CN115544114A - Multi-dimensional technology evaluation method and system based on big data - Google Patents

Multi-dimensional technology evaluation method and system based on big data Download PDF

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CN115544114A
CN115544114A CN202211149115.8A CN202211149115A CN115544114A CN 115544114 A CN115544114 A CN 115544114A CN 202211149115 A CN202211149115 A CN 202211149115A CN 115544114 A CN115544114 A CN 115544114A
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褚晓泉
赵慧军
席天天
仇瑜
刘德兵
张源
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Beijing Zhipu Huazhang Technology Co ltd
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Abstract

The application provides a multidimensional technology evaluation method and a multidimensional technology evaluation system based on big data, wherein the method comprises the steps of taking a technical point or a technical field to be evaluated as an evaluation target and collecting the big data aiming at the evaluation target, wherein the collected data comprises papers and patents; carrying out expert investigation on the TRL of the technical completeness level of the evaluation target; constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and development and industrialization; and calculating each index in the technical comprehensive evaluation index system according to the collected data and the results of expert research, and counting the calculation result of each index to generate a comprehensive evaluation result of an evaluation target. The method performs comprehensive evaluation on the technology in a mode of combining qualitative evaluation and quantitative evaluation, improves the scientificity and accuracy of the evaluation on the technology, and reduces the cost and complexity of the evaluation.

Description

Multi-dimensional technology evaluation method and system based on big data
Technical Field
The application relates to the technical field of technical evaluation, in particular to a multidimensional technical evaluation method and system based on big data.
Background
With the highlight of the position of technological innovation and the emerging form of a large number of emerging technologies, the comprehensive evaluation of each technology is beneficial to contending for the technological advantage place and facilitating the adjustment of the technological development strategy. Therefore, the technical early warning and assessment are increasingly attracting attention.
In the related art, when the technology is evaluated, the evaluation is usually performed by means of expert research and judgment or questionnaire survey. For example, the delphi method is a typical technical evaluation method, and conducts investigation through multiple rounds of questions and answers to domain experts, so as to judge or make decisions about future technical development directions when the opinions of the experts are consistent. In addition, in the related technology, an analytic hierarchy process, an entropy weight method, an approximate ideal solution sorting method and the like all take the statistical result of the expert questionnaire as an object, and the technical development condition is judged by calculating the weight and the score.
However, the above related technical evaluation methods are based on the conclusions of the experts involved in the research, and cannot avoid the interference of human subjective factors on the evaluation results, and the evaluation results depend on the cognition of the experts involved in the research to a great extent, and are more limited, less scientific and interpretable, and difficult to reproduce. Moreover, in practical application, multiple rounds of investigation lead to high evaluation cost and complex process.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present application is to provide a multidimensional technology evaluation method based on big data, which performs comprehensive evaluation on technologies in a qualitative and quantitative combination manner based on scientific and technological big data and literature measurement, and can organically combine objective data calculation results with expert opinions, thereby implementing universal multidimensional technology early warning and comprehensive evaluation in different fields, improving the scientificity and accuracy of technology evaluation, and reducing the cost and complexity of evaluation.
A second objective of the present application is to provide a multidimensional technology evaluation system based on big data.
A third object of the present application is to propose a non-transitory computer-readable storage medium.
In order to achieve the above object, an embodiment of a first aspect of the present application provides a method for multidimensional technology evaluation based on big data, including the following steps:
taking a technical point or a technical field to be evaluated as an evaluation target, and collecting big data aiming at the evaluation target, wherein the collected data comprises a thesis and a patent corresponding to the evaluation target;
carrying out expert investigation on the technical completeness level TRL of the evaluation target;
constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and development and industrialization;
and calculating each index in the technical comprehensive assessment index system according to the collected data and the results of expert research, and counting the calculation result of each index to generate a comprehensive assessment result of the assessment target.
Optionally, in an embodiment of the present application, the big data collection for the evaluation target includes: setting a retrieval rule for the technical name of the evaluation target; searching a corresponding thesis in a preset target thesis database according to the search rule to serve as a data source for technical research and development evaluation; searching a corresponding patent in a preset target patent database according to the search rule to serve as a data source for technical industrialization evaluation; and (4) counting the time series data of published quantities of the papers and the patents under different years.
Optionally, in an embodiment of the present application, the technology comprehensive assessment index system includes: the technical completeness index, the technical research and development maturity index, the technical industrialization maturity index, the technical research and development fusion degree index and the technical industrialization fusion degree index.
