Path selection method and device for urban industrial upgrading at the level of labor force skills

Abstract

This application is about a path selection method and device for urban industrial upgrading at the level of labor force skills. The method uses original information data to build a total skill library; then, based on the total skill library and the superior products and upgraded products of urban industrial upgrading, the superior skills and upgrade demand skills of the corresponding city are obtained; then, guided by the needs of urban industrial upgrading, the difference between superior skills and upgrade demand skills is used as the skill difference to determine the scarce skill library corresponding to urban industrial upgrading; then, the degree of correlation between the scarce skill library and superior skills of industrial upgrading is calculated and determined; finally, based on the degree of correlation between the scarce skill library and superior skills of industrial upgrading, the upgrade path of urban industrial upgrading at the level of labor force skills is selected. This application explores the corresponding relationship of "product-occupation-skill" and clarifies the impact of the skill level on product upgrading, thereby selecting the upgrade path of urban industrial upgrading at the level of labor force skills.

Description

Technical Field

[0001] The present application relates to the field of urban labor optimization technology, and in particular to a path selection method and device for urban industrial upgrading at the labor skill level. Background Art

[0002] As one of the most dynamic economic regions in the world, the Pearl River Delta urban agglomeration accounts for more than 80% of Guangdong Province's GDP. The total regional labor force is large, and there is a large amount of population mobility and migration between regions. The industrial development of each region is highly specialized and has a high degree of skill richness. The mobility of labor skills will further promote regional industrial development. Taking the Pearl River Delta urban agglomeration as a case study, we can clarify the superior skill endowments of various regions, explore the regional product upgrading mechanism from the perspective of skills, and clarify the differentiated development paths of various regions, which can provide countermeasures and suggestions for the formulation of product upgrading policies in various regions of the Pearl River Delta.

[0003] Traditional research on product upgrades has mostly focused on the internal aspects of the enterprise itself, and has difficulty in comprehensively measuring the technical content of products. The "technical complexity" theory provides ideas and methods for directly quantifying the degree of technical complexity contained in products. The academic community believes that the essence of product upgrades is the improvement of regional product complexity. However, in related technologies, although there have been studies on product upgrades, they only focus on the supply-side impact of local related knowledge on the local complex knowledge base, and do not consider the market-based impact mechanism on the regional demand side. Summary of the invention

[0004] In order to overcome the problems existing in the relevant technologies, the present application provides a path selection method and device for urban industrial upgrading at the labor skill level. By exploring the correspondence between "product-occupation-skill" and the impact of the skill level on product upgrading, the upgrade path of urban industrial upgrading at the labor skill level is selected.

[0005] This application provides a path selection method for urban industrial upgrading at the level of labor force skills, including:

[0006] Step S1: obtaining original information data, and using the original information data to construct a total skill library, wherein the original information data includes job description information under various attributes, and the job description information includes corpus information of skills required for the job and corpus information of production products corresponding to the job;

[0007] Step S2: Based on the total skill database, sort out the skill databases of different occupations, and determine the first correspondence between occupations and skills based on the corpus information of the skills required for the positions;

[0008] Step S3: determining a second correspondence between occupations and products using the corpus information of the production products corresponding to the positions;

[0009] Step S4: Based on the first corresponding relationship and the second corresponding relationship, stata operation is performed to jointly construct a third corresponding relationship among products, occupations and skills using occupational factors as a medium;

[0010] Step S5: Identify the probability of each sub-category of skills appearing in high-complexity products and low-complexity products, and further define the complexity of each sub-category of skills;

[0011] Step S6: Based on the calculation of skill correlation and the definition of skill complexity, characterize the sub-category skill correlation network;

[0012] Step S7: Determine the superior skills and upgrading required skills of the corresponding city based on the total skill database and the superior products and upgraded products of the city's industrial upgrading;

[0013] Step S8: guided by the urban industry upgrading needs, the difference between the advantageous skills and the upgrading required skills is used as the skill difference, and a lack of skills library corresponding to the urban industry upgrading is determined;

[0014] Step S9: Calculate and determine the correlation between the lacking skill base and the superior skills of the industrial upgrade;

[0015] Step S10: According to the correlation between the scarce skills base and the advantageous skills of the industrial upgrading, select the upgrading path of the urban industrial upgrading at the labor force skills level.

