard subsystem; if not, removing the thesis from the complete thesis set;
(3) and outputting a standard subsystem corresponding to the subject after traversing the complete paper set corresponding to the subject in the basic database.
Preferably, the calculation of the paper hit rate comprises the steps of:
(1) inputting a standard subsystem corresponding to the subject;
(2) the hit rate of all periodicals in a subject periodical set corresponding to a preset subject in a basic database is 0;
(3) randomly selecting a journal from a subject journal set corresponding to a subject, randomly selecting a paper from a standard subsystem, judging whether the paper is published in the selected journal, if so, adding 1 to the hit rate of the journal, and removing the paper from the standard subsystem; if not, directly removing the paper from the standard subsystem;
(4) after traversing the standard subsystems corresponding to the disciplines, removing the corresponding periodicals from the basic database;
(5) and outputting the paper hit rate of the standard subsystem corresponding to the subject after traversing the basic database corresponding to the subject.
Preferably, the subject list includes at least any one of a human subject, a social subject, and a scientific subject.
Preferably, the selection evaluation results of the subject journal set are arranged in descending order according to the comprehensive quantitative evaluation value.
The invention provides a brand-new periodical evaluation system and method capable of evaluating periodicals of all disciplines, which are used for solving two problems of periodical evaluation in the prior art and finally achieving two main innovation points:
firstly, a core journal evaluation mode which is not based on citation is provided, and a core journal evaluation theory system is enriched.
And secondly, the periodical evaluation mode is flawless from the perspective of evaluating periodicals of different subjects, namely is suitable for evaluating periodicals in any subject field, so that the problem that periodicals in the fields of art and human subjects have no core periodical evaluation standard is solved.
The core periodical quantitative evaluation system based on the computer system provided by the invention is a system with the two innovation points. The paper collection number and the quotation rate are reduced, and SCI and ESI related indexes are not used as requirements of direct judgment bases.
In summary, compared with the prior art, the invention has the beneficial effects that: according to the subject evaluation quantification system, the academic interval of the learner with excellent indexes to be evaluated is considered, the academic institution with the excellent indexes is used for indirectly evaluating the academic output of the learner, and due to the adoption of a big data analysis and post-evaluation mechanism, big data is used as measurement and is not limited to measurement of one person and one language, so that the defects of counterfeiting and toping can be effectively reduced. The system judges through the contribution behavior of the data analysis scholars instead of questionnaires and interview forms, can effectively avoid subjective interference, changes the traditional evaluation system based on SCI citation, and effectively improves the evaluation quantification level of subject literature quality.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below.
Fig. 1 is a schematic block diagram of a core periodical quantitative evaluation system according to an embodiment of the present invention.
Fig. 2 is a flowchart of a method for quantitatively evaluating a core journal according to an embodiment of the present invention.
Fig. 3 is a flow chart of the construction of the discipline classification subsystem according to the embodiment of the present invention.
Fig. 4 is a flowchart of a academic institution set construction process with excellent subject evaluation according to an embodiment of the present invention.
FIG. 5 is a flow chart of the construction of a discipline standard subsystem according to an embodiment of the present invention.
FIG. 6 is a flowchart illustrating the calculation of hit rate of a discipline-standard subsystem paper according to an embodiment of the present invention.
Fig. 7a to 7c are diagrams illustrating the operation of the journal evaluation system according to the embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. Based on the following embodiments, other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present invention.
If there is a description of "first", "second", etc. in an embodiment of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a technical feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions between the various embodiments can be combined with each other, but must be based on the realization of those skilled in the art.
The academic achievement of an evaluation student mainly depends on a publishing journal at present, the evaluation journal depends on evaluation based on citation analysis, and an effective evaluation scale can hardly be constructed after the evaluation journal leaves the citation analysis. The evaluation of the human society is different from the popular citation analysis method of the Science and engineering, the measurement and comparison of the citation amount and the citation amount of the human scholars are difficult, the Web of Science does not provide the cited data of the human scholars, and the academic world generally lacks effective measurement and analysis means for the human scholars. Peer review is theoretically the best academic evaluation means, and the core of the peer review lies in the academic value evaluation of people in the circle. However, how to define a high-quality academic circle and how to ensure the objectivity of peer comments cannot be effectively eliminated due to the social attributes of people, so that the method cannot be widely applied. In view of this, the embodiments of the present invention are intended to construct an effective academic circle, and perform statistical analysis on the academic paper distribution of the academic circle, so as to identify high-level periodicals and papers, thereby completing quantitative evaluation.