Optionally, in an embodiment of the application, calculating each index in the technical comprehensive assessment index system includes: when the technical completeness index is calculated, acquiring an expert set participating in the expert research and a rating result of each expert in the expert set; determining an initial assessment result of the technical completeness index by calculating the mode of all the assessment level results; and judging whether the frequency of the mode is more than or equal to half of the number of the experts, if so, converting the initial evaluation result of the technical completeness index into a percentile system to obtain the evaluation result of the technical completeness index, and if not, re-performing expert investigation.
Optionally, in an embodiment of the application, calculating each index in the technical comprehensive assessment index system includes: when the technology development maturity index is calculated, S-shaped curve fitting is carried out on the technology life cycle according to the time series data of the publication number of the thesis, wherein the formula of the S-shaped curve fitting is as follows:
Figure BDA0003856149560000021
wherein alpha is a position coefficient of the curve, beta is a shape coefficient of the curve, alpha and beta are constants, L represents an upper limit value of the technical life cycle curve, t represents the year, y is a vertical axis coordinate of a point on the S-shaped curve, and y belongs to (0, L); converting the S-shaped curve fitting formula to obtain a deformation formula shown as follows:
Figure BDA0003856149560000022
substituting the publication numbers of the papers in different years into the deformation formula, solving the values of alpha, beta and L based on a least square method, converting the solved values into a percentile system, and obtaining the evaluation result of the research and development maturity index of the technology.
Optionally, in an embodiment of the present application, calculating each index in the technical comprehensive assessment index system includes: when the technology research and development fusion degree index is calculated, counting the number of disciplines, the names of the disciplines and the number of papers corresponding to each discipline in a paper set corresponding to the evaluation target; calculating the proportion of each subject in the evaluation target; calculating the initial evaluation result of the technical development fusion degree index through the following formula:
Figure BDA0003856149560000031
wherein Originaluty o Is the initial evaluation result of the technology research and development fusion degree index, p is the evaluation target and is the subject quantity, s pi Represents the proportion of i disciplines in the p field, i represents any discipline in the p field; and converting the initial evaluation result of the technology research and development fusion degree index into a percentile system to obtain the evaluation result of the technology research and development fusion degree index.
In order to achieve the above object, a second aspect of the present application provides a multidimensional technology evaluation system based on big data, including the following modules:
the system comprises a collecting module, a judging module and a processing module, wherein the collecting module is used for collecting big data aiming at an evaluation target by taking a technical point or a technical field to be evaluated as the evaluation target, and the collected data comprises a paper and a patent corresponding to the evaluation target;
the investigation module is used for carrying out expert investigation on the TRL of the technical completeness level of the evaluation target;
the construction module is used for constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and development and industrialization;
and the calculation module is used for calculating each index in the technical comprehensive evaluation index system according to the collected data and the expert investigation result, counting the calculation result of each index and generating the comprehensive evaluation result of the evaluation target.
Optionally, in an embodiment of the present application, the collection module is specifically configured to: setting a retrieval rule for the technical name of the evaluation target; searching a corresponding paper in a preset target paper database according to the search rule to serve as a data source for technical research and development evaluation; searching a corresponding patent in a preset target patent database according to the search rule to serve as a data source for technical industrialization evaluation; and (4) counting the time series data of published quantities of the papers and the patents under different years.
Optionally, in an embodiment of the present application, the technology integrated assessment index system includes: the system comprises a technical completeness index, a technical research and development maturity index, a technical industrialization maturity index, a technical research and development fusion index and a technical industrialization fusion index.
In order to implement the foregoing embodiments, the third aspect of the present application further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for large-data-based multidimensional technology evaluation in the foregoing embodiments is implemented.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects: the method and the device collect data aiming at the evaluation object and complete expert investigation; then, carrying out multi-dimensional evaluation index design according to angles such as technology research and industrialization and the like to form a multi-dimensional comprehensive technology evaluation index system; and calculating the indexes related to the technology and counting the expert viewpoints by utilizing the collected scientific and technological data resources and the expert research results to generate a comprehensive evaluation result. Therefore, the technology is comprehensively evaluated in a qualitative and quantitative combination mode based on scientific and technological big data, literature measurement and expert research results, objective data calculation results can be organically combined with expert viewpoints, universal multi-dimensional technology early warning and comprehensive evaluation in different fields are achieved, the expandability, scientificity, interpretability and feasibility are achieved, standards are provided for technical evaluation in the universal fields, accuracy of technology evaluation is improved, cost and complexity of evaluation are reduced, and the technology is convenient to implement in practical application.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which
Fig. 1 is a flowchart of a multidimensional technical evaluation method based on big data according to an embodiment of the present application;
FIG. 2 is a schematic structural diagram of a comprehensive evaluation index system according to an embodiment of the present disclosure;
fig. 3 is a flowchart of a method for calculating a technical completeness index according to an embodiment of the present application;
fig. 4 is a flowchart of a method for calculating a technology development maturity indicator according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a multidimensional technology evaluation system based on big data according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
It should be noted that, at present, barriers still exist in the technical evaluation methods of different analysis dimensions and different fields. In the embodiment of the application, the microscopic technical early warning can be evaluated by taking a patent or a technical safety specific event as a minimum knowledge unit, the mesoscopic technical early warning is mostly analyzed from the perspective of an enterprise, the enterprise-owned patent data is generally adopted for analysis, and the basic statistical analysis, the trend analysis, the correlation analysis and other common evaluation methods are adopted for macroscopic early warning in the technical field.