[0016] The present application also provides an electronic device, comprising:

[0017] processor;

[0018] and a memory storing executable codes thereon, which, when executed by the processor, causes the processor to execute the path selection method for urban industrial upgrading at the labor force skill level as described above.

[0019] The present application also provides a non-temporary machine-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor executes the path selection method for urban industrial upgrading at the labor skill level as described above.

[0020] The technical solution provided by this application may have the following beneficial effects:

[0021] The technical solution of this application provides a method and device for selecting an upgrade path for urban industrial upgrading at the level of labor force skills, by using original information data to build a total skill library; then based on the total skill library and the superior products and upgraded products required for urban industrial upgrading, the superior skills and upgrade required skills of the corresponding city are obtained; then, guided by the needs of urban industrial upgrading, the difference between superior skills and upgrade required skills is used as the skill difference to determine the deficient skill library for the corresponding urban industrial upgrading; then the degree of correlation between the deficient skill library and superior skills of industrial upgrading is calculated and determined; finally, based on the degree of correlation between the deficient skill library and superior skills of industrial upgrading, the upgrade path for urban industrial upgrading at the level of labor force skills is selected. This application explores the corresponding relationship of "product-occupation-skill" and clarifies the impact of the skill level on product upgrading, thereby selecting the upgrade path for urban industrial upgrading at the level of labor force skills.

[0022] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and other objects, features and advantages of the present application will become more apparent through a more detailed description of exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0024] Figure 1 It is a flow chart of a path selection method for urban industrial upgrading at the labor force skill level shown in an embodiment of the present application;

[0025] Figure 2 It is a logic diagram of defining a lack of skills library shown in an embodiment of the present application;

[0026] Figure 3 It is a logical schematic diagram of product upgrade path selection in various regions shown in the embodiment of the present application;

[0027] Figure 4 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0029] The applicant found in the study that the labor skill determination scheme provided in the relevant technology only focuses on the supply-side impact of local related knowledge on the local complex knowledge base, and does not consider the market-oriented impact mechanism on the regional demand side. It should be noted that labor, as the main body of local production and development, is an important source of local accumulation of complex knowledge bases, and is also the leading force in promoting product upgrading. Skills, as a comprehensive reflection of the knowledge and abilities stored by the labor force, are a necessary condition for the labor force to carry out production and manufacturing, and are an important measure for studying regional product upgrading. For this reason, the applicant believes in the study that it is necessary to consider the knowledge spillover effect from the perspective of the "product-occupation-skill" factor, and provide a new perspective for the study of labor skill selection for urban industrial upgrading.

[0030] In response to the above problems, an embodiment of the present application provides a path selection method for urban industrial upgrading at the labor skill level. By exploring the "product-occupation-skill" correlation and the impact of the skill level on product upgrading, the upgrade path for urban industrial upgrading at the labor skill level is selected, and corresponding countermeasures are provided for exploring the local skill base and upgrading demand skills in regional development and policy guidance.

[0031] The technical solution of the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0032] Figure 1 This is a flow chart of a method for selecting a path for urban industrial upgrading at the level of labor force skills shown in an embodiment of the present application. This embodiment of the present application is applicable to the selection of labor force skills for urban industrial upgrading at various city levels.

[0033] See also Figure 1 The present application embodiment provides a path selection method for urban industrial upgrading at the labor force skill level, and the method specifically includes the following steps:

[0034] Step S1: Acquire original information data, and use the original information data to build a total skill library.

[0035] It should be noted that the above-mentioned acquisition of original information data and construction of a total skill database using the original information data includes:

[0036] S11: obtaining the original information data through crawler technology, and extracting the job description information under each attribute through multiple screening;

[0037] S12: performing word segmentation processing on the job description information by using a word segmentation algorithm to obtain a plurality of word segments;

[0038] S13: Screening the multiple segmented words to determine valid words containing skill descriptions;

[0039] S14: Integrate the valid words, normalize the words describing the same skill, and remove duplicates to obtain the total skill library. The complete set of subcategories in the total skill library is classified into medium and large categories according to different attributes of the skills.

