CN111598479A - Big data-based life planning analysis method, system, terminal and medium - Google Patents
Big data-based life planning analysis method, system, terminal and medium Download PDFInfo
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Abstract
The invention discloses a big data-based life planning analysis method, which comprises the steps of obtaining evaluation tables of staff in various industries and various functions, and obtaining test results of the characters, interests and competence tendencies of the staff from the evaluation tables; analyzing according to the test result to obtain the most suitable character, interest and ability tendency information in each industry and each function; acquiring character, interest and ability tendency information evaluated by a person to be tested; analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee; and obtaining a proposal of career planning development according to the industry and the function which are most suitable for the testee, obtaining a specialty corresponding to the industry and the function, and making a academic planning proposal and a new high-level examination selection proposal for the testee according to the examination reporting requirements of the specialty. The method adopts actual position data as a reference basis, and the given planning suggestion is accurate and accords with the current social development trend.
Description
Technical Field
The invention relates to the technical field of intellectualization, in particular to a big data-based life planning analysis method, a big data-based life planning analysis system, a big data-based life planning analysis terminal and a big data-based life planning analysis medium.
Background
The existing mainstream life planning method is to analyze the character, interest and tendency indexes of each dimension of a user by adopting a character test, interest test and tendency test evaluation scale, but the accuracy of the evaluation scale is influenced by the professional ability of a manager, the evaluation state, cognition degree, evaluation environment and the like of the user, and suggestions given according to evaluation conclusions cannot be combined with the society developing at high speed at the present time, so that the method is disjointed with the actual workplace industry and the careers.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the invention provides a lifetime planning method, a system, a terminal and a medium based on big data, the actual workplace industry and the actual functions are combined to analyze the personal characteristics and the professional suitable for the functions, the academic and professional planning suggestions are carried out according to the personal characteristics, the actual workplace data is taken as the reference, and the provided planning suggestions are accurate and accord with the current social development trend.
In a first aspect, a lifetime planning analysis method based on big data provided in an embodiment of the present invention includes:
acquiring evaluation tables of staff members under each industry and each function, and acquiring test results of the character, interest and competence tendency of the staff members from the evaluation tables;
analyzing according to the test result to obtain the most suitable character, interest and ability tendency information in each industry and each function;
acquiring character, interest and ability tendency information evaluated by a person to be tested;
analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee;
and obtaining a proposal of career planning development according to the industry and the function which are most suitable for the testee, obtaining a specialty corresponding to the industry and the function, and making a academic planning proposal and a new college entrance selection proposal for the testee according to the examination reporting requirement of the specialty.
Optionally, the assessment scale comprises a occupational lattice test table, a hollander occupational interest test table, and a general tendency to ability test table.
Optionally, the specific method for analyzing the most suitable character, interest and competence tendency information in each industry and each function according to the test result comprises: analyzing the result proportion of character, interest and capability tendency in each industry and each function according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion.
Optionally, the specific method for analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee includes: and comparing the character, interest and ability tendency information of the testee with the character, interest and ability tendency of the staff, and obtaining the industry and function suitable for the testee through proportion analysis.
In a second aspect, an embodiment of the present invention provides a big data-based career plan analysis system, including: a first acquisition module, a first analysis module, a second acquisition module, a second analysis module, and a planning suggestion module, wherein,
the first acquisition module is used for acquiring the evaluation tables of staff members in various industries and various functions and acquiring the test results of the characters, interests and competence tendencies of the staff members from the evaluation tables;
the first analysis module is used for analyzing and obtaining the most suitable character, interest and ability tendency information in each industry and each function according to the test result;
the second acquisition module is used for acquiring the character, interest and ability tendency information evaluated by the testee;
the second analysis module is used for analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function which are most suitable for the testee;
the planning suggestion module is used for obtaining suggestions of career planning development according to the industry and the functions which are most suitable for the testee, obtaining specialties corresponding to the industry and the functions, and making academic planning suggestions and new college entrance suggestions for the testee according to the examination reporting requirements of the specialties.
Optionally, the assessment scale comprises a occupational lattice test table, a hollander occupational interest test table, and a general tendency to ability test table.
Optionally, the specific method for analyzing the most suitable character, interest and competence tendency information in each industry and each function by the first analysis module according to the test result comprises the following steps: analyzing the result proportion of character, interest and capability tendency in each industry and each function according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion.