In order to achieve the above object, the present invention provides a core periodical quantitative evaluation system and method based on a computer system, which is a brand new core periodical evaluation system using big data to construct a database system, the evaluation system completely abandons all contents related to the citation, i.e. does not depend on the citation, redefines various parameters for core periodical evaluation, and the main technical idea of the present invention is as follows:
from the perspective of periodicals, the periodicals are essentially academic forums, a plurality of thematic versions of the forums are formed by periodicals in the same field, each thematic version can form a student group of the periodicals, the student groups are readers and authors, the students can automatically select and gather, and the high-quality thematic versions naturally gather the high-quality student groups, namely an elegant academic circle. Based on the technical thought, the invention takes the discriminant group as a parameter for evaluating the quality of the periodical.
From the perspective of academic institutions, academic institutions are the most important way to distinguish groups of scholars. Scholars in the same academic institution develop a common "academic view", i.e., a common evaluation criterion for academic journals, and practice their "academic view" by posting activities to a certain batch of journals. That is, the "academic behaviors of the scholars" in the present invention includes, but is not limited to, the behaviors of the scholars writing papers, posting papers, and publishing papers in journals. The journal group pointed by the academic behaviors of the scholars of an academic institution is the core journal. A plurality of academic institutions form an academic circle of a certain subject, and core periodicals of different subjects can be found by finding out academic behaviors of a student of the academic circle of each subject in big data. "scholars' academic behaviors" can be used as parameters for evaluating the quality of periodicals.
As shown in fig. 1, the core periodical quantitative evaluation system according to the embodiment of the present invention includes a basic database, a subject classification subsystem, a standard subsystem, and an evaluation subsystem, wherein:
the basic database is used for constructing all subject information databases including academic information data including papers and periodicals;
the subject classification subsystem is used for classifying the periodicals in the basic database according to different subjects to achieve the aim of subject alignment;
the standard subsystem is used as a standard body for evaluating academic quality; incorporating a paper set of a particular academic institution for a particular time period into the standard subsystem based on the subject ranking and/or the results of the subject evaluation; both the subject ranking and the subject assessment refer to the evaluation of subjects by some organizations and the resulting results. The subject ranking mainly refers to subject ranking results of sorting subjects by USNews, QS and the like, and subject evaluation refers to evaluation results of only grades of subjects, such as the evaluation of education department;
the evaluation subsystem is used for calculating the academic quality of each journal to which the subject belongs; and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal.
Preferably, the basic database comprises a complete paper set, a complete journal set, a classification list, a subject list and a complete academic institution set.
Preferably, the quality evaluation index of the journal is obtained by performing weighted operation on the absolute number of the texts sent from the journal in the standard subsystem and the proportion of the texts sent within a specific period.
Preferably, the weighting operation method is as follows:
(1) setting total number K of published papers of periodicals: the total number of the issued documents of the periodical in the time period corresponding to the hit numerical value;
(2) the absolute number of publications G in the standard subsystem of the journal: the number of papers hit in the standard subsystem of the periodical in a specific time;
(3) reduced TOP university release amount r:
Figure 389045DEST_PATH_IMAGE001
，
Figure 742666DEST_PATH_IMAGE002
mean value of K
(4) G and r are normalized and then added with weights, and finally the weight is determined as w after multiple different weight operations1And w2Namely: integrated quantitative evaluation value = w1*G+w2*r。
In this embodiment, the weight w is calculated according to the characteristics of the subject, such as the subject size and the subject issue condition, and the like1And w2Set at 0.45 and 0.55, i.e.: integrated quantitative evaluation value =0.45 × G +0.55 × r. The study isAnd sorting the selection evaluation results of the journal sets in a descending order according to the comprehensive quantitative evaluation value. The "specific time" in the first step may vary depending on the characteristics of the subject, and is 5 years for this application. In the fourth step, the total number G of the messages using the standard subsystem and the converted TOP university message amount r are two indexes which are used for determination, but the weights 0.45 and 0.55 are variable, and the weights 0.45 and 0.55 are obtained by data calculation, so that the stage-wise reasonable results are obtained, and the weights can be adjusted according to the characteristics of different disciplines.
Preferably, as shown in fig. 3, the subject classification subsystem is based on a preset subject classification standard, and if the input subject information is the same as the subject in the preset subject classification standard, the input subject information is kept unchanged; if the input subject information is different from the subjects in the preset subject classification standard, subject mapping is carried out by using a subjective method and an objective method, and the aim of subject alignment is achieved. The subjective and objective modes are usually used in combination.
Preferably, the subjective method is that the expert in the taxonomy of the library analyzes the extensive connotations of different disciplines and performs the discipline mapping work.