[0040] In the embodiment of the present application, the above-mentioned original information data is the job description information under each attribute, and the job description information includes the corpus information of the skills required for the job and the corpus information of the production products corresponding to the job, which can be the "job description" content based on a certain direct recruitment information. It should be noted that the original information data can be crawled by python to obtain the job details under multiple screening attributes in a certain direct recruitment, and used as a micro data source at the "product-occupation-skill" level of the research industry.

[0041] The specific implementation process includes: 1) Filtering categories related to the research industry such as "company industry" and "position type" on the recruitment website, and searching for recruitment information for all occupational categories under it; 2) Setting the search city range to define the "local" and "neighboring" attributes of the research area; 3) The crawling results cover the correspondence between "region-position type-position name-recruitment position-position description".

[0042] In a specific embodiment, the focus is on extracting the "job description" content of each recruitment position, which can be divided into two major sections: "job responsibilities" and "job description": "job description" is selected as the corpus source of the "skills" required for the position; "job responsibilities" is selected as the corpus source of the "production products" corresponding to the position.

[0043] In a specific embodiment, Jieba word segmentation is performed based on the content of the "job description" of a certain direct recruitment information, and then effective words related to the "skill" description can be manually screened. It should be noted that the screening of effective words can be achieved through other automated processes, which are not specifically limited here; then the effective words are translated into English to observe the similarity between the words; synonyms are integrated and normalized into words that describe the same skill, and duplicate removal is performed to obtain a total skill library.

[0044] Step S2: Based on the total skill database, sort out the skill databases of different occupations, and determine the first correspondence between occupations and skills based on the corpus information of the skills required for the positions;

[0045] Step S2 specifically includes the following steps:

[0046] S21: comparing the word segmentation results of the corpus information of the skills required for the positions of different occupations, and screening the skill-related words;

[0047] S22: Match skill words from the total skill database through a vlookup function, and perform deduplication processing to obtain sub-category skills, medium-category skills, and major-category skills corresponding to each occupation;

[0048] S23: Generate an "occupation-mid-category skill" matrix according to the frequency of occurrence of the mid-category skills of each occupation, and determine the correspondence between each occupation and skill that meets the first preset threshold as the first correspondence.

[0049] It should be noted that the skill database of different professions was sorted out to establish the "profession-skill" correspondence: the "jieba word segmentation" results of the "job description" text of different professions were compared, and skill-related vocabulary was manually screened; the vlookup function was used to match skill words from the above-mentioned skill database, and duplicate processing was performed to match the small and medium-class skills corresponding to each profession; the frequency of occurrence of the medium-class skills of each profession was clarified, and an "profession-medium-class skill" matrix was generated, and a threshold value of a% was determined. The total rows and columns in the matrix were each taken with the first a%, and the results were added up to obtain the correspondence between each profession and skill.

[0050] In the embodiment of the present application, skill-related vocabulary is determined by comparing skill word segmentation result tables of different occupations; skill words are matched from the total skill library using a vlookup function, and duplicate removal is performed to obtain valid skill words; setting parameters are determined based on the frequency of occurrence of skills for each occupation, and occupational skills that meet the setting parameters are integrated to obtain skill libraries for different occupations.

[0051] Step S3: determining a second correspondence between occupations and products using the corpus information of the production products corresponding to the positions;

[0052] Step S3 specifically includes the following steps:

[0053] S31: Establishing a product library corresponding to the occupation according to the corpus information of the production products corresponding to the position;

[0054] S32: Screen and extract industry-related products mentioned in the product library;

[0055] S33: Match the product corresponding to the occupation with the export customs code, match the product complexity with the customs code, and determine the correspondence between each occupation and the product as the second correspondence.