Optionally, the specific method for analyzing the evaluation character, interest and ability tendency information of the testee by the second analysis module to obtain the industry and function most suitable for the testee includes: and comparing the character, interest and ability tendency information of the testee with the character, interest and ability tendency of the staff, and obtaining the industry and function suitable for the testee through proportion analysis.
In a third aspect, an embodiment of the present invention provides an intelligent terminal, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described in the foregoing embodiment.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, in which a computer program is stored, the computer program including program instructions, which, when executed by a processor, cause the processor to execute the method described in the above embodiment.
The invention has the beneficial effects that:
according to the life planning analysis method, the life planning analysis system, the life planning analysis terminal and the life planning analysis medium based on the big data, the personal characteristics and the professions suitable for the industry and the function are analyzed by combining the actual industry and the function according to the evaluation data of a large number of staff persons as reference data, the personal characteristics of the person to be tested and the evaluation data of the staff persons are compared and analyzed, the industry and the function which are most suitable for the person to be tested are obtained, the most suitable professional is obtained, and academic industry, career planning suggestions and new college selection suggestions are carried out on the person to be tested. The actual position data is used as a reference, and the given planning suggestion is accurate and accords with the current social development trend.
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In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 shows a flowchart of a big data-based lifetime planning analysis method according to a first embodiment of the present invention;
fig. 2 shows a block diagram of a big data-based lifetime planning analysis system according to a second embodiment of the present invention;
fig. 3 shows a block diagram of an intelligent terminal according to a third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Fig. 1 shows a flowchart of a big data-based lifetime planning analysis method according to a first embodiment of the present invention, where the method includes:
s101, obtaining evaluation tables of excellent employees in each industry and each function, and obtaining the test results of the characters, interests and competence tendencies of the employees from the evaluation tables.
Specifically, the evaluation scales of employees in each industry and each function are collected, and in this embodiment, the evaluation scales are universally used by the MBTI (professional lattice test), the hollander professional interest test, and the general competence tendency test. In actual operation, other evaluation tables may be included for auxiliary analysis to ensure higher evaluation accuracy or wider dimension.
And S102, analyzing and obtaining the most appropriate character, interest and ability tendency information in each industry and each function according to the test result.
Specifically, the result proportion of character, interest and ability tendency in each industry and each function is analyzed according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion.
S103, acquiring the character, interest and ability tendency information of the testee.
And S104, analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function which are most suitable for the testee.
Specifically, the character, interest and ability tendency information of the testee is compared with the character, interest and ability tendency of the staff, and the industry and function most suitable for the testee are obtained through proportion analysis.
And S105, obtaining a proposal of career planning development according to the industry and the functions which are most suitable for the testee, obtaining the professions corresponding to the industry and the functions, and making a academic planning proposal and a new college entrance selection proposal for the testee according to the examination reporting requirements of the professions.
The above embodiments are described in detail below using specific examples:
the results of 16 characters, 6 interests and 9 tendencies of a large number of employees in 51 industries and 1064 functions are collected by three sets of universal evaluation tables of MBTI (professional character test), Holland professional interest test and general tendency test, and 864 different trait combinations can be formed by the characters, the interests and the tendencies. And classifying the industries and functions of each position person as the labels of the position person, and combining the characteristics of the position persons in the same industry and the same function as the labels of the position person for statistics. The character, interest and ability tendency information of the staff is obtained from the evaluation scale, and the data are analyzed to obtain the proportion of each trait combination in 51 industries and 1064 functions. The method comprises the steps of evaluating a person to be tested through MBTI (professional character testing), Holland professional interest testing and general competence tendency testing, obtaining the character, interest and competence tendency information of the person to be tested through evaluation, comparing the character, interest and competence tendency information of the person to be tested with the character, interest and competence tendency of staff, and finding out the industry and functions which are the highest in proportion to the characteristic combination of the person to be tested through the proportion. And obtaining a proposal of career planning development according to the industry and the function which are most suitable for the testee, and also obtaining a specialty corresponding to the industry and the function, and making a academic planning proposal and a new college entrance selection proposal for the testee according to the examination reporting requirement of the specialty.
According to the life planning analysis method based on the big data, provided by the embodiment of the invention, the personal characteristics and the professions suitable for the industry and the functions are analyzed by taking the evaluation data of a large number of staff persons as a reference basis and combining the actual industry and the functions of the workplace, the personal characteristics of the person to be tested and the evaluation data of the staff are compared and analyzed to obtain the industry and the functions most suitable for the person to be tested, the most suitable professional for the career is obtained, and the academic industry, the career planning suggestion and the new high-level scientific research selection suggestion are carried out on the person to be tested. The analysis method adopts actual position data as a reference basis, and the given planning suggestion is accurate and accords with the current social development trend.