Moreover, with the development of artificial intelligence and the arrival of the big data era, scientific and technological data such as papers, patents and the like become important data sources for technical assessment and early warning, and the retrieval platforms of various scientific and technological publications converge scientific and technological achievements in different fields around the world and provide various knowledge sharing services, thereby providing resources for modern technical assessment. Therefore, the intelligent technology evaluation method can be researched based on the existing technology big data resources and the technology evaluation theoretical basis.
However, different technical evaluation methods in the related art have limitations in application scenarios, and an organic fusion method or a general-purpose technology-oriented early warning tool is lacking. Therefore, the multidimensional technical evaluation method based on big data is provided, and the large amount of objective data calculation results can be organically combined with expert opinions, so that universal multidimensional technical early warning and comprehensive evaluation in different fields can be realized.
The following describes a multidimensional technology evaluation method and system based on big data, which is proposed by the embodiment of the invention, with reference to the attached drawings.
Fig. 1 is a flowchart of a method for evaluating a multidimensional technology based on big data according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S101, taking a technical point or a technical field to be evaluated as an evaluation target, and collecting big data aiming at the evaluation target, wherein the collected data comprises a paper and a patent corresponding to the evaluation target.
Specifically, scientific and technical big data retrieval and collection are performed in the step. First, an evaluation target needs to be determined, and in the present application, the evaluation target may be a specific technical point or a technical field including a plurality of similar technical points. For example, the application can select a technical point of a long-short term memory neural network (LSTM) as an evaluation target, and can also select a technical field of artificial intelligence AI as an evaluation target. Therefore, the types of research targets capable of being evaluated are enriched, and technologies of different levels can be evaluated.
Furthermore, a data source for technical evaluation is determined, a large amount of related scientific and technological data are retrieved and collected from the data source, and a data basis is provided for subsequent evaluation index calculation and comprehensive evaluation. Scientific and technical data collected in this application include papers and patents related to assessment goals.
In one embodiment of the present application, big data collection for assessment goals includes the following steps: first, a search rule is set for the technical name of the evaluation target. And then, searching a corresponding thesis in a preset target thesis database according to the search rule to serve as a data source for technical research and development evaluation. And searching a corresponding patent in a preset target patent database according to the search rule to serve as a data source for technical industrialization evaluation. And finally, counting the time series data of the publication numbers of the papers and the patents in different years.
Specifically, the embodiment of the application determines that the evaluation target is a technical term or a technical field of a specification, and facilitates experts who participate in technical evaluation later to carry out further analysis by setting a concise and concise technical name of the evaluation target. Then, a search rule is set for the determined technical name, and in the present embodiment, the search rule is an abbreviation that contains information or is common in the field capable of summarizing key features of technical terms. Continuing with the above example, if the set evaluation target is "artificial intelligence AI", the set retrieval rule is: "artificalininelligent" ORAI.
Further, a target thesis database is selected as a data source for developing technical research and development evaluation, a target patent database is selected as a data source for technical industrialization evaluation, for example, a Webofscience core theory library is selected as a data source for developing technical research and development early warning, and a patent retrieval result in a DerwentInnovationIndex is selected as a data source for technical industrialization early warning. Then, retrieval is carried out in the two data sources through the retrieval rules respectively, and collection of science and technology big data is carried out. The specific implementation manner of collecting the big data in the database may refer to the implementation manner in the related art, for example, the big data collection is completed by performing fragmentation in the database.
Furthermore, the papers and patents collected according to the retrieval rule are processed, and the data with weak correlation is eliminated through repeated investigation, the chronological data of the quantity of the papers and patents in different years related to the technical points is obtained through statistics, and the chronological data of the quantity of the papers and patents in different years is obtained through sorting according to the years of the papers and patents. Therefore, a foundation is laid for further evaluation index calculation and comprehensive evaluation through collection of information of the thesis and the patent related to subject field types and the like.
Step S102, carrying out expert investigation on the technical completeness level TRL of the evaluation target.
Among them, the Technology completeness Level (TRL) is an index for measuring the Technology development maturity, is used for evaluating the Technology maturity in the aerospace field at first, is a commonly used Technology evaluation standard in each field at present, and has different definitions in different fields.