Preferably, the objective method is to set subject journals by subject experts of different institutions or comprehensively analyze subject journals set by subjects of different systems by different institutions, and determine the relationship among the subjects according to the contents such as the proportion of the contained same journals.
For the problem of classifying disciplines of periodicals, the disciplines in the discipline directory are not simply used, but the relatively similar disciplines are combined and calculated according to a specific algorithm, so that the purpose of avoiding artificially splitting the similar disciplines into a plurality of disciplines is achieved. The principle is mainly that there is a high or low correlation between disciplines, which results in some scholars publishing research results in the research direction of the disciplines on periodicals of similar disciplines. It is more advantageous to have a generic circle correspond to a discipline if the similar disciplines are merged. The invention mainly uses a clustering dispersion method (K-Means) to merge the disciplines according to the repetition rate of different disciplines containing the same journal. The K-Means algorithm is:
for sample set D = { x1,x2,…,xm(in the present invention, D is a subject including journal groups.) the K-Means algorithm is for clustering division C = { C = [ C ]1,C2,…,CkMinimize the squared error: (C (Categories) is the self-defined cluster number, the cluster number in the invention is set as 3, 4 and 5, and the possibility of merging disciplines with different attributes is calculated by using different cluster numbers.)
The K-Means algorithm formula is:
Figure 416224DEST_PATH_IMAGE003
wherein:
Figure 411862DEST_PATH_IMAGE004
where x is the mean vector of the cluster Ci, kandiare all positive integers.
E represents how close the intra-cluster samples are around the cluster mean vector, with smaller values of E giving higher similarity to the intra-cluster samples. The meaning of higher similarity is that related disciplines have similarity, and the algorithm result is discipline combination.
Preferably, the preset discipline classification standard is an education department discipline classification standard.
Preferably, as shown in fig. 4, the specific academic institutions of the standard subsystem are a certain number of academic institutions with specific ranking in the preset discipline classification standard, and the certain number of academic institutions with preceding ranking is preferred.
The academic institution with excellent subject evaluation indexes is constructed based on subject ranking and serves as the basis of a dynamic metering evaluation method. Firstly, defining an academic circle evaluation complete set as E ac ：
E ac = { S ac , U nac , P ac , J ac }
Wherein:
S ac represents a complete set of disciplines;
U nac represents a complete set of academic institutions;
P ac represents a corpus of papers;
J ac representing a complete set of periodicals;
in addition, constants are defined as follows:
C qr : representing rank top C for discipline only qr The academic institution of (1);
c: an academic institution representing the discipline rank C is defined as an academic institution; the subsequent verification of this example is taken to be 10.
Further, a related set of discipline circles is defined as follows:
(a) academic institution set U (S, Y): represents the universities of all the disciplines (S) in a certain year (Y) before the ranking C (C is the number of the top ranking).
Figure 237998DEST_PATH_IMAGE005
（1）
Rank(u i S, Y denotes an academic institution (u i ) Ranking of the disciplines (S) in a certain year share (Y).
(b) Paper set P (S, Y): all the paper sets of academy publications of a subject (S) in a year (Y) before the rank C (C is the number of the first rank).
Figure 903465DEST_PATH_IMAGE006
（2）
Wherein the content of the first and second substances,
Figure 188953DEST_PATH_IMAGE007
representing academic institutions: (u i ) All paper collections published in subject (S) in year share (Y); p sub Represents P ac The thesis of all S disciplines in the corpus, search _ p (u i ,p i Y) is True for Y yearsu i Academic Press published a paper p i 。
Preferably, as shown in fig. 5, the standard subsystem is constructed in the following manner:
(1) inputting a specific academic institution set corresponding to the subject;
(2) randomly selecting a paper from a basic database corresponding to the subject, judging whether an author organization is in a specific academic organization set, and if so, adding the paper into a standard subsystem; if not, removing the thesis from the complete thesis set;
(3) and outputting a standard subsystem corresponding to the subject after traversing the complete paper set corresponding to the subject in the basic database.
Journal collection J (S, Y): journal set of all papers published by academic institution representing C before rank of subject S of Y of the year
Figure 581757DEST_PATH_IMAGE008
（3）
Wherein the content of the first and second substances,
Figure 636301DEST_PATH_IMAGE009
the journal j in which the paper p is located is shown, and the search _ j (p, j, Y) is True, which means that the paper p in Y is published in the journal j.
