CN111815125A - Innovative entity science and technology evaluation system optimization method and device based on technical atlas - Google Patents
Innovative entity science and technology evaluation system optimization method and device based on technical atlas Download PDFInfo
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Abstract
The invention relates to a technical atlas-based innovation entity science and technology evaluation system optimization method and a device, wherein the method comprises the following steps: acquiring scientific and technological information resources, establishing a scientific and technological resource library and extracting an innovation entity; constructing a technical map based on scientific and technological information resources in a scientific and technological resource library and dynamically updating; acquiring indexes of each innovation entity, which are related to the thesis, the patent and the technical map, and clustering the innovation entities by taking the indexes as variables; and (3) endowing each group with a label for representing the innovation capability, taking the label of each group as a target variable, and obtaining an index of a technical innovation index system which is reserved by the cooperation of a variable set closely related to the target variable by adopting multivariate analysis. Compared with the prior art, the method adopts clustering and machine learning technologies to optimize the innovative entity science and technology evaluation system, can effectively utilize massive big data, and solves the problem of strong subjectivity caused by manually setting indexes.
Description
Technical Field
The invention relates to the field of scientific and technological innovation evaluation, in particular to a technical atlas-based innovation entity scientific and technological evaluation system optimization method and device.
Background
The technical evaluation system is an evaluation framework for the basic innovation capability of an individual, an enterprise or a research institution. The technical innovation capability is the capability of an innovation entity on the basis of integrating all the components of a technical innovation system, so that more advanced productivity is created, and the technical innovation strategy target is better realized. The technical evaluation of the innovation subject is a complex system problem, and currently, the technical evaluation still remains in the stage of manually setting indexes, such as the number of articles published in a core journal and the number of patents.
The artificially set indexes cannot effectively utilize the increasing data, and the artificially set indexes have hysteresis and have great one-sided problems and cannot truly reflect the technological innovation level of an innovation entity.
Disclosure of Invention
The invention aims to provide an innovative entity science and technology evaluation system optimization method and device based on a technical atlas.
The purpose of the invention can be realized by the following technical scheme:
an innovative entity scientific and technological evaluation system optimization method based on a technical atlas,
constructing a technical map based on scientific and technological information resources in a scientific and technological resource library and dynamically updating;
acquiring indexes of each innovation entity, which are related to the thesis, the patent and the technical map, and clustering the innovation entities by taking the indexes as variables to obtain clustering results;
and (3) assigning labels for representing the innovation capability for each group based on the innovative entity science and technology evaluation system, taking the labels of each group as target variables, obtaining indexes of a technology innovation index system which is reserved by variable set cooperation closely related to the target variables by adopting multivariate analysis, and completing optimization of the innovative entity science and technology evaluation system.
Further, the indexes related to the papers at least comprise article quantity, core journal quantity and proportion, the indexes related to the patents at least comprise claim number, patent family number, specification page number, patent life and other patent citations, and the indexes related to the technical map at least comprise average distance, aggregation coefficient, in degree, out degree, intermediate degree and center degree.
Further, the innovative entities are clustered, specifically by using a KMeans clustering algorithm.
Further, the method further comprises:
based on the optimized innovative entity science and technology evaluation system, an evaluation model is constructed by adopting a classification algorithm;
when the innovative entity is newly introduced, the evaluation model is used for evaluating and predicting the newly introduced innovative entity and evaluating the innovative capability of the newly introduced innovative entity.
Further, the classification algorithm is a decision tree.
An innovative entity science and technology evaluation system optimization device based on a technical atlas comprises a memory, a processor and a program which is stored in the memory and executed by the processor, wherein the processor executes the program to realize the following steps:
acquiring scientific and technological information resources, establishing a scientific and technological resource library and extracting an innovation entity;
constructing a technical map based on scientific and technological information resources in a scientific and technological resource library and dynamically updating;
acquiring indexes of each innovation entity, which are related to the thesis, the patent and the technical map, and clustering the innovation entities by taking the indexes as variables to obtain clustering results;
and (3) assigning labels for representing the innovation capability for each group based on the innovative entity science and technology evaluation system, taking the labels of each group as target variables, obtaining indexes of a technology innovation index system which is reserved by variable set cooperation closely related to the target variables by adopting multivariate analysis, and completing optimization of the innovative entity science and technology evaluation system.
Compared with the prior art, the invention has the following beneficial effects:
1. the clustering and machine learning technology is adopted to optimize the innovative entity science and technology evaluation system, massive big data can be effectively utilized, and the problem of strong subjectivity caused by manual index setting is solved.
2. The technology such as graph database, complex network and machine learning is applied to a technology evaluation system, a key index set influencing technology evaluation is found out, the defects of single index and one-sidedness of a traditional evaluation mode are overcome, a new innovation entity is evaluated in real time, and scientific and technological evaluation and rapid decision-making of scientific and technological management workers are facilitated.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of the present invention;
FIG. 2 is a flowchart of innovation entity evaluation.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
An optimization method for a scientific and technological evaluation system of an innovation entity based on a technical atlas is realized by a computer system with a B/S architecture in a form of computer software, as shown in fig. 1, and specifically comprises the following steps:
constructing a technical map and dynamically updating based on scientific and technological information resources in a scientific and technological resource library, specifically, acquiring metadata including information of articles, patents, articles, research reports, scientific and technological achievements and the like from external data sources such as a knowledge network, a patent database and the like, then converting entities, acquiring information of authors, research institutions, keywords and the like in objects such as the articles, the patents, the articles, the research reports, the scientific and technological achievements and the like, creating entity objects such as research fields, researchers, the research institutions, the keywords and the like, then automatically constructing relationships through entity attributes, checking and maintaining the entity relationship attributes, and finally deducing a map database for constructing the technical map through the entities and the relationships, wherein innovative entities are individuals or organizations;
obtaining indexes related to treatises, patents and technical maps of each innovation entity to form a wide table taking a scientific and technological innovation main body as a row, wherein the indexes related to the treatises at least comprise article quantity, core journal quantity and proportion, the indexes related to the patents at least comprise claim quantity, family patent quantity, specification page number, patent life and other patent quotation quantity, and the indexes related to the technical maps at least comprise average distance, aggregation coefficient, income degree, output degree, betweenness, centrality and subgraph (scientific research team).
