CN115630080A - Guided talent policy welfare calculation method and device - Google Patents
Guided talent policy welfare calculation method and device Download PDFInfo
- Publication number
- CN115630080A CN115630080A CN202211318384.2A CN202211318384A CN115630080A CN 115630080 A CN115630080 A CN 115630080A CN 202211318384 A CN202211318384 A CN 202211318384A CN 115630080 A CN115630080 A CN 115630080A
- Authority
- CN
- China
- Prior art keywords
- policy
- talent
- label information
- interface
- minimum
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2425—Iterative querying; Query formulation based on the results of a preceding query
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2428—Query predicate definition using graphical user interfaces, including menus and forms
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/105—Human resources
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Mathematical Physics (AREA)
- Human Resources & Organizations (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Human Computer Interaction (AREA)
- Economics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application is suitable for the technical field of big data processing, and provides a guided talent policy welfare calculation method and device, wherein the method comprises the following steps: displaying a first interface; receiving first person label information through a first interface; if the minimum declaration condition and the first-person label information in the policy library meet the first policy of the first preset relationship, displaying a second interface; receiving third talent label information through a second interface; and if the first policy does not have the minimum declaration condition and the policy that the third talent label information meets the second preset relationship, generating a matching result, wherein the matching result comprises a matched policy and/or a unmatched policy. The problem that the talent policy matching and searching efficiency is low due to the fact that the difficulty of the user for searching the talent policy is high can be solved through the talent matching and searching method and the system.
Description
Technical Field
The application belongs to the technical field of big data processing, and particularly relates to a guided talent policy welfare calculation method and device.
Background
The introduction of talents is not left in the development of a country, and at present, the introduction of talents by the country is more and more emphasized, and various policies are provided for introducing talents and various enterprises around the country.
However, there are problems that when a user wants to obtain talent policy information of a relevant government, the user can only search through a policy and official network, and the user can only match condition information of the user through the policy information (for example, information of graduates, employment situations, academic levels, honor awards and important items in charge, and the like).
Disclosure of Invention
In view of this, the present application provides a guided talent policy welfare calculation method and apparatus, which can solve the problem that the current user has a high difficulty in searching for a talent policy, and thus the talent policy matching and searching efficiency is low.
A first aspect of an embodiment of the present application provides a guided talent policy welfare calculation method, including:
displaying a first interface, wherein the first interface is used for prompting a user to select at least one item of first-person label information which is in line with the first-person label information from the plurality of pieces of person label information displayed on the first interface;
receiving first person label information through a first interface;
if the minimum declaration condition and the first person label information in the policy library meet the first policy of the first preset relationship, displaying a second interface; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
receiving third talent label information through a second interface;
and if the first policy does not have the minimum declaration condition and the policy that the third talent label information meets a second preset relationship, generating a matching result, wherein the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result comprises a matched policy and/or an unmatched policy.
In another implementation manner of the first aspect, after receiving the first person tag information through the first interface, the method further includes:
if the minimum declaration condition and the first-person label information in the policy library meet a second policy of a third preset relationship, displaying a third interface, wherein the third preset relationship is that the first-person label information completely meets the minimum declaration condition, and the third interface is used for recommending benefits corresponding to the second policy;
accordingly, the matching policy includes a second policy.
In another implementation manner of the first aspect, after receiving the first-person tag information through the first interface, the method further includes:
if the minimum declaration condition and the first-person label information do not exist in the policy library and the third policy that the first-person label information meets the fourth preset relationship exists, a fourth interface is displayed, the fourth preset relationship is that the first-person label information exists in the minimum declaration condition, and the fourth interface is used for displaying the person label information that does not meet the minimum declaration condition of the third policy;
accordingly, the unmatched policies include a third policy.
In another implementation manner of the first aspect, after receiving the third talent label information through the second interface, the method further comprises:
if the first policy has a minimum declaration condition and the third talent label information meets a fourth policy of a fifth preset relationship, displaying a fifth interface, wherein the fifth preset relationship is that the third talent label information completely meets the minimum declaration condition, and the fifth interface is used for recommending benefits corresponding to the fourth policy;
accordingly, the matching policy includes a fourth policy.
In another implementation manner of the first aspect, before displaying the first interface, the method further includes:
acquiring a policy file, wherein the policy file comprises a declaration condition;
extracting talent label information in the declaration conditions;
generating a talent label set of a policy corresponding to the policy file based on talent label information of the policy file, wherein the minimum declaration condition of the policy is determined by the talent label set of the policy;
and constructing a policy library according to the talent label sets of all policies.
In another implementation manner of the first aspect, before displaying the first interface, the method includes:
calculating the importance of talent label information in the policy library, and sequencing the talent label information in the policy library according to the importance of talent label information;
displaying the first interface includes:
displaying talent label information through a first interface according to importance of talent label information in a policy bank, wherein the first talent label information is one or more items in the talent label information displayed in the first interface.
In another implementation manner of the first aspect, the matching result includes a policy of matching, and after generating the matching result, the method further includes:
acquiring a talent label set of the user according to the first talent label information and the third talent label information;
calculating the similarity between the talent label set of the user and the talent label set of each matched policy;
sorting the similarity of the obtained talent label set of the user and the talent label set of each matched policy from high to low;
and determining the policy combination which can be declared by the user as the first N policies in the sequence, wherein N is a natural number which is greater than or equal to 1.
In another implementation of the first aspect, after determining that the user-reportable policy combinations are the top N policies in the ranking, the method further comprises:
and calculating the benefits of the first N policies in the sequence, and recommending the first N policies to the user after the policies are sequenced according to the benefits.