It follows that the first class academic circle E of year Y based on the subject rankingac_f：
Figure 738249DEST_PATH_IMAGE010
（4）
Wherein s is i Representative subject corpus SacOne subject of (U), (B)s i Y) represents the year s of Y i The disciplines correspond to an academic institution. P: (s i Y) represents the year s of Y i A first-class thesis corresponding to the subject, J (s i Y) represents the year s of Y i An academic journal corresponding to the subject, and an academic circle E of the first degree in Y yearsac_fComprises a complete set S of Y-year disciplinesacCorresponding an academic institution, an academic paper and an academic journal;
based on the above definitions and functions, a reliable evaluation scale of the subject journal can be obtained. Because the assessment is carried out by using the contribution behaviors of the scholars, and the questionnaire and interview forms are not adopted, the subjective interference of the human situation and the blind spot can be effectively avoided.
The starting point for the above definition and deduction is the subject ranking and the constants C and C are determined therefrom qr The value of (a).
Preferably, as shown in fig. 6, the paper hit rate in the subject standard subsystem is calculated in the following manner:
(1) inputting a standard subsystem corresponding to the subject;
(2) the hit rate of all periodicals in a subject periodical set corresponding to a preset subject in a basic database is 0;
(3) randomly selecting a journal from a subject journal set corresponding to a subject, randomly selecting a paper from a standard subsystem, judging whether the paper is published in the selected journal, if so, adding 1 to the hit rate of the journal, and removing the paper from the standard subsystem; if not, directly removing the paper from the standard subsystem;
(4) after traversing the standard subsystems corresponding to the disciplines, removing the corresponding periodicals from the basic database;
(5) and outputting the paper hit rate of the standard subsystem corresponding to the subject after traversing the basic database corresponding to the subject.
As shown in fig. 2, the present invention also discloses a core journal quantitative evaluation method based on a computer system, which comprises the following steps:
(1) constructing a basic database including academic information data including papers and periodicals;
(2) classifying the periodicals in the basic database according to different disciplines to achieve the aim of discipline alignment;
(3) according to the result of the subject ranking and/or subject evaluation, bringing a paper set of a specific academic institution in a specific period into a standard subsystem as a standard body for evaluating academic quality;
(4) and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal.
Preferably, the basic database comprises a complete paper set, a complete journal set, a classification list, a subject list and a complete academic institution set.
Preferably, the quality evaluation index of the journal is obtained by weighting the absolute number of the texts of the journal in the standard subsystem and the proportion of the texts in a specific period.
Preferably, the weighting operation method is as follows:
(1) setting total number K of published papers of periodicals: the total number of the issued documents of the periodical in the time period corresponding to the hit numerical value;
(2) the absolute number of publications G in the standard subsystem of the journal: the number of papers hit in the standard subsystem of the periodical in a specific time;
(3) reduced TOP university release amount r:
Figure 511033DEST_PATH_IMAGE001
，
Figure 940484DEST_PATH_IMAGE011
mean value of K
(4) G and r are normalized and then added with weights, and finally the weight is determined as w after a plurality of different weight operations1And w2Namely: integrated quantitative evaluation value = w1*G+w2*r。
Preferably, as shown in fig. 3, the subject classification is based on a preset subject classification standard, and if the input subject information is the same as the subject in the preset subject classification standard, the input subject information is kept unchanged; if the input subject information is different from the subjects in the preset subject classification standard, subject and objective methods are used for subject mapping to achieve the aim of subject alignment, and the subjective and objective methods are generally used comprehensively.
Preferably, the subjective method is that the expert in the taxonomy of the library analyzes the extensive connotations of different disciplines and performs the discipline mapping work.
Preferably, the objective method is to set subject periodicals by subject experts of different institutions, or comprehensively analyze the subject periodicals set by subjects of different systems by different institutions, and determine the relationship between the subjects according to the content such as the proportion of the same contained periodicals.
Preferably, the preset discipline classification standard is an education department discipline classification standard.
Preferably, as shown in fig. 4, the specific academic institutions of the standard subsystem are a certain number of academic institutions with specific ranking in the preset discipline classification standard, and the certain number of academic institutions with ranking before is preferred.
Preferably, as shown in fig. 5, the standard subsystem is constructed by the following steps:
(1) inputting a specific academic institution set corresponding to the subject;
(2) randomly selecting a paper from a basic database corresponding to the subject, judging whether an author organization is in a specific academic organization set, and if so, adding the paper into a standard subsystem; if not, removing the thesis from the complete thesis set;
(3) and outputting a standard subsystem corresponding to the subject after traversing the complete paper set corresponding to the subject in the basic database.
