CN115130997A - Intelligent human resource data integration and publishing platform for classified storage information - Google Patents
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Abstract
The invention relates to a human resource data platform. The invention relates to an intelligent human resource data integration and release platform for classified storage of information. The system comprises an information recording unit, an analysis and evaluation unit, an information sorting unit, a classified storage unit and an information display unit; the information recording unit is used for recording various information of talents. The invention can collect the academic information, the position information and the achievement of talents in time, comprehensively evaluate the talents according to the information, store the evaluation result and the information in the classified storage unit, and recommend proper talents in proper positions, and an operator can also quickly select the talents according to the evaluation result and the information of the talents, thereby avoiding the phenomenon that the recommended talents do not meet the requirements of the operator when the talents are selected, and greatly improving the efficiency of searching the talents.
Description
Technical Field
The invention relates to a human resource data platform, in particular to an intelligent human resource data integration and publishing platform for classified storage information.
Background
Human resources are human resources, and the most extensive definition refers to human resource management work, including six modules: the human resource planning, recruitment, training, performance, pay, labor relationship and the like are mostly used for personnel departments of companies, when a post is lost or a talent is required to be recruited in a company, the talent market is often required to be recruited, or recruitment information is published on the internet, the method cannot often obtain the talent most suitable for the post, and a common talent recruitment website cannot comprehensively evaluate the talent according to various information of the talent, so that the company cannot search the most suitable talent quickly, cannot predict subsequent changes of the talent, and is not convenient for the talent to select by oneself.
Disclosure of Invention
The invention aims to provide an intelligent human resource data integration and release platform for classified storage information, so as to solve the problems in the background technology.
In order to achieve the purpose, an intelligent human resource data integration and release platform for classified storage of information is provided, and comprises an information recording unit, an analysis and evaluation unit, an information sorting unit, a classified storage unit and an information display unit;
the information recording unit is used for recording various information of talents and transmitting the recorded information to the analysis and evaluation unit, the information sorting unit and the classified storage unit;
the analysis and evaluation unit is used for analyzing and evaluating the talent capability according to the information in the information recording unit and the classified storage unit and transmitting the evaluation result to the information sorting unit, the classified storage unit and the information display unit;
the information sorting unit is used for classifying talents according to the information transmitted by the information recording unit and transmitting the classified information to the analysis and evaluation unit and the classified storage unit;
the classified storage unit is used for storing the information in the analysis and evaluation unit and the classified storage unit and transmitting the information stored before to the information sorting unit;
the information display unit is used for displaying the evaluation result and the basic information of the talents according to the information in the analysis and evaluation unit.
As a further improvement of the technical scheme, the information recording unit comprises a study collection module, a position collection module and an achievement collection module;
the academic record collection module is used for collecting the academic record information of talents and transmitting the information to the analysis evaluation unit, the information sorting unit and the classified storage unit;
the position collecting module is used for collecting position change information of talents and transmitting the information to the analysis and evaluation unit, the information sorting unit and the classified storage unit;
the achievement collecting module is used for collecting contribution information made by talents in each position and transmitting the information to the analysis and evaluation unit and the classification and storage unit.
As a further improvement of the technical scheme, the analysis and evaluation unit comprises a academic evaluation module, an experience analysis module, a capability analysis module and a comprehensive evaluation module;
the academic record evaluation module is used for receiving the information transmitted by the academic record collection module, evaluating the academic record condition of the talents according to the information of the academic record collection module and transmitting the experience information of the talents to the comprehensive evaluation module;
the experience analysis module is used for receiving the information transmitted by the position collection module and the achievement collection module, analyzing the experience of the talents according to the information of the position collection module and the achievement collection module and transmitting the experience information of the talents to the comprehensive evaluation module;
the ability analysis module is used for receiving the information transmitted by the position collection module and the achievement collection module, analyzing the ability of the talents according to the information of the position collection module and the achievement collection module and transmitting the experience information of the talents to the comprehensive evaluation module;
the comprehensive evaluation module is used for comprehensively evaluating the talents according to the information transmitted by the academic evaluation module, the experience analysis module and the capability analysis module and transmitting the information to the information sorting unit, the classified storage unit and the information display unit, and the comprehensive evaluation module carries out evaluation by using a score evaluation algorithm.