A second aspect of embodiments of the present application provides a guided talent policy welfare computing device, comprising:
the system comprises a first display module, a second display module and a display module, wherein the first display module is used for displaying a first interface, and the first interface is used for prompting a user to select at least one item of first-person label information which is in line with the first-person label information from a plurality of items of talent label information displayed on the first interface;
the first receiving module is used for receiving the first person label information through a first interface;
the second display module is used for displaying a second interface if the minimum declaration condition and the first person label information in the policy library meet a first policy of a first preset relation; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
the second receiving module is used for receiving the label information of the third talent through a second interface;
and the generating module is used for generating a matching result if the first policy does not have the lowest declaration condition and the third talent label information meets the policy of a second preset relationship, wherein the second preset relationship is that the lowest declaration condition has the third talent label information, and the matching result comprises a matched policy and/or an unmatched policy.
A third aspect of embodiments of the present application provides a terminal, comprising a processor configured to execute a computer program stored in a memory to implement the method of the first aspect as described above.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, in which a computer program is stored, which, when executed by a processor, implements the method of the first aspect as described above.
The guided talent policy welfare calculation method is applied to the terminal. Firstly, a terminal displays a first interface, wherein the first interface is used for prompting a user to select at least one item of first-person label information which is in line with the first-person label information from a plurality of pieces of talent label information displayed on the first interface; secondly, the terminal receives first person label information through a first interface; thirdly, after the terminal determines that the minimum declaration condition exists in the policy library and the first policy that the first-person label information meets the first preset relation according to the first-person label information, the terminal displays a second interface; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface; then, the terminal receives the label information of the third talent through a second interface; and finally, the terminal determines that the minimum declaration condition does not exist in the first policy and the third talent label information meets the policy of a second preset relationship according to the received third talent label information, and then generates a matching result, wherein the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result comprises a matched policy and/or an unmatched policy.
By the method, when a user wants to know the relevant talent policies, the user does not need to independently search and screen the talent policies matched with the condition information of the user through a policy and official network, and only needs to select the talent label information meeting the conditions of the user from the talent label information displayed in the terminal interface by the method provided by the application, so that the matching result can be obtained; therefore, the problem that the talent policy matching and searching efficiency is low due to the fact that the difficulty of searching the talent policy by the user is high can be solved.
It is understood that the beneficial effects of the second aspect and the fourth aspect can be referred to the related description of the first aspect, and are not described herein again.
Drawings
FIG. 1 is a flow chart diagram illustrating a guided talent policy welfare calculation method according to an embodiment of the present application;
FIG. 2 is a flow diagram illustrating a guided talent policy welfare calculation method according to another embodiment of the present application;
FIG. 3 is a flow chart illustrating a guided talent policy welfare calculation method according to another embodiment of the present application;
FIG. 4 is a flow chart illustrating a guided talent policy welfare calculation method according to another embodiment of the present application;
FIG. 5 is a flow chart illustrating a guided talent policy benefit calculation method according to another embodiment of the present application;
FIG. 6 is a diagram illustrating a policy representation generated for a policy according to an embodiment of the present application;
FIG. 7 is a flow diagram illustrating a guided talent policy welfare calculation method according to another embodiment of the present application;
FIG. 8 is a flow chart illustrating a guided talent policy benefit calculation method according to another embodiment of the present application;
FIG. 9 is a flow chart illustrating a guided talent policy benefit calculation method according to another embodiment of the present application;
FIG. 10 is a block diagram illustrating an exemplary configuration of a guided talent policy benefit computing device according to an embodiment of the present application;
fig. 11 is a block diagram schematically illustrating a composition of a terminal according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments obtained by a person skilled in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the embodiments of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the application.
Those skilled in the art will appreciate that the drawings are merely schematic representations of exemplary embodiments, which may not be to scale. The blocks or flows in the drawings are not necessarily required to practice the present application and therefore should not be used to limit the scope of the present application.
Referring to fig. 1, which is a schematic flowchart of a guided talent policy benefit calculation method (i.e., a policy recommendation method) provided in an embodiment of the present application, as shown in the figure, the method may include the following steps:
and S11, displaying the first interface.
In the embodiment of the application, the first interface is used for prompting a user to select at least one item of matched first-person label information from the plurality of pieces of talent label information displayed on the first interface. The first-person label information is one or more of the plurality of person label information displayed in the first interface.
In the embodiment of the application, a user only needs to select the talent label information meeting the self condition according to the preset talent label item in the input box of the first interface. The talent label item can guide a user to select talent label information which is in accordance with the condition of the user. As an example, suppose that talent label items displayed by the first interface are sequentially academic hierarchy and honor award items.
After the user selects the academic hierarchy, the first interface pops up talent label information input frames related to the academic hierarchy, such as talent label information input frames of the academic type, the school type, the graduation year and the like, and the user can select talent label information conforming to the conditions of the user according to guidance of the interface.
After the user selects the honor award item, the first interface pops up talent label information input frames related to the honor award item, such as world-level award items, national-level award items, provincial-level award items, market-level award items and other award items approved by the industry, and the user can select talent label information conforming to the self-winning condition according to the guidance of the interface.
In addition, the first interface may also display other talent label items (e.g., employment situation, important project, basic features, talent type, etc.), and after the user selects other talent label items (e.g., important project), talent label information (e.g., scientific research project, important activity project, talent introduction project) related to the important project is popped up for the user to select. The present application is not illustrated herein.
And S12, receiving the first person label information through the first interface.
In the embodiment of the application, after the user selects the talent label information according to the popped talent label information input box, the first interface can receive the first talent label information selected by the user.
As an example, assume that the first person label information selected by the user at the first interface is { graduation school: 985; the study calendar hierarchy: master researchers; graduation year: 6 months in 2021; honor award item: national level prize terms; sex: woman }.
Then, the first person label information received by the first interface is { graduation institution: 985; the study calendar hierarchy: master researchers; graduation year: 6 months in 2021; honor award item: national level prize terms; sex: woman }.
And S13, if the minimum declaration condition and the first person label information in the policy library meet the first policy of the first preset relationship, displaying a second interface.
In the embodiment of the application, the first preset relationship is that second talent label information exists in the minimum declaration condition except for the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface.