In the first embodiment, a big data-based lifetime planning analysis method is provided, and correspondingly, the present application also provides a big data-based lifetime planning analysis system. Please refer to fig. 2, which is a block diagram illustrating a lifetime planning analysis system based on big data according to a second embodiment of the present invention. Since the apparatus embodiments are substantially similar to the method embodiments, they are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for relevant points. The device embodiments described below are merely illustrative.
Fig. 2 shows a structural block diagram of a big data-based lifetime planning analysis system according to a second embodiment of the present invention, where the structural block diagram includes: the system comprises a first acquisition module 201, a first analysis module 202, a second acquisition module 203, a second analysis module 204 and a planning suggestion module 205, wherein the first acquisition module 201 is used for acquiring evaluation tables of superior staff members in various industries and various functions, and acquiring test results of the characters, interests and competence tendencies of the staff members from the evaluation tables; the first analysis module 202 is used for analyzing and obtaining the most suitable character, interest and ability tendency information in each industry and each function according to the test result; the second obtaining module 203 is used for obtaining the character, interest and ability tendency information evaluated by the person to be tested; the second analysis module 204 is used for analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee; the planning suggestion module 205 is used for obtaining suggestions of career planning development according to industries and functions suitable for the testee, obtaining specialties corresponding to the industries and the functions, and making academic planning suggestions and new college entrance suggestions for the testee according to the examination reporting requirements of the specialties.
In this example, the evaluation tables include occupational tests, hollander occupational interests and general competency tendency.
The specific method for analyzing the most suitable character, interest and ability tendency information in each industry and each function by the first analysis module according to the test result comprises the following steps: analyzing the result proportion of character, interest and capability tendency in each industry and each function according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion. The specific method for analyzing the evaluation character, interest and ability tendency information of the testee by the second analysis module to obtain the industry and function most suitable for the testee comprises the following steps: and comparing the character, interest and ability tendency information of the testee with the character, interest and ability tendency of the staff, and obtaining the industry and function suitable for the testee through proportion analysis.
The above is an example description of a big data-based career plan analysis system according to the second embodiment of the present invention.
According to the life planning and analyzing system based on the big data, provided by the embodiment of the invention, the personal characteristics and the professions suitable for the industry and the functions are analyzed by taking the evaluation data of a large number of staff persons as a reference basis and combining the actual industry and the functions of the workplace, the personal characteristics of the person to be tested and the evaluation data of the staff are compared and analyzed, the industry and the functions most suitable for the person to be tested are obtained, the most suitable professional is obtained, and the academic industry and the career planning suggestions are carried out on the person to be tested. The system adopts actual position data as a reference basis, and the given planning suggestion is accurate and accords with the current social development trend.
Fig. 3 shows a block diagram of an intelligent terminal according to a third embodiment of the present invention, where the intelligent terminal includes a processor 301, an input device 302, an output device 303, and a memory 304, where the processor 301, the input device 302, the output device 303, and the memory 304 are connected to each other, and the memory 304 is used for storing a computer program, where the computer program includes program instructions, and the processor 301 is configured to call the program instructions to execute the method described in the first embodiment.
It should be understood that, in the embodiment of the present invention, the Processor 301 may be a Central Processing Unit (CPU), and the Processor may also be other general processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 302 may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of the fingerprint), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.
The memory 304 may include a read-only memory and a random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store device type information.
In a specific implementation, the processor 301, the input device 302, and the output device 303 described in this embodiment of the present invention may execute the implementation described in the method embodiment provided in this embodiment of the present invention, and may also execute the implementation described in the system embodiment described in this embodiment of the present invention, which is not described herein again.
The invention also provides an embodiment of a computer-readable storage medium, in which a computer program is stored, which computer program comprises program instructions that, when executed by a processor, cause the processor to carry out the method described in the above embodiment.