As a further improvement of the technical solution, the information sorting unit includes a professional classification module and a capability classification module;
the professional classification module is used for classifying the professional directions of talents according to the information transmitted by the academic record collection module and the position collection module and transmitting the classification results to the classification storage unit and the information display unit;
the ability classification module is used for classifying the abilities of the talents according to the information transmitted by the comprehensive evaluation module and transmitting the classification results to the classification storage unit and the information display unit, and the ability classification module classifies the talents as technical talents, common talents or management talents, so that the talents can be conveniently and properly recommended according to the missing posts of each company.
As a further improvement of the technical scheme, the classification storage unit comprises a study storage module, a position storage module and an achievement storage module;
the academic calendar storage module is used for receiving the information of the academic calendar collection module and the academic calendar evaluation module, storing the academic calendars of all talents according to the information transmitted by the academic calendar collection module and the academic calendar evaluation module, and transmitting the stored information to the information display unit;
the position storage module is used for receiving the information of the position collection module and the experience analysis module, storing the position change information of all talents according to the information of the position collection module and the experience analysis module and transmitting the stored information to the information display unit;
the achievement storage module is used for receiving the information of the achievement collecting module and the ability analyzing module, and the achievement storage module stores the contribution information made by all talents in positions according to the information of the achievement collecting module and the ability analyzing module and transmits the stored information to the information display unit.
As a further improvement of the technical scheme, the information display unit comprises a position suggestion module, a capability display module and a template display module;
the position suggestion module is used for receiving information of the comprehensive evaluation module, the professional classification module, the ability classification module, the academic record storage module, the position storage module and the achievement storage module and making suggestions on positions suitable for talents;
the ability display module is used for receiving the information of the comprehensive evaluation module and the achievement storage module, and displaying the position change of talents and the contribution of talents in each position according to the information of the comprehensive evaluation module and the achievement storage module;
the template display module is used for searching talent information similar to the current talents in the classified storage unit as a template and displaying the subsequent development conditions of the template, and the template display module predicts the subsequent changes of the talents by adopting a difference algorithm.
As a further improvement of the technical scheme, the score evaluation algorithm comprises the following steps:
establishing a scoring area: [ a ] A n 、b m 、c p 、d l ]
a: the number of times talents contributed in positions;
b: the number of times of talent job promotion when making contributions;
c: the number of times that talents normally promote their positions;
d: the work time of talents in positions;
e: the study calendar of talents.
(E+H+M)*100％＝Q
E: scoring corresponding to the talent scholarly;
h: the talents are promoted to corresponding scores when making contributions;
m: the corresponding score of talents in normal work.
As a further improvement of the technical solution, the difference analysis algorithm is as follows:
m and n are the lengths of the two character strings a and b respectively;
establishing talent job promotion data H, Hi, 0 is 0, and i is more than or equal to 0 and less than or equal to m; h0, j is 0, j is more than or equal to 0 and less than or equal to n
s(a i ，b j ) Similar functions representing characters in the character string generally add points if the characters are the same, and subtract points if the characters are different;
hi, j represents the maximum similarity coefficient of the suffixes of the two strings;
W i is the gap score coefficient;
the algorithm considers that the influence of the mismatching of the beginning and the end of the character string on the similarity of the two character strings is not large, so that the weight lower than the mismatching of the middle character string is given to the mismatching of the prefix and the suffix, whether the different liquid chlorine loading processes are the same or not can be calculated, and the condition which is possibly generated in the later period can be modeled and predicted according to the recorded talent information.
Compared with the prior art, the invention has the beneficial effects that:
1. in this intelligent manpower resources data integration release platform of categorised storage information, can be with the academic or vocational study information of talent, position information is collected with the achievement of making when the job, and carry out the comprehensive consideration article aassessment to the ability of talent according to these information, and will consider that result and information are all stored in the classified storage unit, and recommend suitable talent in suitable post, the operator can also select the talent fast according to each item information of assessment result and talent, the phenomenon that appears recommending the talent and not conform to the operator requirement when avoiding appearing selecting the talent, improve the efficiency of looking for the talent greatly.
2. In the intelligent human resource data integration and release platform for classified storage information, all information of talents is recorded in real time, talents in different fields and different capability levels are classified according to the information, the situation that talents in different fields are recommended when vacant posts appear is avoided, talents with similar information can be searched according to the information of the talents when the talents are recommended, modeling is performed according to the information of the similar talents, the follow-up changes of the current talents, which are possible to appear, are predicted, and the selection of the talents and companies is facilitated.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic view of the structure of an information recording unit according to the present invention;
FIG. 3 is a schematic view of the structure of an analysis and evaluation unit according to the present invention;
FIG. 4 is a schematic structural diagram of an information collating unit according to the present invention;
FIG. 5 is a schematic diagram of a classified storage unit according to the present invention;
fig. 6 is a schematic structural diagram of an information display unit according to the present invention.