[0056] It should be noted that, in a specific embodiment, the "job responsibilities" content is used to establish a "occupation-product" correspondence: a product library corresponding to the occupation is established based on the text description content corresponding to the "job responsibilities" in the "position description" of a direct recruitment information; industry-related products mentioned in the summary text are manually screened and extracted; the products corresponding to the occupation are matched with the export customs code, and the product complexity is further matched with the customs code.

[0057] Step S4: Based on the first corresponding relationship and the second corresponding relationship, stata operation is performed to jointly construct a third corresponding relationship among products, occupations and skills using occupational factors as a medium;

[0058] In a specific embodiment, based on the correspondence between "occupation-skill" and "occupation-product" in the above description, the "occupation" element is used as a medium to construct the "product-occupation-skill" correspondence: Stata is used to merge data sets, establish a relationship between the "occupation-skill" table and the "occupation-product" table, and clarify the "product-skill" association relationship; according to the different attribute classifications of skills, further match them to the "product-medium-category skill" correlation relationship, which is used as the basic data for defining the skill base of each city in the empirical analysis.

[0059] Step S5: Identify the probability of each sub-category of skills appearing in high-complexity products and low-complexity products, and further define the complexity of each sub-category of skills.

[0060] Step S5 specifically includes the following steps:

[0061] S51: Based on the known product complexity value, taking a fourth threshold as a threshold for defining the level of product complexity;

[0062] S52: Mapping the correlation relationship of “product-subcategory skill” based on the third corresponding relationship;

[0063] S53: Calculate the probability of each sub-category of skills appearing in high-complexity products and low-complexity products respectively, and each sub-category of skills corresponds to two probability values;

[0064] S54: Calculate the difference between the high complexity probability and the low complexity probability of each skill. If the difference is positive, the skill is defined as a high complexity skill. If the difference is zero or negative, the skill is defined as a low complexity skill.

[0065] Step S6: Based on the calculation of skill association and the definition of skill complexity, characterize the sub-category skill association network.

[0066] Step S6 specifically includes the following steps:

[0067] S61: According to the skill correlation matrix, organize the "node" table and "edge" table in the Gephi software;

[0068] S62: In the sub-category skill "node" information, the node size indicates the frequency of each sub-category skill appearing in the industry recruitment information, the node color is graded according to the sub-category skills, and the node shape is used to distinguish the different complexity levels of the skills;

[0069] S63: In the “edge” information between sub-category skills, the lines between nodes represent the correlation between skills, and the thickness of the lines indicates the strength of the correlation between skill pairs.

[0070] In the embodiment of the present application, the complexity of the skill is determined based on the frequency of the skill appearing in high-complexity products and low-complexity products. The frequency of the skill appearing in high-complexity products is subtracted from the frequency of the skill appearing in low-complexity products. A positive number indicates a complex skill, and a negative number indicates a non-complex skill.

[0071] In a specific embodiment, the comparative advantages of skills in various occupations and the correlation between skills are calculated: based on the corresponding relationship between each occupation and skill in the above description, each sub-category of skills and their frequency of occurrence are matched; the comparative advantages of each skill in different occupations are quantified based on the frequency; based on the minimum probability of co-occurrence of sub-category advantages in the same occupation, the correlation between two sub-category skills is calculated.

[0072] In an embodiment of the present application, based on the calculation of skill correlation and the definition of skill complexity, a sub-category skill correlation network is depicted: according to the skill correlation matrix, the "node" table and the "edge" table in the Gephi software are organized; in the "node" information of the sub-category skills, the node size indicates the frequency of each sub-category skill appearing in the industry recruitment information, the node color is graded according to the sub-category skills, and the node shape is used to distinguish the different levels of complexity of the skills; in the "edge" information between the sub-category skills, the lines between the nodes represent the correlation between the skills, and the thickness of the line indicates the strength of the correlation between the skill pairs.

[0073] Step S7: Based on the total skill database and the superior products and upgraded products of the city's industrial upgrading, determine the superior skills and upgrading required skills of the corresponding city.