Preferably, as shown in fig. 6, the calculation of the hit rate of the thesis includes the following steps:
(1) inputting a standard subsystem corresponding to the subject;
(2) the hit rate of all periodicals in a subject periodical set corresponding to a preset subject in a basic database is 0;
(3) randomly selecting a journal from a subject journal set corresponding to a subject, randomly selecting a paper from a standard subsystem, judging whether the paper is published in the selected journal, if so, adding 1 to the hit rate of the journal, and removing the paper from the standard subsystem; if not, directly removing the paper from the standard subsystem;
(4) after traversing the standard subsystems corresponding to the disciplines, removing the corresponding periodicals from the basic database;
(5) and outputting the paper hit rate of the standard subsystem corresponding to the subject after traversing the basic database corresponding to the subject.
Preferably, the subject list includes at least any one of a human subject, a social subject, and a scientific subject.
Preferably, the selection evaluation results of the subject journal set are arranged in descending order according to the comprehensive quantitative evaluation value.
The ESI subject ranking is established by thomson scientific and technical information group on the basis of gathering and analyzing academic documents included in the ISI Web of Science (SCI) and references cited therein, and is performed for 22 professional fields such as mathematics, physics, chemistry, medicine, agriculture, and the like. Whereas the international education market in uk refers to quacqurelli symands ("QS world university subject ranking") published annually by the company quacqurelli in 48 subject areas, ranking world first class universities from four dimensions, academic reputation, employer evaluation, paper quotations and h-index. Considering that the subject division of QS has better correspondence with the subject classification of our country, especially the human social science, in this embodiment, the academic circle E is consideredac_fTaking QS ranking as a value basis; of course, USNews, softscience, education department assessment ranking, etc. may also be taken.
The domestic subject classification includes the national standard 'subject classification and code' (GB/T13745-2009) and the education department subject classification, and foreign countries such as WOS and AisiWeier have respective subject classifications. Because the thinking and the target of each classification system are different, the disciplines are divided differently, the same discipline name has different concept connotations, and the disciplines with different names have possibly consistent connotations. In this embodiment, the educational department, QS department, and WOS classification are analyzed for consistency, and a "subject mapping table" is established, so that the classifications of the three systems can be compared with each other, or even transformed.
Each education department primary subject corresponds to a plurality of WOS journal classifications, and individual subjects can be summarized into a subject department or individually evaluated for secondary subjects due to differences of the WOS classifications, the QS classifications and the education department subject classifications. It should be noted that the disciplines of the education department, which are partially humanistic, are socialized in WOS, and vice versa. For example, folk-custom, WOS belongs to humanity, and education department belongs to the department of discipline and law. For example, there is news propaganda under the department of education and literature, and there is propaganda under the WOS, belonging to the society. Although there are 17 periodicals and one category of propaganda in the a & HCI journal list, there are 88 periodicals in the SSCI's category of propaganda, so for WOS, the propaganda is mainly in society. Only 4 of the 17 periodicals are heavier than 88, and the second classification of the 17 periodicals is mostly languages or linguistics. Therefore, as mentioned above, the classification of the journal is mainly based on the first classification, but the journal is also assigned with reference to other classifications.
In addition, it was found that there is considerable consistency in the definition of the humanity discipline at home and abroad. Namely, the humanistic subjects of the education department (i.e. the first subjects under four discipline categories of philosophy, literature, history and art) have higher consistency with QS humanistic subject classification and WOS on the classification of the A & HCI medium-term journal, and meanwhile, partial subjects of the sociological subjects (i.e. four disciplines of economics, law, education and management) have higher consistency with the classification of the QS subjects and the classification of the WOS on the journal in SSCI.
Defining a periodical selection function as Corejournal _ Select (S, Y) for evaluation and selection of periodicals
Defining a constant:
c _ f: the journal hit by the C _ f journal papers in the academic journal is taken as a core journal;
c _ t: the first C _ t representing the selection of academic periodicals is a core journal;
c _ p: representing that the first C _ p% of academic periodicals are selected as core periodicals;
then there is discipline sub _ qs:
sub_qs= (if subSUBwos, fwq(sub), (if subSUBes , feq(sub),sub) )
Ip = |P(sub_qs,year)|;
Ij = |J(sub_qs,year)|;
While j = 1 to Ij
rj = 0 ;
While i = 1 to Ip
If search_j(Pi,Jj,Y) = True,(Jj, rj++)
SORT (j,r) by r Descending
then a core journal collection: corejournal (S, Y)
Select j while rC_f or the first C_t or first C_p% to Set of Core Journal(S,Y) （5）
Wherein:
fwq (sub) represents the aligned conversion from wos disciplines to QS discipline;
feq (sub) stands for the conversion from the department of education to the QS discipline.