The various reference numbers in the figures mean:
1. an information recording unit;
11. a study calendar collection module; 12. a job collection module; 13. an achievement collecting module;
2. an analysis evaluation unit;
21. a calendar evaluation module; 22. an empirical analysis module; 23. a capability analysis module; 24. a comprehensive evaluation module;
3. an information arrangement unit;
31. a professional classification module; 32. a capability classification module;
4. a classified storage unit;
41. a study calendar storage module; 42. a position storage module; 43. an achievement storage module;
5. an information display unit;
51. a job suggestion module; 52. a capability display module; 53. and a template display module.
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations or positional relationships based on those shown in the drawings, merely for convenience of description and simplicity of description, and do not indicate or imply that the device or element so referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention.
Example 1
Referring to fig. 1 to fig. 6, the present embodiment aims to provide an intelligent human resource data integration and publishing platform for storing information in a classified manner, which includes an information recording unit 1, an analysis and evaluation unit 2, an information sorting unit 3, a classified storage unit 4, and an information display unit 5;
the information recording unit 1 is used for recording various information of talents and transmitting the recorded information to the analysis and evaluation unit 2, the information sorting unit 3 and the classified storage unit 4;
the analysis and evaluation unit 2 is used for analyzing and evaluating the ability of talents according to the information in the information recording unit 1 and the classified storage unit 4, and transmitting the evaluation result to the information sorting unit 3, the classified storage unit 4 and the information display unit 5;
the information sorting unit 3 is used for sorting talents according to the information transmitted by the information recording unit 1 and transmitting the sorted information to the analysis and evaluation unit 2 and the sorting and storage unit 4;
the classification storage unit 4 is used for storing the information in the analysis and evaluation unit 2 and the classification storage unit 4 and transmitting the information stored before to the information sorting unit 3;
the information display unit 5 is used for displaying the evaluation result and the basic information of the talents according to the information in the analysis and evaluation unit 2.
In the invention, a academic record collection module 11 firstly collects the academic record information of talents and transmits the academic record information to an academic record evaluation module 21, a professional classification module 31 and an academic record storage module 41, a position collection module 12 collects the position change information of talents and transmits the position information to an experience analysis module 22, an ability analysis module 23, an ability classification module 32, a position storage module 42, an achievement storage module 43 and an ability display module 52, an achievement collection module 13 collects the contribution condition of talents in the position process and transmits the contribution condition to the ability analysis module 23, the achievement storage module 43 and the ability display module 52, the academic record evaluation module 21 evaluates the academic record information transmitted by the academic record collection module 11 and transmits the evaluation result to a comprehensive evaluation module 24, the experience analysis module 22 analyzes the experience of talents according to the position collection module 12 and the achievement collection module 13, judging whether the talent has management experience, transmitting an analysis result to the comprehensive evaluation module 24, analyzing the ability of the talent by the ability analysis module 23, transmitting the analysis result to the comprehensive evaluation module 24, comprehensively evaluating the information evaluated and analyzed by the comprehensive evaluation module 24 according to the academic evaluation module 21, the experience analysis module 22 and the ability analysis module 23, transmitting the evaluation result to the ability classification module 32, the academic storage module 41, the position storage module 42, the achievement storage module 43, the position suggestion module 51 and the ability display module 52, classifying the professional field of the talent by the professional classification module 31, transmitting the classification result to the academic storage module 41 and the position suggestion module 51, grading the ability of the talent by the ability classification module 32, facilitating the recommendation of talents with different ability grades according to companies with different requirements, the ranking result is transmitted to the position suggestion module 51, the academic record storage module 41 stores the academic record information of the talents according to the information of the academic record collection module 11 and the academic record evaluation module 21, so as to call out the information at the later stage when necessary, and transmits the information to the ability display module 52, the position storage module 42 stores the position change information of the talents and transmits the information to the ability display module 52, the achievement storage module 43 stores the contribution condition of the talents in the positions and transmits the information to the ability display module 52, the position suggestion module 51 gives out the talents information suitable for the vacancy of the company according to the information of the comprehensive evaluation module 24, the professional classification module 31, the ability classification module 32, the academic record storage module 41, the position storage module 42 and the achievement storage module 43, and the ability display module 52 according to the academic record collection module 11, The job position collection module 12, the achievement collection module 13, the comprehensive evaluation module 24, the academic record storage module 41, the job position storage module 42 and the achievement storage module 43 provide completed talents information which is convenient to compare with the job position suggestion module 51, meanwhile, the template display module 53 calls out and models previously similar talents information to obtain changes which can occur in the later period of the current talents information, and compared with a common human resource data integration method, the prediction of talents information is more accurate, and suitable talents can be placed at a suitable position according to the information.