In one embodiment of the present application, in order to improve the applicability of the evaluation method of the present application, for the complete rating evaluation in the general technical field, different ratings in the TRL are defined as shown in the following table 1:
TABLE 1
Figure BDA0003856149560000061
Specifically, in the step, expert investigation is performed according to the technical completeness level of the evaluation target, an expert investigation plan is formulated according to the preset target technical field, and the technical completeness level (TRL) is adopted as the standard of technical qualitative evaluation. And (3) according to the relation of a domain authority expert list and expert investigation of the organization technology complete level, distributing a questionnaire with standard design and brief introduction to experts, wherein the questionnaire comprises detailed definitions and descriptions of relevant research target technologies and different levels of TRLs, and recycling and arranging the questionnaire after the experts finish evaluation. And a foundation is laid for qualitative analysis of technical evaluation through expert investigation of technical completeness level.
When the method is specifically implemented, as a possible implementation mode, the TRL 9-level complete technology level is used as a standard of expert evaluation, and before the evaluation is started, an expert list participating in the technology early warning evaluation is formulated through overall planning and evaluating expert resources in the technical field and is used as an investigation object of an expert investigation link. Then designing an expert questionnaire, clarifying the importance of technical early warning evaluation in the questionnaire, explaining field information, research content and the like contained in technical points, displaying specific definitions of different levels of the TRL in the general technical field, and assisting experts in studying and judging. And finally, ensuring that the experts participating in the research independently complete the technical complete grade assessment, and recovering the questionnaire in an online or offline mode after all the experts complete the research and judgment.
And S103, constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and industrialization.
Specifically, multi-dimensional evaluation index design is carried out according to the angles of technology research and development, industrialization and the like, and a technology comprehensive evaluation index system is formed. When an index system is constructed, a plurality of technical indexes are set, and the technology is evaluated from qualitative and quantitative angles. A feasible and interpretable scientific basis is provided for technical evaluation by constructing a multi-dimensional comprehensive evaluation index system.
Specifically, the application uses scientific and technological papers as key achievement forms in the process of technology research and development, and uses patent data as main expression forms in the process of technology industrialization and achievement transformation, which respectively represent the development conditions of technologies in research and development and industry. The established technical early warning index system supports 'qualitative + quantitative' technical evaluation.
Based on the above construction strategy, in an embodiment of the present application, as shown in fig. 2, a constructed technology comprehensive evaluation index system includes: index of degree of technical completeness x 1 And a technology research and development maturity index x 2 And technical industrialization maturity index x 3 And a technology research and development fusion degree index x 4 And technical industrialization fusion degree index x 5 And forming multi-dimensional evaluation indexes comprising expert judging results, research and development and industrial data by using the 5 indexes, and realizing technical evaluation analysis applicable to multiple fields. Each index may subsequently be calculated from the corresponding data. The dashed boxes in fig. 2 containing the respective indices represent data for calculating the indices.
And step S104, calculating each index in the technical comprehensive evaluation index system according to the collected data and the results of expert investigation, and counting the calculation result of each index to generate a comprehensive evaluation result of an evaluation target.
Specifically, the step calculates the evaluation indexes and counts the expert research results, calculates each index in the technical comprehensive evaluation index system constructed in the previous step according to the collected data (thesis and patents) and the expert research results, and then generates the final comprehensive evaluation result of the evaluation target according to the calculation results of each index.
In an embodiment of the present application, with continuing reference to the example of the comprehensive evaluation index system constructed in the previous step, a specific process for calculating 5 indexes in the index system is as follows:
as a first example, a technical completeness index is calculated. In this example, in order to more clearly describe a specific implementation process of calculating the technical completeness index, an exemplary description is given below by using a calculation method proposed in the embodiment of the present application. Fig. 3 is a flowchart of a method for calculating a technical completeness index according to an embodiment of the present application, and as shown in fig. 3, the method includes the following steps:
step S301, acquiring an expert set participating in expert research and a rating result of each expert in the expert set.
Specifically, each expert participating in the research and the corresponding evaluation result thereof are determined by counting the recovered questionnaire. For a set of experts X participating in the research, X = { X = { n } 1 ，x 2 ，...，x N N is the number of experts participating in the investigation, x i Is the rating result of the ith expert, wherein i =1,2.
Step S302, the initial assessment result of the technical completeness index is determined by calculating the mode of all the assessment grade results.
Specifically, the evaluation result of the technical completeness is calculated by solving a mode of an expert rating level, wherein the mode refers to a numerical value with a significant central tendency point on a statistical distribution and represents a general level of data. In the embodiment of the application, the mode is the rating with the largest occurrence number in the data group of the rating results of all experts.
