CN113220667A - Scientific and technological big data element construction method and system, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a scientific and technical big data element construction method, a scientific and technical big data element construction system, electronic equipment and a storage medium, belonging to the technical field of Internet application, wherein the method comprises the following steps: integrating scientific and technological data sources and unifying the scientific and technological data to a unified platform; collecting the integrated scientific and technological data according to different requirements; storing the acquired scientific and technological data in a text structure according to a preset rule; analyzing the stored scientific and technical data; and constructing scientific and technical big data elements aiming at the analysis result. The system comprises: the device comprises a data integration module, a data acquisition module, a data storage module, a data analysis module and an element construction module. The invention solves the problems of complex general integration of scientific and technological resources and difficulty in sharing scientific and technological big data elements, avoids the problems of dispersion, difficulty in arrangement and difficulty in confirmation of scientific research expert data, and saves a large amount of non-key scientific and technological data acquisition, reconstruction and maintenance costs.
Description
Technical Field
The invention belongs to the technical field of internet application, and particularly relates to a method and a system for constructing scientific and technological big data elements, electronic equipment and a storage medium.
Background
Under the global and information-based internet large background, the online systems in the fields of the internet plus are gradually increased and continuously improved. Internet products in different fields are different and have different emphasis on business and provided services of enterprises, and data storage structures and data ranges from the products have no clear unified rules. Each internet product has its own unique label. Storage of data is also a fundamental requirement for current internet applications. Products with big data requirements need to acquire data, and data resources are divided according to different products and have trade-offs respectively. Data from the Internet and products are relatively complex, and the development and the upgrade of various large data application platforms at home and abroad are facilitated by the key technology and a large number of technical practitioners in China. The technology resource integration is beneficial to improving technology innovation and pushing economic development, and has important strategic significance. The scientific and technological resource platform is initially established in scale, so that the colleges and universities have certain progress in the management of scientific and technological resources, and a plurality of colleges and universities introduce informatization technology. However, due to high data complexity and strong professional, colleges and universities need to integrate the scientific and technological resources to construct the application products and method guidance of the scientific and technological resource big data elements in the aspects of scientific and technological resource integration and scientific and technological big data element construction research.
In summary, based on the background of the rapid development of the internet and the scientific background, colleges and universities are open to the integration of scientific resources and the construction, sharing and opening of elements, and play a very important role in future scientific development. This requires colleges and universities to continuously perfect the integration of scientific and technological resources and platform construction during the construction process. The application system combines scientific and technological resource integration and the establishment of a scientific and technological big data element and an informatization system to provide basic application and management functions.
Along with the technological innovation of domestic and foreign scholars, the research of the technological industry is continuously strengthened and deeply researched and explored, the difficulty of integrating the technological resources is easily found, the integration degree of the technological resources is not high, the big data of the technological resources is relatively dispersed, the resource access is too much, the big data elements of the technological integration are shared, the difference of the various regional industries is large, the uniform marking is not obvious, and the problem directly influences the technological innovation of enterprises, the scientific research institutions of colleges and universities and the difficulty in the transformation of the technological achievements of scientific research institutions. In addition, the development of cities is not scientific. From the practice in various places, the lack of clear scientific and technological resources and scientific and technological big data elements is a key constraint factor.
Scientific and technological resources are integrated, scientific and technological achievement data come from internet channels due to the fact that scientific and technological talents are collected, and the data cannot be compared in a standard mode, therefore, the lack of scientific and technological big data elements is built, and a new mode for helping regional economic development cannot be well promoted.
The actual technical requirements of the industry are faced, an information system for collecting the resources is lacked, and systems of all the places are slightly different in different industries. Few systems process, sort, and extract critical information after collecting the demand.
The integration mode is not standard, and most of the scientific and technological resources are acquired in a single project mode. The regional outstanding effective achievement is not integrated by dividing regional scientific and technological resources. The advantages of the areas and colleges are not utilized much.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a method and a system for constructing scientific and technical big data elements, electronic equipment and a storage medium.