The information recording unit 1 includes a study collection module 11, a job position collection module 12 and an achievement collection module 13;
the academic record collection module 11 is used for collecting the academic record information of the talents and transmitting the information to the analysis evaluation unit 2, the information sorting unit 3 and the classified storage unit 4, and after the academic record collection module 11 collects the academic record conditions of the talents, the academic record evaluation module 21 can conveniently screen the talents according to the requirements of each company, so that the phenomenon that the talents cannot meet the requirements is avoided;
the position collecting module 12 is used for collecting position change information of the talents and transmitting the information to the analysis and evaluation unit 2, the information sorting unit 3 and the classified storage unit 4, and the position collecting module 12 records position change information and change reasons of the talents so that the experience analyzing module 22 and the ability analyzing module 23 can analyze the abilities and experience conditions of the talents;
the achievement collecting module 13 is used for collecting contribution information of the talents in each position and transmitting the information to the analysis and evaluation unit 2 and the classification and storage unit 4, and the achievement collecting module 13 collects contribution and error information of the talents in each position, so that the experience analyzing module 22 and the ability analyzing module 23 can analyze abilities and experience conditions of the talents conveniently.
The analysis and evaluation unit 2 comprises a study evaluation module 21, an experience analysis module 22, a capability analysis module 23 and a comprehensive evaluation module 24;
the academic record evaluation module 21 is used for receiving the information transmitted by the academic record collection module 11, the academic record evaluation module 21 evaluates the academic record condition of the talents according to the information of the academic record collection module 11 and transmits the experience information of the talents to the comprehensive evaluation module 24, and the academic record evaluation module 21 evaluates the academic record information of the talents, so that companies with requirements on the academic records can be effectively screened according to the academic record information, and the phenomenon that recommended talents cannot meet the requirements is avoided;
the experience analysis module 22 is used for receiving the information transmitted by the position collection module 12 and the achievement collection module 13, the experience analysis module 22 analyzes the experience of the talents according to the information of the position collection module 12 and the achievement collection module 13 and transmits the experience information of the talents to the comprehensive evaluation module 24, and the experience analysis module 22 analyzes the experience of the talents in positions which the talents have been used and contributions in each position, so that the talents can be recommended to proper companies and posts according to the experience of the talents;
the ability analysis module 23 is used for receiving the information transmitted by the position collection module 12 and the achievement collection module 13, the ability analysis module 23 analyzes the ability of the talents according to the information of the position collection module 12 and the achievement collection module 13, and transmits the experience information of the talents to the comprehensive evaluation module 24, the ability analysis module 23 analyzes the ability of the talents according to the contribution made by the highest position and the highest position that the talents have been used by the talents, and the talents are recommended to proper companies and positions according to the ability of the talents;
the comprehensive evaluation module 24 is used for comprehensively evaluating the talents according to the information transmitted by the academic form evaluation module 21, the experience analysis module 22 and the ability analysis module 23 and transmitting the information to the information sorting unit 3, the classified storage unit 4 and the information display unit 5, the comprehensive evaluation module 24 carries out evaluation by using a score evaluation algorithm, and the comprehensive evaluation module 24 carries out comprehensive evaluation on the academic form, the ability and the experience information of the talents so as to facilitate the template display module 53 to give out visual display information.