According to the definition, 5220 kinds of periodicals which are imported by SSCI and A & HCI in 2019 are taken as research objects. Wherein, the human subject journal takes 1834 journals recorded in 2019 of A & HCI as basic journals. According to JCR2018 published in 2019, 4781 periodicals of SSCI have 58 categories, and as one periodical can be divided into a plurality of categories, 3386 periodicals are actually provided after duplication is removed. The journal publishes more than 50 papers among 2014-2018, and metadata of the papers is structured and subject mapping is completed to form a data set for evaluation and analysis in the embodiment.
Referring to fig. 7a to 7c, which are examples of operations of the journal evaluation system according to the embodiment of the present invention, an initial interface of the evaluation system is shown in fig. 7a, and a list of subjects can be seen. In fig. 7b, the discipline/classification mapping table is displayed, and the user can select the classification table corresponding to a certain discipline according to the actual situation, and the display result after selection is as shown in fig. 7 c.
By applying the method, the data set is statistically analyzed, so that the paper publication distribution and the important journal list of each subject are obtained, and the concrete implementation process of the invention is explained by taking the human subject as an example. It should be noted that the method of the present invention is applicable to any subject. The languages of the various subject periodicals are not limited.
The first embodiment is as follows:
data processing and analysis were performed starting with a human discipline. QS human disciplines has nine categories: philophys (Philosophy), science, sight & Religious Studies, Classics & antibiotic History (classical and Ancient), English Language & Literture (English and Literature), Modern Languages (Modern Languages), Archaeology (Archaeology), History (History), formed Arts, Art & Design. The constant C was taken to be 10, i.e., the top ten ranks for each subject, for a total of ninety colleges, and after deduplication was 45 colleges.
Statistics were conducted on papers published in A & HCI in five years of 2014-2018 at university 45, totaling 59745 papers, of which 56150 was published on 1696 of 1834 journal included in A & HCI2019, at a rate of about 92.5%. The periodicals of the nine subjects are subjected to statistics and distribution analysis, and the data are collated as shown in table 1.
Figure 256059DEST_PATH_IMAGE012
(Table 1) statistics of journal and issue of human and literature
In Table 1, modern languages, English, and literature periodicals are difficult to distinguish, so they are ranked jointly. QS disciplines ranks The first ten disciplines are The same as The universities, The ninth of modern languages is The University of Tokyo (42 articles of language and literature co-published articles), and The tenth of modern languages is Peking University (51 articles of language and literature co-published articles), and The data of The documents are not counted in The data of The table above in view of keeping The consistency of The statistical calibers of ten academic institution data and The data of The documents are small.
In table 1, only seven colleges and universities with the top ten colleges and universities of the two subjects of art have texts.
In summary, the average issue of the first 25% of periodicals accounts for about 75% of the issue of the university subject, and the distribution of the issues meets the statistical characteristics, which also proves the effectiveness of the assumption and evaluation of the embodiment.
Example two:
the QS social disciplines are 17 in total, and are respectively: economic and metrological economies & economies, Statistics and operations Statistics & International standards, sociological society, Anthropology, Education and Training discovery & Training, psychological pathology, Sports related Subjects, linguistic diagnostics, propagation and Media Research communications & Media standards, Business Management Business & Management standards, Accounting and financial Accounting, tourism Management Business & knowledge, Social Policy and administrative Information, Development, and Library Information. The journals with corresponding classifications of 14 SSCI were evaluated, the 14 subjects ranked 10 had 140 academic institutions, the academic institution with written text after duplication removal was 66, and 551416 SSCI papers were published, wherein 451248 were published on 4698 of 4781 SSCI journals of JCR2018 published by 2019, and the coverage of written text was 98.26%. The statistical results for the 14 subject journal issues are shown in table 2 below.
Figure 387963DEST_PATH_IMAGE013
(Table 2) statistics of social periodical releases
From statistical data, the issue of TOP10 in the first 25% journal is more highly concentrated than that in no human subject, but the concentration trend is still obvious.
Example three:
on the basis of the distribution research of the issue journal, a specific subject is used for data analysis.
Economics (Economic), education department code 02 economics. QS2019 Economics and metrology Economics & Econometrics rank first ten academic institutions: harvard University, Massachusetts Institute of Technology (MIT), Stanford University, University of California, Berkeley (UCB), University of Chicago, The London School of Economics and Political Science, Princeton University, Yale University, University of Oxford. These academic institutions have distributed 9652 articles in a total of 363 journals. The first 25%, 91 journals, 7005 college publications ranked in the top ten, were selected to account for 72.58% of the total (see table 2).