[0074] The method for determining the superior skills specifically comprises the following steps:

[0075] S71: Based on the export volume of customs products, calculate the comparative advantages of industry products in various regions within the urban area, clarify the list of advantageous products in various regions, and establish the corresponding relationship between cities and advantageous products;

[0076] S72: Based on the third correspondence, the product element is used as a medium, and the correspondence between the city and the skill is determined by joint matching;

[0077] S73: Generate a city and skill matrix according to the frequency of occurrence of each type of skill corresponding to each city;

[0078] S74: determining and saving the skills that meet the second preset threshold as advantage skills, generating the advantage skills;

[0079] The method for determining the skills required for upgrading specifically includes the following steps:

[0080] S71 / : Based on the original information data, the corpus information of the production products corresponding to the positions is summarized, and a general database of industry products is established;

[0081] S72 / : Based on the total product database of the industry, products that are not included in the list of superior products of each city and are highly complex are identified as upgraded products, and the list of upgraded products for each region is determined;

[0082] S73 / : Based on the third corresponding relationship, the product elements are used as the medium and joint matching is performed to determine the corresponding relationship between the city and the upgraded product;

[0083] S74 / : Generate a skill matrix of cities and upgrade requirements based on the frequency of each skill in each city;

[0084] S75 / : Determine and save the skills that meet the third preset threshold as upgrade requirement skills, and generate the upgrade requirement skills for each city in the region.

[0085] By matching the "product-skill" data with the merged data sets of "city-advantageous product" and "city-upgraded product", we can obtain the advantageous skills and upgrade required skills of each city. We observe the number of times the skills appear in each city, take the first c horizontally and vertically, and add up the results to obtain the corresponding advantageous skills and upgrade required skills of each city.

[0086] It should be noted that the city's advantageous products are measured and the city's local "advantageous skills" are characterized: based on customs trade data and the export volume of customs products, the comparative advantages of industry products in various regions in the region are calculated, the list of advantageous products in various regions is clarified, and the "city-advantageous product" correspondence is constructed; based on the "product-medium-category skill" correspondence in the above description, the "product" element is used as the medium, and the correlation between cities and skills is obtained through connection and matching; according to the frequency of occurrence of each medium-category skill corresponding to each city, a "city-medium-category advantageous skill" matrix is ​​generated, a threshold value b% is determined, and the total rows and columns in the matrix are taken as the first b%, and the results are added up to obtain the advantageous skills of each city.

[0087] It should be noted that the city upgrade products and the city "upgrade demand skills" are measured: based on the total product database of the industry, products that are not included in the list of advantageous products of each city and have high complexity are determined as upgrade products, and the "city-upgrade product" correspondence is established in various places; based on the "product-medium-category skill" correspondence in the above description, with the "product" element as the medium, the correlation between cities and skills is obtained by connection and matching; according to the frequency of occurrence of each medium-category skill corresponding to each city, a "city-medium-category upgrade demand skill" matrix is ​​generated, and a threshold value b% is determined. The total rows and columns in the matrix are respectively taken as the first b%, and the results are added up to obtain the upgrade demand skills of each city.

[0088] Step S8: guided by the urban industry upgrading needs, the difference between the advantageous skills and the upgrading required skills is used as the skill difference, and a lack of skills library corresponding to the urban industry upgrading is determined;

[0089] It should be noted that the skills required for upgrading and the advantageous skills in various regions within the region need to be compared, and the skill gaps between them will be identified as the regional lack of skill pool, such as Figure 2 shown.

[0090] Step S9: Calculate and determine the correlation between the scarce skills and the advantageous skills for the industrial upgrading.

[0091] Step S10: According to the correlation between the scarce skills and the advantageous skills of the industrial upgrading, select the upgrading path of the urban industrial upgrading at the level of labor force skills.

[0092] In the embodiment of the present application, the path to achieve product upgrade can be determined based on the proximity between the required skills and the local superior skills or the superior skills of the neighboring regions, such as Figure 3 shown.