In a first aspect, the invention provides a scientific and technological big data element construction method, which includes the following steps:
integrating scientific and technological data sources, and unifying the scientific and technological data to a unified platform to obtain integrated scientific and technological data;
acquiring the integrated scientific and technological data according to different requirements to obtain acquired scientific and technological data;
according to a preset rule, performing text structure storage on the acquired scientific and technological data to obtain stored scientific and technological data;
analyzing the stored scientific and technological data to obtain an analysis result;
and constructing scientific and technical big data elements aiming at the analysis result.
Further, the scientific and technical big data element construction method further comprises the following steps: and performing multimedia display on the scientific and technological big data elements, and providing the scientific and technological big data elements for other application systems.
Further, the scientific and technical data sources at least comprise: all scientific and technical resource websites around the world.
Further, according to different demands, the scientific and technological data after the integration are collected, including at least: according to actual requirements, defining related keywords or related labels, and automatically acquiring related data according to the related keywords or the related labels.
Further, the preset rule includes storing according to at least one of the following keywords or tags, and performing backup storage according to needs: data source, region, field, technology, organization, project set, cooperation set and scientific and technological achievement conversion rate.
Further, the analyzing the acquired scientific and technical data includes: according to actual requirements, determining key data of image science and technology big data elements, and extracting the key data.
Further, the constructing scientific and technical big data elements aiming at the analysis result comprises:
determining a calculation formula of the scientific and technological big data element according to the key data and the weight;
calculating the scientific and technological big data elements corresponding to all the target objects according to the calculation formula of the scientific and technological big data elements;
sequencing the scientific and technological big data elements corresponding to all the target objects;
returning a sorting result;
the calculation formula of the science and technology big data element frequency comprises the following steps:
N＝T×60％+(D×100％+D1×80％+D2×60％+D3×40％)×40％
wherein N represents the occurrence frequency of scientific and technological elements; t is a priority level; d is an item set factor; d1 is a regional and organizational factor; d2 is a domain factor; d3 is the item collection and collaboration collection factor.
In a second aspect, the present invention provides a scientific and technological big data element construction system, including:
the system comprises a data integration module, a data acquisition module, a data storage module, a data analysis module and an element construction module;
the data integration module, the data acquisition module, the data storage module, the data analysis module and the element construction module are sequentially connected;
the data integration module is used for integrating scientific and technological data sources and unifying the scientific and technological data to a unified platform;
the data acquisition module is used for acquiring the integrated scientific and technological data according to different requirements;
the data storage module is used for storing the acquired scientific and technological data according to preset rules;
the data analysis module is used for analyzing the acquired scientific and technological data;
the element construction module is used for constructing scientific and technological big data elements aiming at the analysis result.
In a third aspect, the present invention provides an electronic device, comprising:
one or more processors;
a memory;
the memory stores one or more application programs adapted to be executed by the one or more processors to implement the scientific big data element construction method of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, the computer program being capable of being loaded and executed by a processor, wherein the method for constructing a scientific big data element is described in the first aspect.
The invention achieves the following beneficial effects:
the invention provides a scientific and technological big data element construction method, a scientific and technological big data element construction system, electronic equipment and a storage medium, and has the following beneficial technical effects:
1. the invention solves the problems of complex technological resources and difficult technological big data element sharing in common integration, and provides the construction results of the technological big data elements according to different dimensions for other technological resource service platforms except the platform. The general method is to classify single scientific and technological resources without calculating weight and sequencing, and to perform application display singly according to the characteristics of a platform per se, but the method needs to occupy more multi-party resources, has overhigh maintenance cost and has data acquisition authorization risk. The method provides scientific and technological big data element construction results with different dimensions. The method is beneficial to the application of scientific and technological resources, and the number of cloud servers is saved.
2. By basic screening of regional scientific and technological resources, the problems of scattered data, difficulty in sorting and difficulty in confirmation of scientific research experts are solved.
3. According to the method, the technology big data elements with other dimensions except the region dimension are derived through the construction of the technology big data elements, and the purpose of one-to-three operation is really achieved. By the method, a large amount of non-key scientific and technological data acquisition, reconstruction and maintenance cost is saved.
Drawings
FIG. 1 is a flow chart of a method for constructing scientific and technical big data elements according to an embodiment of the present invention;
FIG. 2 is a flowchart of constructing scientific and technological big data elements according to the analysis result in the embodiment of the present invention;
FIG. 3 is a schematic block diagram of a scientific and technological big data element construction system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a method for constructing scientific and technical big data elements according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the invention.