As an example, assume that the first-person label information selected by the user in the person label information displayed on the first interface is { graduation institution: 985; the study calendar hierarchy: master students; graduation year: 6 months in 2021; honor award item: national level prize terms; sex: woman }. After the first interface receives the first person tag information selected by the user, a first policy matched with the first person tag information is found in the policy library.
It should be noted that, the first policy in the embodiment of the present application is any one of a plurality of policies that are found from the policy repository and match the first-person tag information.
As an example, assume that the minimum declaration condition of the first policy is: { university of graduation: 985; the study calendar hierarchy: master studies and above; honor award item: provincial prize terms and above; graduation year: 6 months and later in 2020: sex: without limitation; the important project is as follows: scientific research projects or major event projects; age stratification: within 35 years of age; talent types: high-level talent }. It can be seen that the first talent label information and the lowest declaration condition of the first policy satisfy a first preset relationship, that is, the first policy has the lowest declaration condition, and that second talent label information (major item: scientific and technological research item or major event; age classification: within 35 years) exists in the first policy except the first talent label information (i.e., { graduation college: 985; academic hierarchy: major graduate research, graduation year: 2021 year 6 month; honor award: national family award; gender: woman }).
And under the condition that the first-person label information and the minimum declaration condition of the first policy meet the first preset relationship, displaying a second interface to the user, wherein the second interface is used for prompting the user to select at least one third-person label information from the second-person label information displayed on the second interface, and the second-person label information is label information except the first-person label information selected by the user in the minimum declaration condition of the first policy. Of course, in the above example, only one first policy is taken as an example to explain the embodiment of the present application, and in practical applications, the second-person tag information is tag information except for the first-person tag information in all the person tag information of the first policy (i.e., in the minimum declaration condition).
And S14, receiving the third talent label information through the second interface.
By way of example, it is assumed that the second talent label information is talent label information related to a talent label item "major project" (e.g., scientific and technological research item, talent introduction item, major activity item), talent label information related to "employment situation" (e.g., work unit, work year, work form, work identity), talent label information related to "talent type" (e.g., high-level talents, leadership talents, industrial key talents, overseas talents, domain experts, postdoctrine researchers, business managers, various laborers), and talent label information related to "basic feature" (e.g., housing situation, housing status, age hierarchy), and the like.
And the terminal sequentially displays the second talent label information on a second interface according to the importance of each second talent label information for the user to select.
It should be noted that the third talent label information is one or more items of talent label information selected by the user in the second talent label information displayed on the second interface.
And S15, if the first policy does not have the minimum declaration condition and the policy that the third talent label information meets a second preset relationship, generating a matching result, wherein the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result comprises a matched policy and/or an unmatched policy.
In this embodiment of the application, if the user selects, according to the user's own condition, the third talent label information from the second talent label information displayed on the second interface is { age hierarchy: 35-45 }.
And the terminal searches the policy matched with the third talent label information from the first policies obtained by matching in the S13 according to the third talent label information selected by the user on the second interface. And if the first policy does not have a policy that the minimum declaration condition and the third talent label information selected by the user have a second preset relationship, the terminal generates a matching result, wherein the matching result comprises a matched policy and/or a unmatched policy.
Referring to fig. 2, in another embodiment of the present application, the method comprises:
and S21, displaying the first interface.
And S22, receiving the first person label information through the first interface.
S23, if the minimum declaration condition and the first person label information in the policy library meet a second policy of a third preset relationship, displaying a third interface, wherein the third preset relationship is that the first person label information completely meets the minimum declaration condition, and the third interface is used for recommending benefits corresponding to the second policy;
accordingly, the matching policy includes a second policy.
As an example, assume that the first-person tag information received by the terminal through the first interface is { graduation institution: 985; the study calendar hierarchy: master researchers; graduation year: 6 months in 2021; honor award item: national level prizes; sex: woman }. The policy bank has a second policy whose talent label information is { graduation school: 985; the study calendar hierarchy: master researchers; graduation year: 6 months and later in 2020; honor award item: provincial prize terms and above; sex: without limitation, it should be noted that talent label information of the second policy is the minimum declaration condition of the second policy.
After the terminal receives the first person tag information, the terminal can search the person tag information of the second policy which is completely matched with the first person tag information from the policy library, and correspondingly, the terminal can determine the second policy as the policy matched with the user.
Therefore, when the first-person label information and the minimum declaration condition of the second policy (namely, the talent label information of the second policy) in the policy library satisfy a third preset relationship (namely, the first-person label information completely satisfies the minimum declaration condition), the terminal can determine the second policy as the policy completely matching the first-person label information.
Therefore, the matching policy in the matching result in S15 may include the second policy.
After the second policy completely matched with the first person label information is obtained, the terminal can recommend the relevant benefits of the second policy to the user through the third interface, such as housing benefits, cash benefits, rights and interests benefits and the like.
Referring to fig. 3, in another embodiment of the present application, the method includes:
and S31, displaying the first interface.
And S32, receiving the first person label information through the first interface.
S33, if the lowest declaration condition and the third policy that the first-person label information meets a fourth preset relationship do not exist in the policy library, displaying a fourth interface, wherein the fourth preset relationship is that the first-person label information exists in the lowest declaration condition, and the fourth interface is used for displaying the talent label information that does not meet the lowest declaration condition of the third policy;
accordingly, the unmatched policies include a third policy.
As an example, assume that the first-person tag information received by the terminal through the first interface is { graduation school: common one is used; the study calendar hierarchy: master students; graduation year: year 2021, month 6 }.
After the terminal receives the first-person tag information, the terminal does not search the talent tag information of the third policy containing the first-person tag information from the policy library (the talent tag information of the third policy is the minimum declaration condition of the third policy), that is, the first-person tag information and the minimum declaration condition of the third policy satisfy a fourth preset relationship: there is no first-person tag information in the minimum declared condition (e.g., { graduate colleges: general one; academic hierarchy: major studios; graduate years: 2021, 6 months).