The information sorting unit 3 comprises a professional classification module 31 and a capability classification module 32;
the professional classification module 31 is used for classifying the professional directions of talents according to the information transmitted by the academic calendar collection module 11 and the position collection module 12, and transmitting the classification results to the classification storage unit 4 and the information display unit 5, and the professional classification module 31 is convenient for analyzing which field the talents work in, so that the phenomenon that talent information in different fields is recommended is avoided;
the ability classification module 32 is used for classifying the abilities of the talents according to the information transmitted by the comprehensive evaluation module 24 and transmitting the classification results to the classification storage unit 4 and the information display unit 5, and the ability classification module 32 classifies the talents as technical talents, common talents or management talents, so as to facilitate proper talent recommendation according to the missing posts of each company.
The classification storage unit 4 includes a study history storage module 41, a job position storage module 42, and an achievement storage module 43;
the academic record storage module 41 is used for receiving the information of the academic record collection module 11 and the academic record evaluation module 21, the academic record storage module 41 stores the academic records of all talents according to the information transmitted by the academic record collection module 11 and the academic record evaluation module 21, and transmits the stored information to the information display unit 5, and the academic record storage module 41 is convenient for screening according to the academic records when searching for talents, so that the efficiency of searching for talents is greatly improved;
the position storage module 42 is used for receiving the information of the position collection module 12 and the experience analysis module 22, the position storage module 42 stores the position change information of all talents according to the information of the position collection module 12 and the experience analysis module 22, and transmits the stored information to the information display unit 5, and the position storage module 42 is convenient for screening according to the requirement on position experience when searching for talents, so that the efficiency of searching for talents is improved;
the achievement storage module 43 is used for receiving the information of the achievement collecting module 13 and the ability analyzing module 23, the achievement storage module 43 stores the contribution information of all talents in positions according to the information of the achievement collecting module 13 and the ability analyzing module 23, and transmits the stored information to the information display unit 5, and the achievement storage module 43 is convenient for displaying the contributions of all talents in each position directly when searching for the talents, so that the talents can be screened as required.
The information display unit 5 comprises a position suggestion module 51, a capability display module 52 and a template display module 53;
the position suggestion module 51 is used for receiving the information of the comprehensive evaluation module 24, the professional classification module 31, the ability classification module 32, the academic record storage module 41, the position storage module 42 and the achievement storage module 43 and making suggestions for positions suitable for talents, and the position suggestion module 51 makes evaluations for the academic records, the abilities and the experiences of talents according to the comprehensive evaluation module 24 and gives suitable suggestions; the position suggestion module 51 recommends the professional field and the ability level of the talents according to the information of the professional classification module 31 and the ability classification module 32; talent information stored in the classified storage unit 4 is directly transmitted to the job suggestion module 51, so that talents can be selected conveniently;
the ability display module 52 is used for receiving the information of the comprehensive evaluation module 24 and the achievement storage module 43, the ability display module 52 displays the position change and contribution in each position of the talent according to the information of the comprehensive evaluation module 24 and the achievement storage module 43, so that in order to avoid the phenomenon that the talent recommended in the position suggestion module 51 does not meet the position requirement, the ability display module 52 displays the position change and contribution of the talent and directly displays the position change and contribution to an operator, and the operator can conveniently and directly select the talent according to the information;
the template display module 53 is used for searching talents similar to the current talents in the classified storage unit 4 as templates and displaying the subsequent development conditions of the templates, the template display module 53 predicts the subsequent changes of the talents by adopting a difference algorithm, and the template display module 53 establishes a template to form a contrast with the current talents, so that the talents can be conveniently screened.
The steps of the score evaluation algorithm are as follows:
establishing a scoring area: [ a ] A n 、b m 、c p 、d l ]
a: the number of times talents contributed in positions;
b: the number of times of talent job promotion when making contributions;
c: the number of times that talents normally promote their positions;
d: the work time of talents in positions;
e: the study calendar of talents.
(E+H+M)*100％＝Q
E: scoring corresponding to the talent scholarly;
h: the corresponding score of talent promotion when making contributions;
m: scoring corresponding to the talents working normally;
after the scores of the talents in the work are estimated, the comprehensive ability of the talents is judged, and the talents can be conveniently classified, recommended and stored.