Reference numerals:
100, an electronic device; 101, a processor; 102, a bus; 103, a memory.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and the contents of the present invention are only a part of the embodiments of the present invention, rather than all the embodiments, and based on the embodiments of the present invention, all other embodiments obtained by a person skilled in the art without creative efforts belong to the protection scope of the present invention.
The invention provides a scientific and technological big data element construction method and system, electronic equipment and a storage medium.
In a first aspect, the present invention provides a scientific and technological big data element construction method, as shown in fig. 1 and fig. 4, including the following steps:
step S1: and integrating scientific and technological data sources, and unifying the scientific and technological data to a unified platform to obtain the integrated scientific and technological data.
Scientific resources are the general term for the human, material, financial, organization, management, information, and other software and hardware elements engaged in scientific activities, or emphasizes the collection of some elements. It provides material guarantee for scientific and technological activities, basic condition guarantee for scientific and technological management, decision making and scientific research, and is an important strategic resource of the country.
The internet scientific and technological resource industry is combined, a proper scientific and technological resource data source is found, collection is carried out, and the source of the scientific and technological resource data is determined through investigation, evidence obtaining and communication and online and offline combination. The sources of data include some specified products, such as: hundred academia, science fund, etc.
Step S2: and acquiring the integrated scientific and technological data according to different requirements to obtain the acquired scientific and technological data.
Collecting the integrated scientific and technological data means that in the specified product of S1, the data are collected by using the product characteristics, the related keywords and the related labels, and the scientific and technological resource data are updated by combining the old data. Through the mode of information management, the function of using form to type in can carry out automatic and artifical two-way data acquisition, obtains the scientific and technological data after gathering.
Step S3: according to a preset rule, performing text structure storage on the acquired scientific and technological data to obtain stored scientific and technological data;
through current storage device, store the scientific and technological data after gathering, use common storage device, separately save characters and image. And carrying out backup processing on the key data. The storage mode is expanded from single hardware storage to cache and disk permanent storage.
The single database is used for storage, necessary text structure storage is added, and element extraction is facilitated.
Step S4: and analyzing the stored scientific and technological data to obtain an analysis result.
According to the processes of cleaning repeated and redundant garbage data, organizing and sorting data models with different dimensions and analyzing industrial data of various regions, the collected scientific and technical data are processed for two or more times, effective data are stored, and the effective data are analysis results so as to better serve other related products.
Step S5: and constructing scientific and technical big data elements aiming at the analysis result.
The big data elements are constructed by applying an integration mode, and the demonstration and the application of platform function key information are provided mainly for building a Guangdong, hong Kong and Macao scientific and technological resource big data service platform, so that the subsequent matching and demonstration are better performed, and the contribution is made for sharing the scientific and technological big data elements.
The scientific and technological big data element construction method further comprises the following steps: and performing multimedia display on the scientific and technological big data elements, and providing the scientific and technological big data elements for other application systems. Finally, unique scientific and technological resource characteristics in each field are formed, the characteristics of scientific and technological talents and regional projects which take colleges and universities and organizations as units are formed, the visual results are also returned to the user for multimedia display, and finally, the sharing of scientific and technological resource elements is provided by combining a data structure and the visual display results.
The scientific and technological resources are the basic part for completing the platform, constitute a user interaction module, integrate scientific and technological data sources and combine an application system for constructing and applying scientific and technological big data elements.
The scientific and technical data sources at least comprise: all scientific and technical resource websites around the world.
According to different demands, the scientific and technological data after the integration are collected, and the method at least comprises the following steps: according to actual requirements, defining related keywords or related labels, and automatically acquiring related data according to the related keywords or the related labels.
Illustratively, selecting tens of millions of scientific and technological resources on line depending on scientists, customizing service and customizing acquisition standards; and (4) collecting the form, continuously optimizing by Dongguan worker of the head-pulling institute, and finally determining.
The preset rule comprises storing according to at least one of the following keywords or tags: data source, region, field, technology, organization, project set, cooperation set, and conversion rate of scientific and technological achievements.
The preset rule also comprises the step of carrying out backup storage on the specified data.