At this time, the terminal can determine that the third policy (i.e. all policies in the policy library) is a non-matching policy.
Therefore, the policy that is not matched in the matching result in S15 may include the third policy.
After the unmatched third policy is determined according to the first person label information, the terminal can display the minimum declaration condition which needs to be met by declaring the third policy to the user through the fourth interface.
Referring to fig. 4, in another embodiment of the present application, the method comprises the steps of:
and S41, displaying the first interface.
And S42, receiving the first person label information through the first interface.
S43, if the minimum declaration condition and the first person label information in the policy library meet the first policy of the first preset relationship, displaying a second interface.
And S44, receiving the third talent label information through the second interface.
S45, if the first policy has a minimum declaration condition and the third talent label information meets a fourth policy of a fifth preset relationship, displaying a fifth interface, wherein the fifth preset relationship is that the third talent label information completely meets the minimum declaration condition, and the fifth interface is used for recommending benefits corresponding to the fourth policy;
accordingly, the matching policy includes a fourth policy.
For the description of the embodiment of the present application, reference may be made to the related description in S23, and details are not repeated here.
Referring to fig. 5, before displaying the first interface, the method further includes:
s51, a policy file is obtained, and the policy file comprises declaration conditions.
In the embodiment of the application, policy documents related to talents can be acquired from official networks of various government departments through a web crawler technology, wherein the policy documents comprise policy document numbers, policy items, release time, validity periods, declaration conditions, crowd-oriented conditions, restriction conditions, cash benefits, housing benefits, rights benefits and other structured information.
In the embodiment of the application, the acquired policy file can be subjected to structured processing through a text analysis method, and structured information of the policy file is extracted, wherein the structured information comprises structured information of a policy file number, policy items, release time, a validity period, declaration conditions, crowd-oriented conditions, limitation conditions, cash benefits, housing benefits, rights benefits and the like.
As an example, after performing a structuring process on one policy file of all the obtained policy files, the obtained structured information may be:
(1) The policy file name: policy (trial) for supporting the development of the important industry with further attracting elite talents;
(2) Policy items: house guarantee;
(3) Release time: 2020.10.1;
(4) The validity period is as follows: 2022.12.31;
(5) Facing to the crowd: top talents (class a);
(6) Reporting conditions: excellent talents of enterprise industrial work are emphasized, the excellent talents of provincial level and above are obtained, the excellent talents participate in scientific and technological research projects or talent introduction projects, and the excellent talents have professional technical titles of '8230';
(7) The limiting conditions are as follows: housing welfare and cash welfare cannot be applied at the same time;
(8) Cash welfare: 6 ten thousand yuan per year; the duration of the year: 3 years;
(9) Housing welfare: 220m 2 (ii) a The duration of the year: 3 years;
(10) Benefit and welfare: the highest limit of the house public accumulation fund loan application is widened to two times of the current deadline; the duration of the year: is disposable.
And S52, extracting talent label information in the declaration condition.
In the embodiment of the application, after the acquired policy file is subjected to structural processing through a text analysis method to obtain the declaration conditions, talent label information in the declaration conditions can be extracted.
As an example, the talent label information extracted from the declaration conditions of the policy document obtained in S51 is: the major enterprise industry works, obtains provincial and above awards, participates in scientific and technological research projects or talent introduction projects, and has professional technical titles.
And S53, generating a talent label set of the policy corresponding to the policy file based on the talent label information of the policy file, wherein the minimum declaration condition of the policy is determined by the talent label set of the policy.
As an example, the talent label information of the policy file extracted in S52 is combined to generate a talent label set for the policy corresponding to the policy file: { talent type: key enterprise industrial work; honor award item: provincial and above awards; the important project is as follows: scientific and technological research projects or talent introduction projects; and (4) job title level: professional technical title }.
It should be noted that the talent label set generated for the policy is also the minimum declaration condition of the policy.
And S54, constructing a policy library according to the talent label sets of all policies.
In the embodiment of the application, after the talent label set is generated for the policy corresponding to each obtained policy file, a policy representation is generated for each policy according to the restriction conditions of the policy. Wherein the limiting conditions include: the sharing relationship (for example, the housing welfare and the equity welfare can be simultaneously applied, the cash welfare and the equity welfare can be simultaneously applied), the exclusive relationship (for example, the housing welfare and the cash welfare can not be simultaneously applied) and the precedence relationship (for example, the cash welfare can be applied after the housing welfare is expired).
After a policy profile is generated for each policy corresponding to the obtained policy file, a policy library can be constructed based on the policy profiles of all policies.
For example, referring to fig. 6, a policy profile is generated for the policy corresponding to one of all policy documents.
Referring to fig. 7, in another embodiment of the present application, before displaying the first interface, the method further includes:
and S71, calculating the importance of the talent label information in the policy library, and sequencing the talent label information in the policy library according to the importance of the talent label information.
In the embodiment of the present application, after the policy library is constructed through the steps described in S51 to S54, the connection degree of the talent label information in the policy library (which may be the number of connecting edges of the talent label information in the policy portrait) is counted, and after the importance degree of the talent label information is obtained, the talent label information in the policy library can be sorted according to the importance degree of the talent label information.
As an example, assume that the importance of talent label information related to the talent label item "academic hierarchy" existing in the policy repository is first, the importance of talent label information related to the talent label item "honor award" is second, the importance of talent label information related to the talent label item "major item" is third, and so on. Then, the terminal can sort the talent label information in the policy repository according to the importance of the talent label information.
Accordingly, a first interface is displayed, comprising:
and S72, displaying talent label information through the first interface according to the importance of the talent label information in the policy library, wherein the first talent label information is one or more items in the talent label information displayed in the first interface.
In the embodiment of the application, after the importance of the talent label information in the policy repository is sorted through the step in S71, the terminal can display the talent label information according to the importance of the talent label information in the policy repository through the first interface to guide the user to sequentially select the talent label information meeting the conditions of the user.