The computer readable storage medium may be an internal storage unit of the terminal described in the foregoing embodiment, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, 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 provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. 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 invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the terminal and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal and method can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled 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; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. A big data-based life planning analysis method is characterized by comprising the following steps:
acquiring evaluation tables of staff members under each industry and each function, and acquiring test results of the character, interest and competence tendency of the staff members from the evaluation tables;
analyzing according to the test result to obtain the most suitable character, interest and ability tendency information in each industry and each function;
acquiring character, interest and ability tendency information evaluated by a person to be tested;
analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee;
and obtaining a proposal of career planning development according to the industry and the function which are most suitable for the testee, obtaining a specialty corresponding to the industry and the function, and making a academic planning proposal and a new college entrance selection proposal for the testee according to the examination reporting requirement of the specialty.
2. The big-data based life planning analysis method of claim 1, wherein the evaluation tables include a career format test table, a Holland career interest test table, and a general ability tendency test table.
3. The big-data-based life planning analysis method according to claim 1, wherein the specific method for analyzing the most suitable character, interest and competence tendency information in each industry and each function according to the test results comprises: analyzing the result proportion of character, interest and capability tendency in each industry and each function according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion.
4. The big data based life planning analysis method of claim 1, wherein the specific method for analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function most suitable for the testee comprises the following steps: and comparing the character, interest and ability tendency information of the testee with the character, interest and ability tendency of the staff, and obtaining the industry and function suitable for the testee through proportion analysis.
5. A big data based career planning analysis system, comprising: a first acquisition module, a first analysis module, a second acquisition module, a second analysis module, and a planning suggestion module, wherein,
the first acquisition module is used for acquiring the evaluation tables of staff members in various industries and various functions and acquiring the test results of the characters, interests and competence tendencies of the staff members from the evaluation tables;
the first analysis module is used for analyzing and obtaining the most suitable character, interest and ability tendency information in each industry and each function according to the test result;
the second acquisition module is used for acquiring the character, interest and ability tendency information evaluated by the testee;
the second analysis module is used for analyzing the evaluation character, interest and ability tendency information of the testee to obtain the industry and function which are most suitable for the testee;
the planning suggestion module is used for obtaining suggestions of career planning development according to the industry and the functions which are most suitable for the testee, obtaining specialties corresponding to the industry and the functions, and making academic planning suggestions and new college entrance suggestions for the testee according to the examination reporting requirements of the specialties.
6. The big-data based life planning analysis system of claim 5, wherein the assessment tables include a career format test table, a Holland career interest test table, and a general ability propensity test table.
7. The big-data based career planning analysis system of claim 5, wherein the specific method for the first analysis module to analyze the most appropriate character, interest and competence tendency information in each industry and each function according to the test results comprises: analyzing the result proportion of character, interest and capability tendency in each industry and each function according to the test result; and analyzing the most suitable character, interest and ability tendency information in each industry and each function according to the result proportion.
8. The big data based life planning analysis system of claim 5, wherein the second analysis module analyzes the evaluation character, interest and ability tendency information of the testee, and a specific method for obtaining the industry and function most suitable for the testee comprises: and comparing the character, interest and ability tendency information of the testee with the character, interest and ability tendency of the staff, and obtaining the industry and function suitable for the testee through proportion analysis.
9. An intelligent terminal comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, the memory being adapted to store a computer program, the computer program comprising program instructions, characterized in that the processor is configured to invoke the program instructions to perform the method according to any of claims 1-4.
10. A computer-readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method according to any of claims 1-4.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112766647A (en) * | 2020-12-30 | 2021-05-07 | 广东德诚科教有限公司 | Method and device for assessing lifetime planning of junior high school students |
| CN115358605A (en) * | 2022-08-26 | 2022-11-18 | 山东心法科技有限公司 | Multi-mode fusion-based career planning auxiliary method, equipment and medium |
| CN118095646A (en) * | 2024-03-11 | 2024-05-28 | 深圳九间科技有限公司 | Career planning method, device, terminal equipment and storage medium |
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2020
- 2020-05-25 CN CN202010449714.6A patent/CN111598479A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112766647A (en) * | 2020-12-30 | 2021-05-07 | 广东德诚科教有限公司 | Method and device for assessing lifetime planning of junior high school students |
| CN115358605A (en) * | 2022-08-26 | 2022-11-18 | 山东心法科技有限公司 | Multi-mode fusion-based career planning auxiliary method, equipment and medium |
| CN115358605B (en) * | 2022-08-26 | 2023-05-05 | 山东心法科技有限公司 | Professional planning auxiliary method, device and medium based on multi-mode fusion |
| CN118095646A (en) * | 2024-03-11 | 2024-05-28 | 深圳九间科技有限公司 | Career planning method, device, terminal equipment and storage medium |
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