Besides necessary storage data, the migration and supplement of related data are mainly completed by system intellectualization.
The scientific and technological data after to gathering carry out the analysis, include: according to actual requirements, determining key data of image science and technology big data elements, and extracting the key data.
The key data for determining the image science and technology big data elements comprise identification junk data and valid data, and the data junk refers to repeated and invalid data confirmed after manual and algorithm analysis. Effective data comprises contents such as expert portraits, achievement templates, success cases and the like. The machine automatically records and takes the field as the dimension, analyzes according to the frequency of use and the success rate, analyzes the scientific and technological big data elements in different fields, and collects, marks symbols and even stores again aiming at the regional characteristics of Guangdong, hong Kong and Macao. In the process of determining key data of image science and technology big data elements, junk data need to be abandoned, and the big data elements are constructed in effective data.
The constructing of the scientific and technological big data element aiming at the analysis result, as shown in fig. 2, includes:
step S5.1: determining a calculation formula of the scientific and technological big data element according to the key data and the weight;
step S5.2: calculating the scientific and technological big data elements corresponding to all the target objects according to the calculation formula of the scientific and technological big data elements;
step S5.3: sequencing the scientific and technological big data elements corresponding to all the target objects;
step S5.4: and returning the sorting result.
The scientific and technological big data elements comprise scientific research expert elements, technical enterprise big data elements, local government planning big data elements and financial investment theme big data elements.
An embodiment of the method for constructing scientific and technical big data elements, provided by the invention, is as follows:
the method integrates global innovative intelligence resources, rules of automatic learning and data rules and project rules provided by colleges and universities, and performs effective automatic analysis and correction. And the system provides a scientific and technological resource supplement function, and combines the services of an application system, and has extracted result information in different fields and organizations according to the presented scientific and technological big data elements.
Step 1: a Guangdong, hong Kong and Australia scientific and technological resource big data service platform deploys a plurality of WEB servers, acquires cloud sharing expert scientific and technological resource big data relying on an online platform of third-party scientists in an authorization mode, assists the third-party platform to acquire collected scientific and technological resource technical enterprise big data information in a crawler mode, and combines the existing project cases of colleges and universities. Here, the above crawling and cleaning of the scientific resources is performed by professional techniques (i.e., step S1, integrating the scientific data sources, and unifying the scientific data to a unified platform). And the sharing of scientific and technological big data elements is carried out in a website form of a PC (personal computer) end, and the scientific and technological expert big data, the technical enterprise big data, the local government planning big data and the financial investment main body big data are included. Talents, scientific and technological achievements and enterprise requirements of all regions are displayed and applied in a visualization and data sharing mode according to statistical analysis of scientific and technological resource big data elements. And technical and method guidance is provided for other systems for constructing scientific and technical big data and applying the big data. Combining data of regional, peripheral colleges and universities in Guangdong, hong Kong and Macao.
Step 2: and collecting the integrated scientific and technical data according to different requirements.
And step 3: and storing the acquired scientific and technical data in a text structure according to a preset rule.
The data is stored by the existing storage equipment, and the characters and the images are stored separately by applying common storage equipment. And carrying out backup processing on the key data. The storage mode is expanded from single hardware storage to cache and disk permanent storage.
The single database is used for storage, necessary text structure storage is added, and element extraction is facilitated.
The embodiment stores the data according to the region as the dimension, stores the crawled data in the form of texts, and stores the texts in the form of different keywords or labels. For example: data source, region, field, technology, organization, project set, cooperation set, and conversion rate of scientific and technological achievements.
And 4, step 4: and analyzing the acquired scientific and technical data.
And (4) refining the scientific and technological resources T level optimal resources of the scientific and technological big data elements. The T-level preferred resources comprise three preferred resources of T1, T2 and T3, wherein T1 is a preferred resource of regions in Australia, Guangdong and eastern guan university of science and technology; t2 is the preferable resource of technical conversion experts and projects except T1; t3 is the preferred resource for a cooperative college, organization.
Through regional characteristics of Guangdong, hong Kong and Australia, Dongguan rationality, cooperative colleges, enterprises and organizations are optimized and analyzed, and relevant elements of scientific and technical big data are sorted. Meanwhile, the basic elements are corrected, supplemented and finally confirmed mainly by scientific research achievements and experts of Dongguan rationalist in colleges and universities.