As an example, the terminal may sequentially display "academic hierarchy", "honor award", "big item", and so on as the tab items for the user to preferentially select.
Accordingly, as an example, after the user selects "scholarly hierarchy", the first interface pops up talent label information input boxes related to "scholarly hierarchy", such as talent label information input boxes of a scholarly type, a school type, a graduation year and the like, and the user can select talent label information according to the guidance of the interface.
After the user selects the "honor prize" the first interface pops up the talent label information input box related to the "honor prize", such as the world-level prize, the national-level prize, the province-level prize, the market-level prize and other prize approved by the industry, and the user can select the prize conforming to the prize winning condition according to the guidance of the interface.
After the user selects the 'major project', the first interface pops up talent label information input boxes related to the 'major', such as popping up scientific and technological research projects, major activity projects and talent introduction projects, the user can select projects meeting the conditions of the responsibility of the project according to the guidance of the interface, and the like, until the user sequentially selects talent label information meeting the conditions of the user according to the talent label items displayed on the first interface.
Referring to fig. 8, in another embodiment of the present application, the matching result includes a matching policy, and after the generating the matching result, the method further includes:
and S81, obtaining a talent label set of the user according to the first talent label information and the third talent label information.
In the embodiment of the application, the talent label set of the user is obtained according to the first talent label information selected by the user in the talent label information displayed on the first interface and the third talent label information selected by the user in the second talent label information displayed on the second interface.
As an example, assume that the first-person tag information selected by the user in the person tag information displayed on the first interface is: { university of graduation: 985; the study calendar hierarchy: master students; graduation year: 6 months in 2021; honor award item: national level prize terms; sex: woman }; the third talent label information selected by the user from the talent label information displayed on the second interface is: { age stratification: 35 to 45 percent; the important project is as follows: scientific and technological research projects; housing conditions: no house of its own }.
Correspondingly, the talent label set of the user can be obtained according to the first talent label information and the third talent label information selected by the user as follows: { university of graduation: 985; the study calendar hierarchy: master researchers; graduation year: 6 months in 2021; honor award item: national level prizes; sex: a woman; age stratification: 35 to 45 percent; the important project is as follows: scientific and technological research projects; housing conditions: no house of its own }.
Here, it should be noted that after the user selects the first-person tag information from the talent tag information displayed on the first interface, if a policy with the minimum declaration condition of the first-person tag information is matched from the policy library, the first-person tag information is the talent tag set of the user.
S82, calculating the similarity between the talent label set of the user and the talent label set of each matched policy.
As an example, assume that 30 first policies are matched from the policy repository based on the first-person tag information selected by the user, and that 15 more conforming policies are matched from the 30 first policies based on the third-person tag information selected by the user.
When the 15 matched policies are recommended to the user, the similarity between the talent label set of the next user and the talent label set of each matched policy is calculated.
As an example, a cosine similarity algorithm may be employed to calculate the similarity between the user's talent label set and the talent label set of each of the 15 policies that were matched.
And S83, sequencing the similarity of the obtained talent label set of the user and the talent label set of each matched policy from high to low.
As an example, after obtaining the similarity between the talent tag set of the user and each policy of the 15 policies matched, the 15 policies matched are sorted from large to small according to the similarity.
S84, determining the policy combination which can be declared by the user as the first N policies in the sequence, wherein N is a natural number which is greater than or equal to 1.
As an example, after the 15 matched policies are sorted from large to small according to the similarity with the talent label set of the user, the policy in the top 10 is recommended to the user as a policy combination.
Referring to fig. 9, in another embodiment of the present application, the method further comprises the steps of:
and S91, acquiring a talent label set of the user according to the first talent label information and the third talent label information.
And S92, calculating the similarity between the talent label set of the user and the talent label set of each matched policy.
And S93, sequencing the similarity of the acquired talent label set of the user and the talent label set of each matched policy from high to low.
S94, determining the policy combination which can be declared by the user as the first N policies in the sequence.
And S95, calculating the benefits of the first N policies in the sequence, and recommending the first N policies to the user after the policies are sequenced according to the benefits.
By way of example, after determining the top 10 ranked policy combination that the user can claim, the benefit size of each policy in the policy combination (e.g., house benefits, cash benefits, and equity benefits, etc.) is calculated. And (4) sorting the 10 policies in the policy combination again from high to low according to the benefits, and recommending the policies to the user. In this way, it can be further ensured that the policy combination recommended to the user is more suitable for the user's expectation.
Referring to fig. 10, fig. 10 illustrates a guided talent policy welfare computing device (i.e., policy recommendation device) provided in an embodiment of the present application, including:
a first display module 1010, configured to display a first interface, where the first interface is configured to prompt a user to select at least one item of matching first-person label information from multiple pieces of talent label information displayed on the first interface;
a first receiving module 1020, configured to receive first-person tag information through a first interface;
the second display module 1030 is configured to display a second interface if the minimum declaration condition and the first-person tag information in the policy library meet a first policy of a first preset relationship; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
the second receiving module 1040 is configured to receive the third talent label information through the second interface;
the generating module 1050 is configured to generate a matching result if the minimum declaration condition does not exist in the first policy and the third talent label information satisfies a policy of a second preset relationship, where the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result includes a matched policy and/or a non-matched policy.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
the third display module is used for displaying a third interface if the minimum declaration condition and the second policy that the first-person tag information meets a third preset relationship exist in the policy library, wherein the third preset relationship is that the first-person tag information completely meets the minimum declaration condition, and the third interface is used for recommending benefits corresponding to the second policy; accordingly, the matching policy includes a second policy.