The difference analysis algorithm is as follows:
m and n are the lengths of the two character strings a and b respectively;
establishing talent job promotion data H, Hi, 0 is 0, and i is more than or equal to 0 and less than or equal to m; h0, j is 0, j is more than or equal to 0 and less than or equal to n
s(a i ，b j ) The similar functions representing the characters in the character string generally add points if the similar functions are the same, and subtract points if the similar functions are different;
hi, j represents the maximum similarity coefficient of the suffixes of the two strings;
W i is the gap score coefficient;
the algorithm considers that the influence of the mismatching of the beginning and the end of the character string on the similarity of the two character strings is not large, so that the weight lower than the mismatching of the middle character string is given to the mismatching of the prefix and the suffix, whether the different liquid chlorine loading processes are the same or not can be calculated, and the condition which is possibly generated in the later period can be modeled and predicted according to the recorded talent information.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. The utility model provides an intelligent manpower resources data integration issuing platform of categorised storage information which characterized in that: comprises an information recording unit (1), an analysis and evaluation unit (2), an information sorting unit (3), a classified storage unit (4) and an information display unit (5);
the information recording unit (1) is used for recording various information of talents and transmitting the recorded information to the analysis and evaluation unit (2), the information sorting unit (3) and the classified storage unit (4);
the analysis and evaluation unit (2) is used for analyzing and evaluating the ability of talents according to the information in the information recording unit (1) and the classified storage unit (4), and transmitting the evaluation result to the information sorting unit (3), the classified storage unit (4) and the information display unit (5);
the information sorting unit (3) is used for classifying talents according to the information transmitted by the information recording unit (1) and transmitting the classified information to the analysis and evaluation unit (2) and the classified storage unit (4);
the classified storage unit (4) is used for storing the information in the analysis and evaluation unit (2) and the classified storage unit (4) and transmitting the information stored before to the information arrangement unit (3);
the information display unit (5) is used for displaying the evaluation result and the basic information of the talents according to the information in the analysis and evaluation unit (2).
2. The intelligent human resource data integration and publishing platform for classified storage information according to claim 1, wherein: the information recording unit (1) comprises a study collection module (11), a position collection module (12) and an achievement collection module (13);
the academic record collection module (11) is used for collecting the academic record information of talents and transmitting the information to the analysis evaluation unit (2), the information sorting unit (3) and the classified storage unit (4);
the position collecting module (12) is used for collecting position change information of talents and transmitting the information to the analysis and evaluation unit (2), the information sorting unit (3) and the classified storage unit (4);
the achievement collecting module (13) is used for collecting contribution information made by talents in various positions and transmitting the information to the analysis and evaluation unit (2) and the classification and storage unit (4).
3. The intelligent human resource data integration and publishing platform for classified storage information according to claim 2, wherein: the analysis and evaluation unit (2) comprises a academic evaluation module (21), an empirical analysis module (22), a capability analysis module (23) and a comprehensive evaluation module (24);
the academic calendar evaluation module (21) is used for receiving the information transmitted by the academic calendar collection module (11), and the academic calendar evaluation module (21) evaluates the academic calendar condition of the talents according to the information of the academic calendar collection module (11) and transmits the experience information of the talents to the comprehensive evaluation module (24);
the experience analysis module (22) is used for receiving the information transmitted by the position collection module (12) and the achievement collection module (13), and the experience analysis module (22) analyzes the experience of the talents according to the information of the position collection module (12) and the achievement collection module (13) and transmits the experience information of the talents to the comprehensive evaluation module (24);
the ability analysis module (23) is used for receiving the information transmitted by the position collection module (12) and the achievement collection module (13), and the ability analysis module (23) analyzes the ability of the talents according to the information of the position collection module (12) and the achievement collection module (13) and transmits the experience information of the talents to the comprehensive evaluation module (24);
the comprehensive evaluation module (24) is used for comprehensively evaluating the talents according to the information transmitted by the academic evaluation module (21), the experience analysis module (22) and the capability analysis module (23) and transmitting the information to the information sorting unit (3), the classified storage unit (4) and the information display unit (5), and the comprehensive evaluation module (24) carries out evaluation by using a score evaluation algorithm.
4. The intelligent human resource data integration and release platform for classified storage information according to claim 3, characterized in that: the information sorting unit (3) comprises a professional classification module (31) and a capability classification module (32);
the professional classification module (31) is used for classifying the professional directions of talents according to the information transmitted by the academic record collection module (11) and the position collection module (12), and transmitting the classification results to the classification storage unit (4) and the information display unit (5);
the ability classification module (32) is used for classifying the abilities of the talents according to the information transmitted by the comprehensive evaluation module (24) and transmitting the classification results to the classification storage unit (4) and the information display unit (5), and the ability classification module (32) classifies the talents as technical talents, common talents or management talents, so that the proper talents can be recommended according to the missing posts of each company.