[0093] Step S10 specifically includes the following steps:

[0094] S101: If the lacking skills appear among the city's advantage skills, then the correlation is the highest, and development should be prioritized by relying on local strength;

[0095] S102: By observing the correlation between other lacking skills and the city's advantageous skills, the fifth threshold is used to define the degree of correlation. If the correlation is high, it also relies on the power of the city and has the conditions for coordinated development;

[0096] S103: Take the sixth threshold to define the degree of correlation between skills, and leave the skills with low correlation with local advantage skills, and observe the skills with high correlation with them in the whole set of skills, as well as the city advantages corresponding to these skills;

[0097] S104: Based on the high correlation frequency between the advantageous skills of neighboring cities and the skills that are in short supply locally, clarify the upgrading path of industrial upgrading in various cities at the level of labor force skills.

[0098] It should be noted that, based on the degree of correlation between the skills required for industrial upgrading and the local advantageous skills or the advantageous skills of neighboring regions, the specific paths for various places to achieve product upgrading can be clarified as follows: if the scarce skills appear among the local advantageous skills, then the correlation is the highest, and development is given priority by relying on local forces; observe the correlation between other scarce skills and local advantageous skills, and take the threshold e% to define the degree of correlation. If the correlation is high, it is possible to rely on local forces and develop in a coordinated manner; take the threshold f% to define the degree of correlation between skills, and observe which cities have advantageous skills for the remaining skills with low correlation with local advantageous skills; and clarify the important neighboring sources for various places to achieve product upgrading based on the high correlation frequency between the advantageous skills of each neighboring city and the local scarce skills.

[0099] The embodiment of the present application provides a path selection method for urban industrial upgrading at the level of labor force skills, which constructs a total skill library by using original information data; then, based on the total skill library and the superior products and upgraded products required for urban industrial upgrading, obtains the superior skills and upgrade demand skills of the corresponding city; then, guided by the needs of urban industrial upgrading, the difference between the superior skills and the upgrade demand skills is used as the skill difference to determine the lack of skills library corresponding to the urban industrial upgrading; then, the degree of correlation between the deficient skills library and the superior skills of industrial upgrading is calculated and determined; finally, based on the degree of correlation between the deficient skills library and the superior skills of industrial upgrading, the upgrade path of urban industrial upgrading at the level of labor force skills is selected. This application explores the corresponding relationship of "product-occupation-skill" and clarifies the impact of the skill level on product upgrading, thereby selecting the upgrade path of urban industrial upgrading at the level of labor force skills, and provides corresponding countermeasures for exploring the local skill library and upgrade demand skills in regional development and policy guidance.

[0100] Figure 4 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application.

[0101] See also Figure 4 , the electronic device 400 includes a memory 410 and a processor 420.

[0102] The processor 420 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0103] The memory 410 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage devices. Among them, ROM can store static data or instructions required by the processor 420 or other modules of the computer. The permanent storage device may be a readable and writable storage device. The permanent storage device may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In some other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 410 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 410 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0104] The memory 410 stores executable codes, and when the executable codes are processed by the processor 420 , the processor 420 can execute part or all of the methods described above.

[0105] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0106] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing the following method steps:

[0107] Step S1: obtaining original information data, and using the original information data to construct a total skill library, wherein the original information data includes job description information under various attributes, and the job description information includes corpus information of skills required for the job and corpus information of production products corresponding to the job;

[0108] Step S2: Based on the total skill database, sort out the skill databases of different occupations, and determine the first correspondence between occupations and skills based on the corpus information of the skills required for the positions;

[0109] Step S3: determining a second correspondence between occupations and products using the corpus information of the production products corresponding to the positions;

[0110] Step S4: Based on the first corresponding relationship and the second corresponding relationship, stata operation is performed to jointly construct a third corresponding relationship among products, occupations and skills using occupational factors as a medium;

[0111] Step S5: Identify the probability of each sub-category of skills appearing in high-complexity products and low-complexity products, and further define the complexity of each sub-category of skills;

[0112] Step S6: Based on the calculation of skill correlation and the definition of skill complexity, characterize the sub-category skill correlation network;

[0113] Step S7: Determine the superior skills and upgrading required skills of the corresponding city based on the total skill database and the superior products and upgraded products of the city's industrial upgrading;

[0114] Step S8: guided by the urban industry upgrading needs, the difference between the advantageous skills and the upgrading required skills is used as the skill difference, and a lack of skills library corresponding to the urban industry upgrading is determined;

[0115] Step S9: Calculate and determine the correlation between the lacking skill base and the superior skills of the industrial upgrade;

[0116] Step S10: According to the correlation between the scarce skills base and the advantageous skills of the industrial upgrading, select the upgrading path of the urban industrial upgrading at the labor force skills level.