In the embodiment of the application, the occurrence frequency of each rating result is counted, the rating with the largest occurrence frequency is determined to be a mode x', and the frequency n of the mode is recorded.
In step S303, it is determined whether the frequency of the mode is equal to or greater than half of the number of experts, if so, step S304 is performed, and if not, step S305 is performed.
Step S304, the initial assessment result of the technical completeness index is converted into a percentile system.
Specifically, if the frequency N of occurrence of the mode x 'exceeds half of the number of experts, namely N is more than or equal to N/2, taking x' as a technical completeness level evaluation result and converting the technical completeness level evaluation result into a percentile system x. Thereby obtaining the evaluation result of the technical completeness index.
In step S305, the expert investigation is performed again, and the process returns to step S301.
Specifically, if N is less than N/2, a "temporary result" needs to be returned, which indicates that the expert investigates the result with a large deviation and generates a temporary consensus evaluation result, and the expert needs to be reorganized to perform a new round of investigation. And returning to the step S301 to repeatedly execute the steps until the occurrence frequency n of the mode x' is determined to be more than half of the number of experts, and obtaining the final evaluation result of the technical completeness index.
In this example, the final x 1 ＝x，x 1 That is, the calculation result of the technical completeness index in the technical early warning assessment index system shown in fig. 2.
As a second example, a computational technology development maturity indicator. In this example, in order to more clearly illustrate a specific implementation process of calculating a technology development maturity index, an exemplary description is given below of a calculation method provided in the embodiment of the present application. Fig. 4 is a flowchart of a method for calculating a technology development maturity index according to an embodiment of the present application, and as shown in fig. 4, the method includes the following steps:
step S401, performing S-shaped curve fitting on the technology life cycle according to the time series data of the publication number of the paper.
The S-shaped curve is a rule for predicting the life cycle of the technology, can be approximately regarded as a technology maturity prediction curve meeting the technology evolution rule, and divides the technology evolution process into four stages, namely a baby stage, a growth stage, a maturity stage and a decline stage.
Specifically, in the embodiment, the technical development maturity is subjected to the fitting of the life cycle of the S-type technology according to the time sequence change of the published quantity of the scientific and technological papers, the fitting result is converted in percentage by combining with the bearing capacity developed in the current field, and the calculation result is used as an evaluation standard for measuring the growth speed and the development level in the technical development aspect. In a specific calculation process, firstly, fitting an "S" type curve, wherein the expression is as follows:
Figure BDA0003856149560000091
wherein alpha is a position coefficient of the curve, beta is a shape coefficient of the curve, alpha and beta are constants, L represents an upper limit value of the technical life cycle curve, t represents the year, y is a vertical axis coordinate of a point on the S-shaped curve, and y belongs to (0, L).
Wherein t and y are both historical data, and are collected in the above embodiments. The alpha, the beta and the L are obtained by curve fitting solution.
And step S402, converting the S-shaped curve fitting formula to obtain a deformation formula.
Specifically, the following formula is obtained by transforming the curve fitting formula and taking the logarithm:
Figure BDA0003856149560000092
the meaning of each parameter in the formula is the same as that in the formula of fitting the S-shaped curve, and the description is omitted here.
And S403, substituting the publication numbers of the papers in different years into a deformation formula, solving the numerical value of the curve coefficient based on a least square method, and converting the solved numerical value into a percentile system to obtain the evaluation result of the technical research and development maturity index.
Specifically, historical data, namely years related to technical points and the publication amount of a paper in the current year, are substituted into the deformation formula, the minimum mode is solved by using a least square method, and then the corresponding values of alpha, beta and L are obtained. Defining the calculation result of the research and development maturity of the technology as x 2 ：
Figure BDA0003856149560000093
x 2 That is, the calculation result of the technology development maturity in the technology early warning evaluation index system shown in fig. 2.
As a third example, a technology industrialization maturity index is calculated. In this example, the technology industrialization maturity degree can be calculated from the number of patent applications related to the technology point, and the technology industrialization maturity degree calculation result is defined as x in fig. 2, where the technology industrialization maturity degree calculation result is calculated from the number of patent applications measured according to the historical time series data of the annual statistics 3 。
As a fourth example, computing techniques develop a fusion degree index. In the present example, the number of disciplines, the names of the disciplines, and the number of papers corresponding to each discipline contained in the paper set corresponding to the evaluation target are counted; calculating the proportion of each subject in the evaluation target; the initial evaluation result of the technology research and development fusion degree index is calculated through the following formula:
Figure BDA0003856149560000094
wherein, the origin p Is the initial evaluation result of the technology research and development fusion degree index, p is the evaluation target, N is the subject number, s pi Represents the proportion of i subjects in the p field, wherein i represents any subject in the p field; and converting the initial evaluation result of the technology research and development fusion degree index into a percentile system to obtain the evaluation result of the technology research and development fusion degree index.
Specifically, a calculation mode of technology research and development fusion degree in the related technology is mainly used for measuring and calculating a microscopic single patent, and in order to meet the macroscopic evaluation requirement facing the technical field, the application provides a method for measuring and calculating technology research and development and industrialization fusion degree by using papers and patent data. The specific calculation method is as follows:
firstly, for a thesaurus related to a target technology p, according to the standard of the field of the technology, the subject names, the subject number N and the thesis number containing the subject contained in the thesaurus are counted, the proportion of different subjects in the field is calculated, and s is used pi Represents the number proportion of i disciplines in the field of p. The method for calculating the original value of the fusion degree in research and development in the technical field p comprises the following steps:
Figure BDA0003856149560000101
Originality p the value range is between 0 and 1, and the closer the value is to 1, the higher the originality degree of the technical field is. Defining the technology development fusion degree as x 4 And then:
x 4 ＝Originality p ×100
x 4 the index is the index of knowledge fusion degree of the research and development results in the evaluation technical field shown in fig. 2, and provides technical safety evaluation information for the technical early warning comprehensive evaluation.
As a fifth exampleAnd calculating the technical industrialization fusion degree index. In this example, the technology industrialization maturity is using patent data for origin p The specific calculation method is described in the fourth example, and the calculation result of the technology industrialization fusion degree after the percentile processing is recorded as x 5 That is, the calculation result of the technical industrialization fusion degree index shown in fig. 2 is information for providing technical industrialization safety evaluation for the technical early warning comprehensive evaluation.
Therefore, after data statistics is carried out on data collection results, each evaluation index is calculated according to the calculation method, calculation results of each index are counted, and comprehensive evaluation results of evaluation targets are generated according to the statistical results.
In an embodiment of the present application, with continuing reference to the above-mentioned embodiment, since each index is a numerical value ranging from 0 to 100, the calculation results of each index can be collectively shown in the same way. For example, the calculation results of the indexes are shown by a statistical graph such as a histogram. For another example, a radar map can be introduced as a statistical and display mode of calculation results of various technical evaluation indexes, a coordinate system corresponding to each index in a technical evaluation index system is created in the radar map, the maximum value of each coordinate system is the same, then corresponding points of the calculation results of each index in the corresponding coordinate system are determined, the first area of a polygon formed by connecting all the corresponding points is calculated, and the second area of a regular polygon formed by connecting the maximum points of each coordinate system is calculated; and then calculating the ratio of the first area to the second area, and determining the evaluation grade of the evaluation target according to the ratio, so that the method can be suitable for the technical evaluation quantitative analysis of different scenes. The technical evaluation can be evaluated from two aspects of qualitative and quantitative, and the current aspects of the technology are reflected, so that the comprehensive evaluation result of the evaluation target is obtained.
To sum up, the multidimensional technical evaluation method based on big data according to the embodiment of the application first collects data for an evaluation object to complete expert investigation, then performs multidimensional evaluation index design according to the angles of technical research and development, industrialization and the like to form a multidimensional technical comprehensive evaluation index system, and then calculates and counts expert viewpoints for technical related indexes by using collected scientific and technological data resources and expert research results to generate a comprehensive evaluation result. Therefore, the method is based on scientific and technological big data, literature measurement and expert research results, comprehensive evaluation is carried out on the technology in a qualitative and quantitative combination mode, objective data calculation results and expert viewpoints can be organically combined, universal multi-dimensional technology early warning and comprehensive evaluation in different fields are achieved, the method has expandability, scientificity, interpretability and feasibility, standards are provided for technical evaluation in the universal fields, accuracy of technology evaluation is improved, cost and complexity of evaluation are reduced, and the method is convenient to implement in practical application.
In order to implement the above embodiments, the present application further provides a multidimensional technology evaluation system based on big data.
Fig. 5 is a schematic structural diagram of a multidimensional technology evaluation system based on big data according to an embodiment of the present application.
As shown in FIG. 5, the big data based multi-dimensional technology evaluation system includes a collection module 100, a research module 200, a construction module 300, and a calculation module 400.
The collection module 100 is configured to collect big data for an evaluation target by taking a technical point or a technical field to be evaluated as the evaluation target, where the collected data includes a thesis and a patent corresponding to the evaluation target.
And the investigation module 200 is used for carrying out expert investigation on the technical completeness level TRL of the evaluation target.
The building module 300 is used for building a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology development and industrialization.
And the calculating module 400 is used for calculating each index in the technical comprehensive evaluation index system according to the collected data and the results of expert research, counting the calculation result of each index, and generating a comprehensive evaluation result of an evaluation target.
Optionally, in an embodiment of the present application, the collection module 100 is specifically configured to: setting a retrieval rule aiming at the technical name of the evaluation target; searching a corresponding paper in a preset target paper database according to a search rule to serve as a data source for technical research and development evaluation; searching a corresponding patent in a preset target patent database according to a search rule to serve as a data source for technical industrialization evaluation; and (5) counting the time series data of the publication numbers of the papers and the patents under different years.
Optionally, in an embodiment of the present application, the technology comprehensive assessment index system constructed by the construction module 300 includes: the technical completeness index, the technical research and development maturity index, the technical industrialization maturity index, the technical research and development fusion degree index and the technical industrialization fusion degree index.
Optionally, in an embodiment of the present application, the computing module 400 is specifically configured to: when the technical completeness index is calculated, acquiring an expert set participating in expert research and a rating result of each expert in the expert set; determining an initial evaluation result of the technical completeness index by calculating the mode of all the evaluation grade results; and judging whether the frequency of the mode is more than or equal to half of the number of the experts, if so, converting the initial evaluation result of the technical completeness index into a percentile system to obtain the evaluation result of the technical completeness index, and if not, re-performing expert research.
Optionally, in an embodiment of the present application, the calculation module 400 is further configured to: when a technology research and development maturity index is calculated, S-shaped curve fitting is carried out on the technology life cycle according to the time series data of the publication number of papers, wherein the formula of the S-shaped curve fitting is as follows:
Figure BDA0003856149560000121
wherein alpha is a position coefficient of the curve, beta is a shape coefficient of the curve, alpha and beta are constants, L represents an upper limit value of the technical life cycle curve, t represents the year, y is a vertical axis coordinate of a point on the S-shaped curve, and y belongs to (0, L); transforming the formula of the S-shaped curve fitting to obtain the following deformation formula:
Figure BDA0003856149560000122
substituting the publication numbers of the papers in different years into the deformation formula, solving the values of alpha, beta and L based on a least square method, and converting the solved values into a percentile system to obtain the evaluation result of the technical research and development maturity index.
Optionally, in an embodiment of the present application, the computing module 400 is further configured to: when a fusion degree index is researched and developed by computing technology, counting the number of disciplines, the names of the disciplines and the number of papers corresponding to each discipline in a paper set corresponding to an evaluation target; calculating the proportion of each subject in the evaluation target; the initial evaluation result of the fusion degree index is researched and developed through the following formula calculation technology:
Figure BDA0003856149560000123
wherein, the origin p Is the initial evaluation result of the technology research and development fusion degree index, p is the evaluation target, N is the subject number, s pi Represents the proportion of i disciplines in the p field, i represents any discipline in the p field; and converting the initial evaluation result of the technology research and development fusion degree index into a percentile system to obtain the evaluation result of the technology research and development fusion degree index.
In summary, the multidimensional technology evaluation system based on big data in the embodiment of the application performs comprehensive evaluation on technologies in a qualitative and quantitative combination manner based on scientific and technological big data, literature measurement and expert research results, can organically combine objective data calculation results with expert opinions, achieves universal multidimensional technology early warning and comprehensive evaluation in different fields, has expandability, scientificity, interpretability and feasibility, provides standards for technical evaluation in the general fields, improves accuracy of technology evaluation, reduces cost and complexity of evaluation, and is convenient to implement in practical application.
In order to implement the foregoing embodiments, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for multidimensional technology evaluation based on big data according to the embodiment of the first aspect of the present application.
In the description of the present specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In the present specification, if a schematic expression of the above-described terms is employed in a plurality of embodiments or examples, it does not mean that the embodiments or examples are the same. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (10)

1. A multidimensional technology evaluation method based on big data is characterized by comprising the following steps:
taking a technical point or a technical field to be evaluated as an evaluation target, and collecting big data aiming at the evaluation target, wherein the collected data comprises a thesis and a patent corresponding to the evaluation target;
carrying out expert investigation on the technical completeness level TRL of the evaluation target;
constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and development and industrialization;
and calculating each index in the technical comprehensive assessment index system according to the collected data and the results of expert research, and counting the calculation result of each index to generate a comprehensive assessment result of the assessment target.
2. The technical assessment method according to claim 1, wherein said collecting big data for said assessment target comprises:
setting a retrieval rule for the technical name of the evaluation target;
searching a corresponding thesis in a preset target thesis database according to the search rule to serve as a data source for technical research and development evaluation;
searching a corresponding patent in a preset target patent database according to the search rule to serve as a data source for technical industrialization evaluation;
and (4) counting the time series data of published quantities of the papers and the patents under different years.