And (4) performing element classification on the resources at the T level through the conversion rate D of the scientific and technological achievements of the same type. D1 is the scientific and technological achievement conversion rate related to regional institutions, and is obtained by performing statistics by combining regional arrangement field elements and experts, enterprises and projects. D2 is the scientific and technological achievement conversion rate related to the field, and is obtained by configuring and counting experts, enterprises and project labels according to the field characteristics. D3 is the scientific and technological achievement conversion rate related to project organization, it arranges the scientific and technological resource mode, and mainly colleges and universities, enterprise organizations, carries on the statistics of scientific and technological resource factors.
The extraction of the scientific and technical big data elements uses the weight T as the basic product number of scientific and technical resources, and the data D, D1, D2 and D3 are sequentially cleaned, marked and stored.
Illustratively, the single piece of scientific and technological resource data which is preliminarily collected and sorted is marked, and the used labels comprise: resource data such as type (element type), source (source), address (region), domain (region), technology (technology), org (organization), projects (item set), and Cooperate (collaboration set). S level rights are determined by address filtering, S level is marked, D is determined by projects, D1 is determined by address and org, D2 is determined by domain, and D3 is determined by projects and Cooperate. D is an item set factor; d1 is a regional and organizational factor; d2 is a domain factor; d3 is the item collection and collaboration collection factor.
And 5: and constructing scientific and technical big data elements aiming at the analysis result.
Step 5.1: according to the key data, a calculation formula of the frequency of the scientific and technological big data elements is determined according to the weight, the formula is weighted and summed of the grades and the percentage of the grades, and different grade limits, different percentage limits and different weighted and summed modes are given according to different products.
The calculation was performed with S120, S1 100, S2 80, S3 60, S4 20, and D, D1, D2, and D3, respectively, with 100 as the base. And taking the type as an element type, recording the value N, wherein N represents the occurrence frequency of the scientific and technological elements, and N is a scientific and technological resource item.
N＝T×60％+(D×100％+D1×80％+D2×60％+D3×40％)×40％
To screen the scientific and technical big data elements, the scientific and technical big data elements must be classified and sorted, wherein the sorting is related to the occurrence frequency N and the priority level T of the scientific and technical elements. Each element or the combination of the elements can obtain the ranking value M thereof by the following method, and the greater the ranking value M of the scientific big data element is, the more dominant the scientific big data element is.
Illustratively, taking type and domain as an element set as an example, a ranking value of type and a ranking value of type + domain may be obtained. The sort value of the type is basically determined by the item type and the item; the type + domain ranking value is determined by the project type, project field, and project level. By analogy, more dimensions can be applied.
Step 5.2: and calculating the scientific and technological big data elements corresponding to all the target objects according to the calculation formula of the scientific and technological big data elements.
Preliminary scientific and technological resources are ready before collection, and besides automatic machine analysis, manual correction and intervention functions are also available. Taking the address, org of scientific and technological resources as an example, some information needs to be corrected manually.
Step 5.3: and sequencing the scientific and technological big data elements corresponding to all the target objects.
Step 5.4: and returning the sorting result.
When the type scientific and technological resource integration data is less, the addition of N is processed by using the language characteristic STREAM STREAM mode of the program and the sequencing result is returned, and when the data is excessive, the sequencing is performed by applying classical computer algorithms such as binary tree and bubbling. The characteristics of the machine language used are also used for structured data storage, such as file style. And the sequencing result is the final construction result of the scientific and technical big data elements, and the processing is carried out for multiple times according to the big data elements to form a data structure with meaningful structure, so that the data structure can be applied to subsequent similar matching recommendation functions.
In a second aspect, the present invention provides a scientific and technological big data element construction system, as shown in fig. 3, including:
the system comprises a data integration module, a data acquisition module, a data storage module, a data analysis module and an element construction module;
the data integration module, the data acquisition module, the data storage module, the data analysis module and the element construction module are sequentially connected;
the data integration module is used for integrating scientific and technological data sources and unifying the scientific and technological data to a unified platform;
the data acquisition module is used for acquiring the integrated scientific and technological data according to different requirements;
the data storage module is used for storing the acquired scientific and technological data according to preset rules;
the data analysis module is used for analyzing the acquired scientific and technological data;
the element construction module is used for constructing scientific and technological big data elements aiming at the analysis result.