5. The intelligent human resource data integration and release platform for classified storage information according to claim 3, characterized in that: the classification storage unit (4) comprises a study calendar storage module (41), a position storage module (42) and an achievement storage module (43);
the academic record storage module (41) is used for receiving information of the academic record collection module (11) and the academic record evaluation module (21), and the academic record storage module (41) stores the academic records of all talents according to the information transmitted by the academic record collection module (11) and the academic record evaluation module (21) and transmits the stored information to the information display unit (5);
the position storage module (42) is used for receiving information of the position collection module (12) and the experience analysis module (22), and the position storage module (42) stores position change information of all talents according to the information of the position collection module (12) and the experience analysis module (22) and transmits the stored information to the information display unit (5);
the achievement storage module (43) is used for receiving the information of the achievement collecting module (13) and the ability analyzing module (23), and the achievement storage module (43) stores contribution information made by all talents in positions according to the information of the achievement collecting module (13) and the ability analyzing module (23) and transmits the stored information to the information display unit (5).
6. The intelligent human resource data integration and publishing platform for classified storage information according to claim 5, wherein: the information display unit (5) comprises a position suggestion module (51), a capability display module (52) and a template display module (53);
the position suggestion module (51) is used for receiving information of the comprehensive evaluation module (24), the professional classification module (31), the ability classification module (32), the academic record storage module (41), the position storage module (42) and the achievement storage module (43) and making suggestions on positions suitable for talents;
the ability display module (52) is used for receiving the information of the comprehensive evaluation module (24) and the achievement storage module (43), and the ability display module (52) displays the position change of talents and the contribution of talents in each position according to the information of the comprehensive evaluation module (24) and the achievement storage module (43);
the template display module (53) is used for searching talent information similar to the current talents in the classified storage unit (4) to serve as a template and displaying the subsequent development conditions of the template, and the template display module (53) adopts a difference algorithm to predict the subsequent changes of the talents.
7. The intelligent human resource data integration and publishing platform for classified storage information according to claim 3, wherein: the score evaluation algorithm has the following steps:
establishing a scoring area: [ a ] A n 、b m 、c p 、d l ]
a: the number of times talents contributed in positions;
b: the number of times of talent promotion while making contributions;
c: the number of times that talents normally promote their positions;
d: the work hours of talents in the job;
e: a talent's calendar;
(E+H+M)*100％＝Q
e: scoring corresponding to the talent scholarly;
h: the talents are promoted to corresponding scores when making contributions;
m: and scoring corresponding to the talents working normally.
8. The intelligent human resource data integration and release platform for classified storage of information according to claim 6, wherein: the difference analysis algorithm is as follows:
m and n are the lengths of the two character strings a and b respectively;
establishing talent development data H, Hi, 0 is 0, and i is more than or equal to 0 and less than or equal to m; h0, j is 0, j is more than or equal to 0 and less than or equal to n
s(a i ，b j ) Similar functions representing characters in the character string generally add points if the characters are the same, and subtract points if the characters are different;
hi, j represents the maximum similarity coefficient of the suffixes of the two strings;
W i is the gap score coefficient;
the algorithm considers that the influence of the mismatching of the beginning and the end of the character string on the similarity of the two character strings is not large, so that the weight lower than the mismatching of the middle character string is given to the mismatching of the prefix and the suffix, whether the different liquid chlorine loading processes are the same or not can be calculated, and the condition which is possibly generated in the later period can be modeled and predicted according to the recorded talent information.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110135808A (en) * | 2019-05-15 | 2019-08-16 | 浙江中普科技咨询有限公司 | A kind of talent service platform Internet-based |
| CN111144781A (en) * | 2019-12-31 | 2020-05-12 | 江苏德尔斐数字科技有限公司 | Intelligent talent evaluation screening method based on cloud data |
| CN114418534A (en) * | 2022-01-14 | 2022-04-29 | 彭苏勉 | Talent evaluation method and system based on big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110135808A (en) * | 2019-05-15 | 2019-08-16 | 浙江中普科技咨询有限公司 | A kind of talent service platform Internet-based |
| CN111144781A (en) * | 2019-12-31 | 2020-05-12 | 江苏德尔斐数字科技有限公司 | Intelligent talent evaluation screening method based on cloud data |
| CN114418534A (en) * | 2022-01-14 | 2022-04-29 | 彭苏勉 | Talent evaluation method and system based on big data |
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