In another embodiment of the present application, the policy recommendation apparatus 10 further comprises:
the fourth display module is used for displaying a fourth interface if the lowest declaration condition and the first-person label information do not exist in the policy library and a third policy that the first-person label information meets a fourth preset relationship, wherein the fourth preset relationship is that the first-person label information exists in the lowest declaration condition, and the fourth interface is used for displaying the talent label information that does not meet the lowest declaration condition of the third policy; accordingly, the non-matching policy includes a third policy.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
the fifth display module is used for displaying a fifth interface if the minimum declaration condition exists in the first policy and the third talent label information meets a fourth policy of a fifth preset relationship, wherein the fifth preset relationship is that the third talent label information completely meets the minimum declaration condition, and the fifth interface is used for recommending benefits corresponding to the fourth policy; accordingly, the matching policy includes a fourth policy.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
the policy construction module is used for acquiring a policy file, and the policy file comprises a declaration condition; extracting talent label information in the declaration conditions; generating a talent label set of a policy corresponding to the policy file based on talent label information of the policy file, wherein the minimum declaration condition of the policy is determined by the talent label set of the policy; and constructing a policy library according to the talent label sets of all policies.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
the first calculation module is used for calculating the importance of the talent label information in the policy library and sequencing the talent label information in the policy library according to the importance of the talent label information.
In another embodiment of the present application, the first display module 1010 is further configured to:
and displaying talent label information through the first interface according to the importance of the talent label information in the policy library, wherein the first talent label information is one or more items of talent label information displayed in the first interface.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
the acquisition module is used for acquiring a talent label set of the user according to the first talent label information and the third talent label information;
the second calculation module is used for calculating the similarity between the talent label set of the user and the talent label set of each matched policy;
the sorting module is used for sorting the similarity of the obtained talent label set of the user and the talent label set of each matched policy from high to low;
and the determining module is used for determining the policy combination which can be declared by the user as the first N policies in the sequence, wherein N is a natural number which is greater than or equal to 1.
In another embodiment of the present application, the policy recommending apparatus 10 further includes:
and the recommendation module is used for calculating the benefits of the first N policies in the sequence, and recommending the first N policies to the user after the policies are sequenced according to the benefits.
It should be noted that the implementation process and mutual information interaction between the above-mentioned devices/modules and the guided talent policy welfare calculation method provided in the embodiments of the present application are based on the same concept, and specific functions and technical effects thereof may be specifically referred to in the method embodiments, and are not described herein again.
Referring to fig. 11, fig. 11 is a schematic structural diagram of a terminal provided in an embodiment of the present application, and as shown in the drawing, the terminal 11 includes:
one or more processors 1110, a memory 1120, and computer programs 1130 stored in the memory 1120 and executable on the processors 1110. The processor 1110, when executing the computer program 1130, implements the steps of the various method embodiments described above, such as steps S11 to S15 shown in fig. 1.
Illustratively, the computer program 1130 may be divided into one or more units, which are stored in the memory 1120 and executed by the processor 1110 to implement the one or more units of the present application may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 1130 in the terminal 11. For example, the computer program 1130 may be divided into several modules, as an example:
a first display module 1010, configured to display a first interface, where the first interface is configured to prompt a user to select at least one item of matching first-person label information from multiple pieces of talent label information displayed on the first interface;
a first receiving module 1020, configured to receive first-person tag information through a first interface;
the second display module 1030 is configured to display a second interface if the minimum declaration condition and the first-person tag information in the policy library meet a first policy of a first preset relationship; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
the second receiving module 1040 is configured to receive the third talent label information through the second interface;
the generating module 1050 is configured to generate a matching result if the minimum declaration condition does not exist in the first policy and the third talent label information satisfies a policy of a second preset relationship, where the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result includes a matched policy and/or a non-matched policy.
The terminal includes, but is not limited to, a processor 1110, a memory 1120. Those skilled in the art will appreciate that fig. 11 is only one example of a terminal 11 and does not constitute a limitation of the terminal 11 and may include more or less components than those shown, or combine certain components, or different components, for example, the terminal 11 may also include an input device, an output device, a network access device, a bus, etc.
The Processor 1110 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 1120 may be an internal storage unit of the terminal 11, such as a hard disk or a memory of the terminal 11. The memory 1120 may also be an external storage device of the terminal 11, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal 11. Further, the memory 1120 may also include both an internal storage unit and an external storage device of the terminal 11. The memory 1120 is used for storing the computer programs and other programs and data required by the terminal 11. The memory 1120 may also be used to temporarily store data that has been output or is to be output.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the example guided talent policy benefit calculation method steps described in connection with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In another embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, and the computer program, when executed on a processor, implements any of the guided talent policy welfare calculation methods provided by the embodiments of the present application.
The guided talent policy welfare calculation method provided by the embodiment of the application can be stored in a computer readable storage medium if the guided talent policy welfare calculation method is realized in the form of a software functional unit and is sold or used as an independent product. Based on such understanding, all or part of the processes in the methods of the embodiments described above may be implemented by a computer program, which may be stored in a computer readable storage medium and used by one or more processors to implement the steps of the embodiments of the methods described above.
Also, as a computer program product, when the computer program product runs on a robot, the terminal is enabled to implement the steps of the above-mentioned method embodiments when executed.
Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
It should be noted that the computer-readable storage medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable storage media may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A guided talent policy welfare calculation method, comprising:
displaying a first interface for prompting a user to select at least one item of matched first-person label information from a plurality of pieces of talent label information displayed on the first interface;
receiving the first person tag information through the first interface;
if the minimum declaration condition and the first person label information in the policy library meet a first policy of a first preset relation, displaying a second interface; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
receiving the third talent label information through the second interface;
if the first policy does not have the minimum declaration condition and the third talent label information meets the policy of a second preset relationship, generating a matching result, wherein the second preset relationship is that the minimum declaration condition has the third talent label information, and the matching result comprises a matched policy and/or a non-matched policy.
2. The method of claim 1, wherein after the receiving the first-person tag information via the first interface, the method further comprises:
if a minimum declaration condition and a second policy that the first-person label information meets a third preset relationship exist in the policy library, displaying a third interface, wherein the third preset relationship is that the first-person label information meets the minimum declaration condition, and the third interface is used for recommending benefits corresponding to the second policy;
accordingly, the matching policy includes the second policy.