3. The technical assessment method according to claim 1, wherein said technical synthesis assessment index system comprises: the technical completeness index, the technical research and development maturity index, the technical industrialization maturity index, the technical research and development fusion degree index and the technical industrialization fusion degree index.
4. The technical assessment method according to claim 3, wherein the calculating each index in the technical composite assessment index system comprises:
when the technical completeness index is calculated, acquiring an expert set participating in the expert research and a rating result of each expert in the expert set;
determining an initial assessment result of the technical completeness index by calculating the mode of all the assessment level results;
and judging whether the frequency of the mode is more than or equal to half of the number of the experts, if so, converting the initial evaluation result of the technical completeness index into a percentile system to obtain the evaluation result of the technical completeness index, and if not, re-performing expert investigation.
5. The method according to claim 3, wherein the calculating each index in the technical composite assessment index system comprises:
when the technology research and development maturity index is calculated, S-shaped curve fitting is carried out on the technology life cycle according to the time series data of the publication number of the papers, wherein the formula of the S-shaped curve fitting is as follows:
Figure FDA0003856149550000021
wherein alpha is a position coefficient of the curve, beta is a shape coefficient of the curve, alpha and beta are constants, L represents an upper limit value of the technical life cycle curve, t represents the year, y is a vertical axis coordinate of a point on the S-shaped curve, and y belongs to (0, L);
and converting the S-shaped curve fitting formula to obtain a deformation formula shown as follows:
Figure FDA0003856149550000022
substituting the publication numbers of the papers in different years into the deformation formula, solving the values of alpha, beta and L based on a least square method, and converting the solved values into a percentile system to obtain the evaluation result of the technical research and development maturity index.
6. The technical assessment method according to claim 3, wherein the calculating each index in the technical composite assessment index system comprises:
when the technology research and development fusion degree index is calculated, the subject number, the subject name and the thesis number corresponding to each subject contained in the thesis set corresponding to the evaluation target are counted;
calculating the proportion of each subject in the evaluation target;
calculating the initial evaluation result of the technology research and development fusion degree index through the following formula:
Figure FDA0003856149550000023
wherein, origin p Is the initial evaluation result of the technology research and development fusion degree index, p is the evaluation target, N is the subject number, s pi Represents the proportion of i disciplines in the p field, i represents any discipline in the p field;
and converting the initial evaluation result of the technology research and development fusion degree index into a percentile system to obtain the evaluation result of the technology research and development fusion degree index.
7. A big data-based multi-dimensional technology evaluation system is characterized by comprising:
the system comprises a collecting module, a judging module and a processing module, wherein the collecting module is used for collecting big data aiming at an evaluation target by taking a technical point or a technical field to be evaluated as the evaluation target, and the collected data comprises a thesis and a patent corresponding to the evaluation target;
the investigation module is used for carrying out expert investigation on the technical completeness level TRL of the evaluation target;
the construction module is used for constructing a multi-dimensional technology comprehensive evaluation index system from multiple angles including technology research and industrialization;
and the calculation module is used for calculating each index in the technical comprehensive evaluation index system according to the collected data and the expert investigation result, counting the calculation result of each index and generating the comprehensive evaluation result of the evaluation target.
8. The technology evaluation system of claim 7, wherein the collection module is specifically configured to:
setting a retrieval rule aiming at the technical name of the evaluation target;
searching a corresponding thesis in a preset target thesis database according to the search rule to serve as a data source for technical research and development evaluation;
searching a corresponding patent in a preset target patent database according to the search rule to serve as a data source for technical industrialization evaluation;
and (4) counting the time series data of published quantities of the papers and the patents under different years.
9. The technical assessment system according to claim 7, wherein the technical portfolio assessment index system comprises: the technical completeness index, the technical research and development maturity index, the technical industrialization maturity index, the technical research and development fusion degree index and the technical industrialization fusion degree index.
10. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the big data based multi-dimensional technology evaluation method of any of claims 1-6.
CN202211149115.8A 2022-09-21 2022-09-21 Multi-dimensional technology evaluation method and system based on big data Pending CN115544114A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116757314A (en) * 2023-06-02 2023-09-15 中国人民解放军军事科学院国防科技创新研究院 Technology prediction method and system based on big data and artificial intelligence fusion driving

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116757314A (en) * 2023-06-02 2023-09-15 中国人民解放军军事科学院国防科技创新研究院 Technology prediction method and system based on big data and artificial intelligence fusion driving
CN116757314B (en) * 2023-06-02 2024-03-19 中国人民解放军军事科学院国防科技创新研究院 Technology prediction method and system based on big data and artificial intelligence fusion driving

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