In a third aspect, the present invention provides an electronic device, as shown in fig. 5, including: a memory and one or more processors.
The memory stores one or more application programs adapted to be executed by the one or more processors to implement the scientific big data element construction method of the first aspect.
As shown in fig. 5, the electronic apparatus 100 includes: a processor 101 and a memory 103. Wherein the processor 101 is coupled to the memory 103, such as via a bus 102.
The structure of the electronic device 100 is not limited to the embodiment of the present invention.
The processor 101 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 101 may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors.
The memory 103 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, the computer program being capable of being loaded and executed by a processor, wherein the method for constructing a scientific big data element is described in the first aspect.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A scientific and technological big data element construction method is characterized by comprising the following steps:
integrating scientific and technological data sources, and unifying the scientific and technological data to a unified platform to obtain integrated scientific and technological data;
acquiring the integrated scientific and technological data according to different requirements to obtain acquired scientific and technological data;
according to a preset rule, performing text structure storage on the acquired scientific and technological data to obtain stored scientific and technological data;
analyzing the stored scientific and technological data to obtain an analysis result;
and constructing scientific and technical big data elements aiming at the analysis result.
2. The method for building scientific and technical big data elements according to claim 1, further comprising: and performing multimedia display on the scientific and technological big data elements, and providing the scientific and technological big data elements for other application systems.
3. The method for building scientific and technical big data elements according to claim 1, wherein the scientific and technical data sources at least comprise: all scientific and technical resource websites around the world.
4. The method for constructing scientific and technological big data elements according to claim 1, wherein the collecting the integrated scientific and technological data according to different requirements at least comprises: according to actual requirements, defining related keywords or related labels, and automatically acquiring related data according to the related keywords or the related labels.
5. The method for building scientific and technical big data elements according to claim 1, wherein the preset rules comprise storing according to at least one of the following keywords or tags, and performing backup storage according to the need: data source, region, field, technology, organization, project set, cooperation set and scientific and technological achievement conversion rate.
6. The method for constructing scientific and technical big data elements according to claim 1, wherein the analyzing the collected scientific and technical data comprises: according to actual requirements, determining key data of image science and technology big data elements, and extracting the key data.
7. The method for constructing scientific and technical big data element according to claim 1, wherein the constructing scientific and technical big data element according to the analysis result comprises:
determining a calculation formula of the scientific and technological big data element according to the key data and the weight;
calculating the scientific and technological big data elements corresponding to all the target objects according to the calculation formula of the scientific and technological big data elements;
sequencing the scientific and technological big data elements corresponding to all the target objects;
returning a sorting result;
the calculation formula of the science and technology big data element frequency comprises the following steps:
N＝T×60％+(D×100％+D1×80％+D2×60％+D3×40％)×40％
wherein N represents the occurrence frequency of scientific and technological elements; t is a priority level; d is an item set factor; d1 is a regional and organizational factor; d2 is a domain factor; d3 is the item collection and collaboration collection factor.
8. A system for implementing the scientific big data element construction method according to any one of claims 1 to 7, comprising:
the system comprises a data integration module, a data acquisition module, a data storage module, a data analysis module and an element construction module;
the data integration module, the data acquisition module, the data storage module, the data analysis module and the element construction module are sequentially connected;
the data integration module is used for integrating scientific and technological data sources and unifying the scientific and technological data to a unified platform;
the data acquisition module is used for acquiring the integrated scientific and technological data according to different requirements;
the data storage module is used for storing the acquired scientific and technological data according to preset rules;
the data analysis module is used for analyzing the acquired scientific and technological data;
the element construction module is used for constructing scientific and technological big data elements aiming at the analysis result.
9. An electronic device, comprising:
one or more processors;
a memory;
the memory stores one or more application programs adapted to be executed by the one or more processors to implement the scientific big data element construction method of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, the computer program being capable of being loaded and executed by a processor to implement the scientific big data element construction method according to claims 1 to 7.
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