[0117] The scheme of the present application has been described in detail above with reference to the accompanying drawings. In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments. Those skilled in the art should also be aware that the actions and modules involved in the description are not necessarily required for the present application. In addition, it can be understood that the steps in the method of the embodiment of the present application can be adjusted in order, merged and deleted according to actual needs, and the modules in the device of the embodiment of the present application can be merged, divided and deleted according to actual needs.

[0118] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0119] Alternatively, the present application can also be implemented as a non-temporary machine-readable storage medium (or computer-readable storage medium, or machine-readable storage medium) on which executable code (or computer program, or computer instruction code) is stored. When the executable code (or computer program, or computer instruction code) is executed by a processor of an electronic device (or electronic device, server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0120] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the application herein may be implemented as electronic hardware, computer software, or a combination of both.

[0121] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system and method according to multiple embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a part of a module, a program segment or a code, and the part of the module, the program segment or the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or the flow chart, and the combination of the square boxes in the block diagram and / or the flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0122] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0123] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0124] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A path selection method for urban industrial upgrading at the level of labor force skills, characterized in that: include: Step S1: obtaining original information data, and using the original information data to construct a total skill library, wherein the original information data includes job description information under various attributes, and the job description information includes corpus information of skills required for the job and corpus information of production products corresponding to the job; Step S2: Based on the total skill database, sort out the skill databases of different occupations, and determine the first correspondence between occupations and skills based on the corpus information of the skills required for the positions; Step S3: determining a second correspondence between occupations and products using the corpus information of the production products corresponding to the positions; Step S4: Based on the first corresponding relationship and the second corresponding relationship, stata operation is performed to jointly construct a third corresponding relationship among products, occupations and skills using occupational factors as a medium; Step S5: Identify the probability of each sub-category of skills appearing in high-complexity products and low-complexity products, and further define the complexity of each sub-category of skills; Step S6: Based on the calculation of skill correlation and the definition of skill complexity, characterize the sub-category skill correlation network; Step S7: Determine the superior skills and upgrading required skills of the corresponding city based on the total skill database and the superior products and upgraded products of the city's industrial upgrading; Step S8: guided by the urban industry upgrading needs, the difference between the advantageous skills and the upgrading required skills is used as the skill difference, and a lack of skills library corresponding to the urban industry upgrading is determined; Step S9: Calculate and determine the correlation between the lacking skill base and the superior skills of the industrial upgrade; Step S10: Selecting an upgrade path for urban industrial upgrading at the labor force skill level based on the correlation between the scarce skill base and the superior skills of the industrial upgrading; Wherein, step S2 specifically includes the following steps: S21: comparing the word segmentation results of the corpus information of the skills required for the positions of different occupations, and screening the skill-related words; S22: Match skill words from the total skill database through a vlookup function, and perform deduplication processing to obtain sub-category skills, medium-category skills, and major-category skills corresponding to each occupation; S23: generating an "occupation-medium-class skill" matrix according to the occurrence frequency of the middle-class skill of each occupation, and determining the correspondence between each occupation and skill that meets the first preset threshold as the first correspondence; Step S3 specifically includes the following steps: S31: Establishing a product library corresponding to the occupation according to the corpus information of the production products corresponding to the position; S32: Screen and extract industry-related products mentioned in the product library; S33: matching the product corresponding to the occupation with the export customs code, matching the product complexity with the customs code, and determining the correspondence between each occupation and the product as the second correspondence; Step S5 specifically includes the following steps: S51: Based on the known product complexity value, taking a fourth threshold as a threshold for defining the level of product complexity; S52: Based on the third corresponding relationship, a correlation relationship of "product-subcategory skill" is mapped out; S53: Calculate the probability of each sub-category of skills appearing in high-complexity products and low-complexity products respectively, and each sub-category of skills corresponds to two probability values; S54: Calculate the difference between the high complexity probability and the low complexity probability of each skill. If the difference is positive, the skill is defined as a high complexity skill. If the difference is zero or negative, the skill is defined as a low complexity skill. The method for determining the superior skill in step S7 specifically comprises the following steps: S71: Based on the export volume of customs products, calculate the comparative advantages of industry products in various regions within the urban area, clarify the list of advantageous products in various regions, and establish the corresponding relationship between cities and advantageous products; S72: Based on the third correspondence, the product element is used as a medium, and the correspondence between the city and the skill is determined by joint matching; S73: Generate a city and skill matrix according to the frequency of occurrence of each type of skill corresponding to each city; S74: determining and saving the skills that meet the second preset threshold as advantage skills, generating the advantage skills; The method for determining the skills required for upgrading described in step S7 specifically includes the following steps: S71 / : Based on the original information data, the corpus information of the production products corresponding to the positions is summarized, and a general database of industry products is established; S72 / : Based on the total product database of the industry, products that are not included in the list of superior products of each city and are highly complex are identified as upgraded products, and the list of upgraded products for each region is determined; S73 / : Based on the third correspondence, the product element is used as a medium and joint matching is performed to determine the correspondence between the city and the skill; S74 / : Generate a skill matrix of cities and upgrade requirements based on the frequency of each skill in each city; S75 / : Determine and save the skills that meet the third preset threshold as upgrade requirement skills, and generate the upgrade requirement skills for each city in the region.

2. The method according to claim 1, characterized in that Step S1 specifically includes the following steps: S11: obtaining the original information data through crawler technology, and extracting the job description information under each attribute through multiple screening; S12: performing word segmentation processing on the job description information by using a word segmentation algorithm to obtain a plurality of word segments; S13: Screening the multiple segmented words to determine valid words containing skill descriptions; S14: Integrate the valid words, normalize the words describing the same skill, and remove duplicates to obtain the total skill library. The complete set of subcategories in the total skill library is classified into medium and large categories according to different attributes of the skills.

3. The method according to claim 1, characterized in that Step S6 specifically includes the following steps: S61: According to the skill correlation matrix, organize the "node" table and "edge" table in the Gephi software; S62: In the "node" information of sub-category skills, the size of the node indicates the frequency of each sub-category skill appearing in the industry recruitment information, the node color is graded according to the sub-category skills, and the node shape is used to distinguish the different complexity levels of the skills; S63: In the "edge" information between sub-category skills, the lines between nodes represent the correlation between skills, and the thickness of the lines indicates the strength of the correlation between skill pairs.

4. The method according to claim 1, characterized in that Step S10 specifically includes the following steps: S101: If the lacking skills appear among the local advantage skills, then the correlation is the highest, and development should be prioritized by relying on local strength; S102: By observing the correlation between other scarce skills and local advantageous skills, the fifth threshold is used to define the degree of correlation. If the correlation is high, it also relies on the power of the city and has the conditions for coordinated development; S103: Take the sixth threshold to define the degree of correlation between skills, and leave the skills with low correlation with local advantage skills, and observe the skills with high correlation with them in the whole set of skills, as well as the city advantages corresponding to these skills; S104: Based on the high correlation frequency between the advantageous skills of neighboring cities and the skills that are in short supply locally, clarify the upgrading path of industrial upgrading in various cities at the level of labor force skills.

5. An electronic device, characterized in that: include: processor; and a memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the path selection method for urban industrial upgrading at the labor force skill level as described in any one of claims 1 to 4.

6. A non-transitory machine-readable storage medium, characterized in that: An executable code is stored thereon, and when the executable code is executed by a processor of an electronic device, the processor executes the path selection method for urban industrial upgrading at the labor force skill level as described in any one of claims 1-4.

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