The book of international academic journals classification of economic colleges of Zhejiang university (2020 edition), published by economic colleges of Zhejiang university, contains top-grade (5 types), A + (14 types), A (11 types) and B (54 types of middle-containing journals). This catalog can be regarded as the evaluation result of the subject experts on the journals, wherein 27 journals are in the SSCI economics catalog, which are the first 30 journals set to top, a +, a. A study on statistics of journal issues of nobel economics awards (the research on the literature measurement characteristics of nobel economics award obtainer in greater university 2011) in liu yong billo shows that there are 8 journal issues of nobel economics awards in 2001 and 2010, 6 of which are in the top grade and a + journal of the economic institute of zhejiang university, and this result can prove that the international journal catalog of zhejiang university economic institute (2020 edition) issued by the economic institute of zhejiang university is a relatively objective core journal list obtained by experts in subject.
Taking the evaluation result of the subject experts of the economic college of Zhejiang university as a reference, comparing the core journal result obtained by the impact factor evaluation method with the result obtained by the core journal quantification system of the embodiment, and sorting the journals by using three evaluation methods (subject expert journal grading, core journal quantification system, and impact factor method), wherein the list is shown in the following table 3.
Figure 772677DEST_PATH_IMAGE014
(Table 3) economic journal selection evaluation comparison table
From the top 5 periodicals identified by the subject experts, the ranks obtained by the first discipline method in this embodiment are 1, 2, 3, 5, and 12, and the ranks obtained by the impact factors are 1, 5, 14, 20, and 25, so that it can be seen that the rank of the core journal quantification system is closer to the peer review results of the subject experts, and the comparison results of the three evaluation methods are summarized and compared, and the results are shown in table 4.
Figure 523595DEST_PATH_IMAGE015
(Table 4) evaluation method comparison
From the results in table 4, if the academic experts grade the economic journal as a reference, the evaluation of the influence factors has a large deviation, and the data statistics and evaluation results of the embodiment prove that the core journal quantification system has obvious advantages and feasibility in the social field compared with the current citation evaluation method.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, shall be included in the scope of the present invention.

Claims (8)

1. A core periodical quantitative evaluation system based on a computer system is characterized by comprising a basic database, a subject classification subsystem, a standard subsystem and an evaluation subsystem, wherein:
the basic database is used for constructing all subject information databases including academic information data including papers and periodicals;
the subject classification subsystem is used for classifying the periodicals in the basic database according to different subjects to achieve the aim of subject alignment;
the standard subsystem is used as a standard body for evaluating academic quality; incorporating a paper set of a particular academic institution for a particular time period into the standard subsystem based on the subject ranking and/or the results of the subject evaluation; the standard subsystem is constructed in the following way:
(1) inputting a specific academic institution set corresponding to the subject;
(2) randomly selecting a paper from a basic database corresponding to the subject, judging whether an author organization is in a specific academic organization set, and if so, adding the paper into a standard subsystem; if not, removing the thesis from the complete thesis set;
(3) after traversing a complete paper set corresponding to a subject in a basic database, outputting a standard subsystem corresponding to the subject;
the evaluation subsystem is used for calculating the academic quality of each journal to which the subject belongs; calculating the paper hit rate of each journal corresponding to the subject in a standard subsystem by inputting subject information to obtain a quality evaluation index of the journal;
the subject classification subsystem combines the subjects by a clustering dispersion method according to the repetition rate of different subjects containing the same periodical keywords;
the quality evaluation index of the periodical is obtained by weighting the absolute number of the texts sent from the periodical in the standard subsystem and the proportion of the texts sent in a specific period;
the weighting operation method comprises the following steps:
(1) setting total number K of published papers of periodicals: the total number of papers in the journal in a specific time;
(2) the absolute number G of publications in the standard subsystem of the journal: the number of papers hit in the standard subsystem of the periodical in a specific time;
(3) reduced TOP university release amount r:
Figure FDA0003637068660000011
Figure FDA0003637068660000012
means the average value of K;
(4) g and r are normalized and then added with weights, and finally the weight is determined as w after a plurality of different weight operations1And w2Namely: integrated quantization evaluation value w1*G+w2*r。
2. The quantitative evaluation system of core journals according to claim 1, wherein said basic database comprises a corpus of papers, a corpus of journals, a sorted list, a subject list and a corpus of academic institutions.
3. The quantitative evaluation system of a core journal as claimed in claim 1, wherein the subject classification subsystem is based on a preset subject classification standard, and if the input subject information is the same as the subject in the preset subject classification standard, the input subject information is kept unchanged; if the input subject information is different from the subjects in the preset subject classification standard, performing subject mapping by using a subjective method and an objective method to achieve the aim of subject alignment; the subjective method is that experts analyze the extensive connotations of different disciplines and perform discipline mapping work; the objective method is that experts set subject periodicals or comprehensively analyze subject periodicals set by subjects of different systems, and the relationship between the subjects is determined according to the proportion of the same contained periodicals.