Clustering the innovation entities by adopting a KMeans clustering algorithm on the basis of the broad table of the innovation body and by taking the paper index, the patent related index and the technical map related index as variables to obtain a clustering result;
the method comprises the steps of giving labels for representing innovation capability height to each group based on an innovative entity science and technology evaluation system, obtaining indexes of a technology innovation index system reserved by variable sets closely related to target variables by adopting multivariate analysis by taking the labels of each group as the target variables, and completing optimization of the innovative entity science and technology evaluation system, wherein the closely related indexes are the first indexes (for example, the first 6-12 indexes) with the top correlation.
The evaluation index system is displayed on the display page in a KPI report form mode, the report form types comprise a KPI statistical report form and a KPI analysis report form, and the method also comprises the following steps: based on the optimized innovation entity science and technology evaluation system, an innovation capability evaluation prediction model is constructed by adopting a classification algorithm; as shown in FIG. 2, when a newly introduced innovation entity, the newly introduced innovation entity is evaluated for innovation capability ratings using an evaluation model. The classification algorithm is a decision tree.
Claims (10)
1. An innovative entity science and technology evaluation system optimization method based on a technical atlas is characterized by comprising the following steps:
acquiring scientific and technological information resources, establishing a scientific and technological resource library and extracting an innovation entity;
constructing a technical map based on scientific and technological information resources in a scientific and technological resource library and dynamically updating;
acquiring indexes of each innovation entity, which are related to the thesis, the patent and the technical map, and clustering the innovation entities by taking the indexes as variables to obtain clustering results;
and (3) assigning labels for representing the innovation capability for each group based on the innovative entity science and technology evaluation system, taking the labels of each group as target variables, obtaining indexes of a technology innovation index system which is reserved by variable set cooperation closely related to the target variables by adopting multivariate analysis, and completing optimization of the innovative entity science and technology evaluation system.
2. The method as claimed in claim 1, wherein the indexes related to the treatises include at least article quantity, core periodical quantity and proportion, the indexes related to the patents include at least claim number, patent family number, specification page number, patent lifetime and other patent citations, and the indexes related to the technical atlas include at least average distance, aggregation coefficient, income degree, output degree, intermediary number and centrality degree.
3. The method for generating a scientific and technological evaluation system of innovative entities based on technical atlases as claimed in claim 1, characterized in that the innovative entities are clustered, specifically using KMeans clustering algorithm.
4. The method for generating a scientific and technological evaluation system of an innovation entity based on a technical atlas as claimed in claim 1, the method further comprising:
based on the optimized innovative entity science and technology evaluation system, an evaluation model is constructed by adopting a classification algorithm;
when the innovative entity is newly introduced, the evaluation model is used for evaluating and predicting the newly introduced innovative entity and evaluating the innovative capability of the newly introduced innovative entity.
5. The method as claimed in claim 1, wherein the classification algorithm is a decision tree.
6. An innovative entity science and technology evaluation system optimization device based on a technical atlas, which comprises a memory, a processor and a program, wherein the program is stored in the memory and executed by the processor, and the processor executes the program to realize the following steps:
acquiring scientific and technological information resources, establishing a scientific and technological resource library and extracting an innovation entity;
constructing a technical map based on scientific and technological information resources in a scientific and technological resource library and dynamically updating;
acquiring indexes of each innovation entity, which are related to the thesis, the patent and the technical map, and clustering the innovation entities by taking the indexes as variables to obtain clustering results;
and (3) assigning labels for representing the innovation capability for each group based on the innovative entity science and technology evaluation system, taking the labels of each group as target variables, obtaining indexes of a technology innovation index system which is reserved by variable set cooperation closely related to the target variables by adopting multivariate analysis, and completing optimization of the innovative entity science and technology evaluation system.
7. The apparatus as claimed in claim 6, wherein the indexes related to the treatises include at least article quantity, core periodical quantity and proportion, the indexes related to the patents include at least claim number, patent family number, specification page number, patent lifetime and other patent citations, and the indexes related to the technical atlas include at least average distance, aggregation coefficient, income degree, output degree, intermediary number and centrality degree.
8. The device for generating a scientific and technological evaluation system of innovative entities based on technical atlases as claimed in claim 6, wherein the innovative entities are clustered by using KMeans clustering algorithm.
9. The apparatus according to claim 6, wherein the processor executes the program to perform the following steps:
based on the optimized innovative entity science and technology evaluation system, an evaluation model is constructed by adopting a classification algorithm;
when the innovative entity is newly introduced, the evaluation model is used for evaluating and predicting the newly introduced innovative entity and evaluating the innovative capability of the newly introduced innovative entity.
10. The apparatus according to claim 6, wherein the classification algorithm is a decision tree.
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Cited By (1)
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| CN113516411A (en) * | 2021-08-02 | 2021-10-19 | 上海量明科技发展有限公司 | Technical innovation capability evaluation method and system based on innovation element increment |
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Cited By (2)
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