3. The method of claim 1, wherein after the receiving the first person tag information via the first interface, the method further comprises:
if the minimum declaration condition does not exist in the policy library and the first-person label information does not meet a third policy of a fourth preset relationship, displaying a fourth interface, wherein the fourth preset relationship is that the first-person label information exists in the minimum declaration condition, and the fourth interface is used for displaying the talent label information which does not meet the minimum declaration condition of the third policy;
accordingly, the unmatched policies include the third policy.
4. The method of claim 1, wherein after said receiving the third talent tag information through the second interface, the method further comprises:
if a minimum declaration condition and a fourth policy that the third talent label information meets a fifth preset relationship exist in the first policy, displaying a fifth interface, wherein the fifth preset relationship is that the third talent label information meets the minimum declaration condition, and the fifth interface is used for recommending a benefit corresponding to the fourth policy;
accordingly, the matching policy includes the fourth policy.
5. The method of claim 1, wherein prior to said displaying the first interface, the method further comprises:
acquiring a policy file, wherein the policy file comprises a declaration condition;
extracting talent label information in the declaration condition;
generating a talent label set of a policy corresponding to the policy file based on talent label information of the policy file, wherein the minimum declaration condition of the policy is determined by the talent label set of the policy;
and constructing the policy library according to the talent label sets of all the policies.
6. The method of claim 5, wherein prior to displaying the first interface, comprising:
calculating the importance of talent label information in the policy library, and sequencing the talent label information in the policy library according to the importance of the talent label information;
the displaying a first interface includes:
displaying the talent label information through the first interface according to the importance of the talent label information in the policy base, wherein the first talent label information is one or more items of talent label information displayed in the first interface.
7. The method of claim 1, wherein the match result includes a matching policy, the method further comprising, after generating the match result:
acquiring a talent label set of the user according to the first talent label information and the third talent label information;
calculating a similarity of the user's talent label set to each of the matched policy's talent label sets;
sorting the obtained similarity of the talent label set of the user and the talent label set of each matched policy from high to low;
and determining the policy combination which can be declared by the user as the first N policies in the sequence, wherein N is a natural number which is greater than or equal to 1.
8. The method of claim 7, wherein after the determining that the combination of user-reportable policies is the top N policies in the ranking, the method further comprises:
and calculating the benefits of the first N policies in the sequence, and recommending the first N policies to the user after the policies are ranked according to the benefits.
9. A guided talent policy welfare computing device, comprising:
the system comprises a first display module, a second display module and a third display module, wherein the first display module is used for displaying a first interface, and the first interface is used for prompting a user to select at least one item of matched first-person label information from a plurality of pieces of personnel label information displayed on the first interface;
a first receiving module, configured to receive the first person tag information through the first interface;
the second display module is used for displaying a second interface if the minimum declaration condition and the first person label information in the policy library meet a first policy of a first preset relation; the first preset relationship is that second talent label information exists in the minimum declaration condition except the first talent label information, and the second interface is used for prompting a user to select at least one item of third talent label information from the second talent label information displayed on the second interface;
the second receiving module is used for receiving the third talent label information through the second interface;
a generating module, configured to generate a matching result if a minimum declaration condition does not exist in the first policy and the third talent label information satisfies a policy of a second preset relationship, where the second preset relationship is that the third talent label information exists in the minimum declaration condition, and the matching result includes a matched policy and/or an unmatched policy.
10. A terminal, characterized in that it comprises a processor for running a computer program stored in a memory for implementing the method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211318384.2A CN115630080B (en) | 2022-10-26 | 2022-10-26 | Guided talent policy welfare calculation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211318384.2A CN115630080B (en) | 2022-10-26 | 2022-10-26 | Guided talent policy welfare calculation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115630080A true CN115630080A (en) | 2023-01-20 |
| CN115630080B CN115630080B (en) | 2023-08-04 |
Family
ID=84906181
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211318384.2A Active CN115630080B (en) | 2022-10-26 | 2022-10-26 | Guided talent policy welfare calculation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115630080B (en) |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398916A (en) * | 2007-09-29 | 2009-04-01 | 上海市高新技术成果转化服务中心 | Method for constructing intelligent policy expert system |
| US20130275193A1 (en) * | 2011-10-05 | 2013-10-17 | John H. Chuang | System and method for managing a talent platform |
| US20160132602A1 (en) * | 2014-11-06 | 2016-05-12 | Kumaresh Pattabiraman | Guided search |
| CN106021553A (en) * | 2016-05-30 | 2016-10-12 | 深圳市华傲数据技术有限公司 | Structuralized data matching method and system |
| CN106484851A (en) * | 2016-09-30 | 2017-03-08 | 深圳市华傲数据技术有限公司 | Information searching system based on talents selection information platform and method |
| KR20180072594A (en) * | 2018-02-12 | 2018-06-29 | 스토리앤브라더스(주) | User equipment and computer program stored in computer readable medium for matching talented person with project |