4. The quantitative evaluation system of a core journal as claimed in claim 3, wherein the preset subject classification standard is a subject classification standard of education department.
5. The quantitative evaluation system for core periodicals according to claim 1, wherein the specific academic institution of the standard subsystem is a certain number of academic institutions ranked first in the preset discipline classification standard.
6. The quantitative evaluation system of core periodicals of claim 1, wherein the clustering discretization method is a K-Means algorithm, which has the formula:
Figure FDA0003637068660000021
wherein:
Figure FDA0003637068660000022
x represents the mean vector of the cluster Ci,
e represents how close the intra-cluster samples are around the cluster mean vector,
the smaller the E value, the higher the similarity of the samples within the cluster.
7. The quantitative evaluation system of core journals according to claim 1, wherein said evaluation subsystem is characterized in that said paper hit rate is calculated by:
(1) inputting a standard subsystem corresponding to the subject;
(2) the hit rate of all periodicals in a subject journal set corresponding to a preset subject in the basic database is 0;
(3) randomly selecting a journal from a subject journal set corresponding to a subject, randomly selecting a paper from a standard subsystem, judging whether the paper is published in the selected journal, if so, adding 1 to the hit rate of the journal, and removing the paper from the standard subsystem; if not, directly removing the paper from the standard subsystem;
(4) after traversing the standard subsystems corresponding to the disciplines, removing the corresponding periodicals from the basic database;
(5) and outputting the paper hit rate of the standard subsystem corresponding to the discipline after traversing the basic database corresponding to the discipline.
8. A quantitative evaluation method of core periodicals constructed by the quantitative evaluation system of core periodicals according to any one of claims 1 to 7, comprising the steps of:
(1) constructing a basic database including academic information data including papers and periodicals;
(2) classifying the periodicals in the basic database according to different disciplines to achieve the aim of discipline alignment;
(3) according to the result of the subject ranking and/or subject evaluation, bringing a paper set of a specific academic institution in a specific period into a standard subsystem as a standard body for evaluating academic quality;
(4) and calculating the paper hit rate of each journal corresponding to the subject in the standard subsystem by inputting subject information to obtain the quality evaluation index of the journal.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105978743A (en) * 2016-07-25 2016-09-28 广东科学技术职业学院 Journal evaluation method based on high-order aggregation coefficient
CN106875088A (en) * 2017-01-03 2017-06-20 中国科学院科技政策与管理科学研究所 Scientific research institution's academic evaluation method and system based on periodical editorial member's index
CN109359824A (en) * 2018-09-25 2019-02-19 浙江理工大学 A kind of evaluation method of the academic level of subject
CN110705821A (en) * 2019-08-23 2020-01-17 上海科技发展有限公司 Hotspot subject prediction method, device, terminal and medium based on multiple evaluation dimensions

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101442518B1 (en) * 2014-01-09 2014-09-26 재단법인 한국연구재단 System for evaluating journal, method for evaluating journal, and medium recorded with program for evaluating journals
CN107832412B (en) * 2017-11-06 2020-06-30 浙江工业大学 Publication clustering method based on literature citation relation
CN109685330A (en) * 2018-12-05 2019-04-26 浙江理工大学 A kind of assessment and prediction technique of Journals influence power
CN109858827A (en) * 2019-02-21 2019-06-07 上海软科教育信息咨询有限公司 Visualization comparative approach, system, electric terminal and the storage medium of subject level
CN112989070B (en) * 2020-06-17 2022-07-19 浙江大学 Core periodical quantitative evaluation system and method based on computer system

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105978743A (en) * 2016-07-25 2016-09-28 广东科学技术职业学院 Journal evaluation method based on high-order aggregation coefficient
CN106875088A (en) * 2017-01-03 2017-06-20 中国科学院科技政策与管理科学研究所 Scientific research institution's academic evaluation method and system based on periodical editorial member's index
CN109359824A (en) * 2018-09-25 2019-02-19 浙江理工大学 A kind of evaluation method of the academic level of subject
CN110705821A (en) * 2019-08-23 2020-01-17 上海科技发展有限公司 Hotspot subject prediction method, device, terminal and medium based on multiple evaluation dimensions

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
人文学科期刊评价新视角：以人评文、以文评刊——以中国语言文学为例;侯鑫鑫等;《中国科技期刊研究》;20190531;第30卷(第5期);第537-544页 *

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