| KR20190052980A (en) * | 2017-11-09 | 2019-05-17 | 김태령 | Device and method of processing recruitment information |
| CN110457696A (en) * | 2019-07-31 | 2019-11-15 | 福州数据技术研究院有限公司 | A kind of talent towards file data and policy intelligent Matching system and method |
| CN110516072A (en) * | 2019-08-30 | 2019-11-29 | 广州开发区信息工程有限公司 | Policy data processing method, device, computer equipment and storage medium |
| CN110532451A (en) * | 2019-06-26 | 2019-12-03 | 平安科技（深圳）有限公司 | Search method and device for policy text, storage medium, electronic device |
| CN111061679A (en) * | 2019-12-16 | 2020-04-24 | 上海市研发公共服务平台管理中心 | Method and system for rapid configuration of technological innovation policy based on rete and drools rules |
| CN111930966A (en) * | 2020-10-07 | 2020-11-13 | 杭州实在智能科技有限公司 | Intelligent policy matching method and system for digital government affairs |
| CN112380318A (en) * | 2020-11-12 | 2021-02-19 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise policy matching method based on label similarity |
| CN112819286A (en) * | 2021-01-07 | 2021-05-18 | 连云港中教常青科技发展有限公司 | Classified matching system and method for high embedding degree of elite talents and posts |
| CN113297350A (en) * | 2021-05-20 | 2021-08-24 | 浙江微雨科技有限公司 | Intelligent matching retrieval system and method for policies |
| CN113870083A (en) * | 2021-09-27 | 2021-12-31 | 中关村意谷(北京)科技服务有限公司 | Method, apparatus, system, electronic device, and readable storage medium for policy matching |
| WO2022016561A1 (en) * | 2020-07-22 | 2022-01-27 | 江苏宏创信息科技有限公司 | Ai modeling system and method for policy profiling based on big data |
-
2022
- 2022-10-26 CN CN202211318384.2A patent/CN115630080B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101398916A (en) * | 2007-09-29 | 2009-04-01 | 上海市高新技术成果转化服务中心 | Method for constructing intelligent policy expert system |
| US20130275193A1 (en) * | 2011-10-05 | 2013-10-17 | John H. Chuang | System and method for managing a talent platform |
| US20160132602A1 (en) * | 2014-11-06 | 2016-05-12 | Kumaresh Pattabiraman | Guided search |
| CN106021553A (en) * | 2016-05-30 | 2016-10-12 | 深圳市华傲数据技术有限公司 | Structuralized data matching method and system |
| CN106484851A (en) * | 2016-09-30 | 2017-03-08 | 深圳市华傲数据技术有限公司 | Information searching system based on talents selection information platform and method |
| KR20190052980A (en) * | 2017-11-09 | 2019-05-17 | 김태령 | Device and method of processing recruitment information |
| KR20180072594A (en) * | 2018-02-12 | 2018-06-29 | 스토리앤브라더스(주) | User equipment and computer program stored in computer readable medium for matching talented person with project |
| CN110532451A (en) * | 2019-06-26 | 2019-12-03 | 平安科技（深圳）有限公司 | Search method and device for policy text, storage medium, electronic device |
| CN110457696A (en) * | 2019-07-31 | 2019-11-15 | 福州数据技术研究院有限公司 | A kind of talent towards file data and policy intelligent Matching system and method |
| CN110516072A (en) * | 2019-08-30 | 2019-11-29 | 广州开发区信息工程有限公司 | Policy data processing method, device, computer equipment and storage medium |
| CN111061679A (en) * | 2019-12-16 | 2020-04-24 | 上海市研发公共服务平台管理中心 | Method and system for rapid configuration of technological innovation policy based on rete and drools rules |
| WO2022016561A1 (en) * | 2020-07-22 | 2022-01-27 | 江苏宏创信息科技有限公司 | Ai modeling system and method for policy profiling based on big data |
| CN111930966A (en) * | 2020-10-07 | 2020-11-13 | 杭州实在智能科技有限公司 | Intelligent policy matching method and system for digital government affairs |
| CN112380318A (en) * | 2020-11-12 | 2021-02-19 | 中国科学技术大学智慧城市研究院(芜湖) | Enterprise policy matching method based on label similarity |
| CN112819286A (en) * | 2021-01-07 | 2021-05-18 | 连云港中教常青科技发展有限公司 | Classified matching system and method for high embedding degree of elite talents and posts |
| CN113297350A (en) * | 2021-05-20 | 2021-08-24 | 浙江微雨科技有限公司 | Intelligent matching retrieval system and method for policies |
| CN113870083A (en) * | 2021-09-27 | 2021-12-31 | 中关村意谷(北京)科技服务有限公司 | Method, apparatus, system, electronic device, and readable storage medium for policy matching |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115630080B (en) | 2023-08-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Cook et al. | When to consult precision-recall curves | |
| Saleh et al. | Big data analytics and financial reporting quality: qualitative evidence from Canada | |
| Kalathian et al. | Some topological indices in fuzzy graphs | |
| US20210117417A1 (en) | Real-time content analysis and ranking | |
| Athanasopoulos et al. | Bagging in tourism demand modeling and forecasting | |
| Tleuberdinova et al. | Macro-economic factors influencing tourism entrepreneurship: The case of Kazakhstan | |
| Podobnik et al. | Bankruptcy risk model and empirical tests | |
| Ayal | International product life cycle: a reassessment and product policy implications | |
| Goretzko | Factor retention in exploratory factor analysis with missing data | |
| CN112750029A (en) | Credit risk prediction method, device, electronic equipment and storage medium | |
| Qatawneh | The influence of data mining on accounting information system performance: a mediating role of information technology infrastructure | |
| König et al. | Party ideology and legislative agendas: Estimating contextual policy positions for the study of EU decision-making | |
| Beyers | The Great Recession and state unemployment trends | |
| Yang et al. | Deep learning and complex network theory based analysis on socialized manufacturing resources utilisations and an application case study | |
| Shon et al. | Proposal reviewer recommendation system based on big data for a national research management institute | |
| CN114493853A (en) | Credit rating evaluation method, device, electronic device and storage medium | |
| Corbet et al. | Investigating the academic response to cryptocurrencies: Insights from research diversification as separated by journal ranking | |
| La Cava et al. | Visually wired NFTs: Exploring the role of inspiration in non-fungible tokens | |
| John et al. | Exploring the Predictive Analytics Frontier in Business: A Bibliometric Journey | |
| Owda et al. | Financial discussion boards irregularities detection system (fdbs-ids) using information extraction | |
| Mukthar et al. | Research dynamics in AI and fintech: a bibliometric investigation using R | |
| Fan et al. | An improved quantum clustering algorithm with weighted distance based on PSO and research on the prediction of electrical power demand | |
| CN109636627B (en) | Insurance product management method, device, medium and electronic equipment based on block chain | |
| Gordo | “Big data” in the information age | |
| CN115630080A (en) | Guided talent policy welfare calculation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |