CN112232773A - Software recommendation method and system - Google Patents
Software recommendation method and system Download PDFInfo
- Publication number
- CN112232773A CN112232773A CN202011121523.3A CN202011121523A CN112232773A CN 112232773 A CN112232773 A CN 112232773A CN 202011121523 A CN202011121523 A CN 202011121523A CN 112232773 A CN112232773 A CN 112232773A
- Authority
- CN
- China
- Prior art keywords
- free
- resume
- label
- matching
- text
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000008520 organization Effects 0.000 claims description 16
- 230000007115 recruitment Effects 0.000 claims description 15
- 238000004891 communication Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 10
- 238000011161 development Methods 0.000 claims description 8
- 230000004927 fusion Effects 0.000 claims description 4
- 230000003542 behavioural effect Effects 0.000 claims description 3
- 238000010276 construction Methods 0.000 claims description 3
- 230000008450 motivation Effects 0.000 claims description 3
- 238000002372 labelling Methods 0.000 abstract description 12
- 238000012545 processing Methods 0.000 abstract description 5
- 238000013473 artificial intelligence Methods 0.000 description 25
- 238000010586 diagram Methods 0.000 description 13
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR 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
- G06Q10/1053—Employment or hiring
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Economics (AREA)
- Marketing (AREA)
- Data Mining & Analysis (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a software recommendation method and a system, which comprises a resume free employee, an enterprise HR employment information release, a matching score, an AI talent portrait and a position label database, wherein the output end of the resume free employee is connected with the input end of an upload, the output end of the upload is connected with the input end of an AI resume text analysis, the output end of the AI resume text analysis is connected with the input end of a labeling, the output end of the labeling is respectively connected with the input ends of a free employee user label, a free employee occupation label and a free employee behavior label, the free employee can support the free employee to upload a PDF resume file through the set AI resume text analysis, the system analyzes the resume file into a field and a form text and outputs the text into a text format, the text format is automatically filled in the basic information of a system user, and the text processing is carried out through the set labeling, the parsed text information can be subjected to labeling processing.
Description
Technical Field
The invention relates to the technical field of computer software, in particular to a software recommendation method and a software recommendation system.
Background
Computer Software (Software) refers to a program and its documents in a computer system, and the program is a description of a processing object and a processing rule of a computing task; the documentation is illustrative data that is needed to facilitate understanding of the process. The program must be loaded into the machine to work, and the document is generally visible to humans and not necessarily loaded into the machine.
1. At present, a few famous flexible employment platforms exist in China, the number of effective job information released every day can reach ten thousands, but the existing flexible employment platforms relate to a wide industry and complicated jobs, and the platforms which are concentrated on flexible employment of programmers in the IT field are lacking in China.
2. Most of the existing recruitment modes confirm whether talents are suitable or not by looking up resumes and instant communication, and resume analysis of job seekers is not thorough in the recruitment process, so that the matching degree of talents and posts is poor, and recruitment wastes time and labor.
The following problems are now posed with respect to the prior art;
1. AI (Artificial Intelligence) artificial intelligence technology is not effectively fused, and the resume cannot be subjected to AI analysis to form a resume portrait of talents;
2. AI analysis can not be carried out on the post description of the enterprise to form a post requirement portrait;
3. the intelligent matching, scoring and post recommendation of talents and posts cannot be realized through AI technology.
Disclosure of Invention
The present invention is directed to a software recommendation method and system, so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme:
the software recommendation system comprises a resume free employee, an enterprise HR information publishing, a matching score, an AI talent portrait and a post label database, wherein the output end of the resume free employee is connected with the input end of uploading, the output end of uploading is connected with the input end of AI resume text analysis, the output end of AI resume text analysis is connected with the input end of labeling, the output end of labeling is respectively connected with the input ends of a free career user label, a free career professional label and a free career behavior label, the output ends of the free career user label and the free career behavior label are connected with the input end of searching correlation, and the output end of searching correlation is connected with the input end of the AI talent.
As a further scheme of the invention: the liberty caretaker user tags include name, year and month of birth, gender, household/residence, contact/mailbox/WeChat, school/academic calendar, and academic specialty.
As a still further scheme of the invention: the free career occupation labels comprise position categories, skill labels, expected salary one, work experience one, project names, project profiles and project experiences.
As a still further scheme of the invention: the discretionary actor behavioral labels include job title/certificate, employer rating, star rating, identity authentication, membership authentication, order status, and case prompts.
As a still further scheme of the invention: the HR information issuing output end of the enterprise is mutually connected with the labeled input end, the labeled output end is mutually connected with the technical requirement of an employment department, the personnel requirement of the employment department and the management requirement of the employment department respectively, the technical requirement of the employment department, the personnel requirement of the employment department and the management requirement of the employment department are mutually connected with the search related input end, and the search related output end is mutually connected with the input end of the post label database.
As a still further scheme of the invention: the technical requirements of the employment department comprise development ability, JAVA development, database construction, technical ability, programming ability, communication ability and working experience II.
As a still further scheme of the invention: the employment department personnel needs include marital status, place of residence, expected salary two, work experience three, scholars/academic levels, organization components, and background surveys.
As a still further scheme of the invention: the employment department management requirements include compliance arrangements, compliance specifications, employee codes, job leaving frequency, management capabilities, coordination capabilities, and organizational capabilities.
As a still further scheme of the invention: the input of matching score respectively with the output interconnect of the matching of individual and position, the matching of individual and team and the matching of individual and organization, the output of matching score and the input interconnect of personnel's unit, the output of personnel's unit and the input interconnect of free operator.
As a still further scheme of the invention: the person's match to the job position includes the person's knowledge, the person's skills, the person's competency, work remuneration, work motivation, and recruitment stiffness conditions.
As a still further scheme of the invention: the matching of the individuals and the teams comprises a behavior style matching degree, a value view matching degree, a team assistance capacity, a team knowledge capacity, a team fusion capacity and a team organization capacity.
As a still further scheme of the invention: the matching of the individual and the organization comprises company culture matching degree, company value and view matching degree, team style matching degree, leader style matching degree, job seeking willingness and market supply and demand relationship.
A software recommendation method comprises the following steps:
step one; the resume free caretaker analyzes the field and form text of the resume file and outputs the parsed text into a text format by uploading a PDF resume file, the text is automatically filled in basic information of a system user, the resume information can be labeled and divided into a free caretaker user label, a free caretaker occupation label and a free caretaker behavior label through AI resume text analysis, a specific AI talent portrait is formed, and an initial talent portrait is formed for the free caretaker after the resume text is analyzed;
step two; after the order of the ape dispatching platform is completed, both parties A and B can carry out star-level evaluation on the order, the evaluation result of an employer on a free job operator is used as the evaluation of the historical employer of the free job operator and is used for enriching the original talent portrait, the finally formed talent portrait is stored in a talent database by a system and is used for post matching, after the HR information issuing information of an enterprise is published, the technical requirement of an employment department, the personnel requirement of the employment department and the management requirement of the employment department can be labeled to form a post label database, and data communication can be carried out between the post label database and the AI talent portrait, so that data communication can be realized between the free job operator and the employment unit;
step three; through accurate talent post matching, can match the degree to matching of individual and position, individual and team's matching, individual and the matching of organizing respectively and score, reach a comprehensive people's post and match the score, the highest resume of degree of matching is given personnel unit to the automatic propelling movement of system, and simultaneously, the automatic propelling movement of system matches the highest position of degree and gives freedom operator, realizes accurate people's post matching.
Compared with the prior art, the invention has the beneficial effects that:
1. through the analysis of the set AI resume text, the system can support the free job owners to upload the PDF resume files, and the system analyzes the fields and form texts of the resume files and outputs the texts into a text format, and automatically fills the text format in the basic information of the system users;
2. through the labellization of setting, can carry out labellization to the text message who analyzes out, the first type is that the user information of free-standing practitioner analyzes and the labellization, includes: name, year and month of birth, gender, place of residence/place of residence, contact/mailbox/WeChat, university name, institute specialty, etc. The second type is professional information parsing and labeling of the free-job operator, and comprises the following steps: job category, skill label, expected salary, work experience, project name, project introduction, project experience, etc.;
3. through the set AI talent portrait, the mathematical modeling of the free occupation can be established for the analyzed label of the free job operator, and the accurate user portrait can be obtained through the label data of the free job operator, so that a foundation is laid for the accurate post matching of enterprises;
4. through the set post label database, post requirements can be issued to an enterprise which is resident on the platform according to the requirements of system rules, each post forms an accurate post requirement portrait and is stored in the post label database, the database is continuously and dynamically changed, when a newly added post requirement database accumulates a piece of data, when a post is closed, the database is reduced;
5. through the accurate people post matching that sets up, can match degree to the matching of individual and position, individual and team, individual and the matching of organizing respectively and score, reach a comprehensive people post and match the score value, the highest resume of degree of matching is given personnel unit to the automatic propelling movement of system, and simultaneously, the automatic propelling movement of system matches the position that the degree is the highest and gives free position owner, realizes accurate people post matching.
Drawings
FIG. 1 is a system block diagram of an AI portrait in a software recommendation method and system;
FIG. 2 is a system framework diagram of a freeform practitioner user tag in a software recommendation method and system;
FIG. 3 is a system framework diagram of a free occupational label in a software recommendation method and system;
FIG. 4 is a system framework diagram of a discretionary practitioner behavior tag in the software recommendation method and system;
FIG. 5 is a system framework diagram of a post label database in the software recommendation method and system;
FIG. 6 is a system framework diagram of the requirements for department of industry technology in the software recommendation method and system;
FIG. 7 is a system framework diagram of employment department personnel requirements in a software recommendation method and system;
FIG. 8 is a system framework diagram of a department of industry management requirement for use in a software recommendation method and system;
FIG. 9 is a system framework diagram of precision human-job matching in a software recommendation method and system;
FIG. 10 is a system framework diagram of person to job matching in the software recommendation method and system;
FIG. 11 is a system framework diagram of person to team matching in the software recommendation method and system;
FIG. 12 is a system framework diagram of the matching of individuals and organizations in the software recommendation method and system;
FIG. 13 is a system framework diagram of a software recommendation method and system;
in the figure: 1. resume free job owners; 2. uploading; 3. AI resume text analysis; 4. labeling; 5. a free caretaker user tag; 6. a free professional occupation label; 7. a free career behavior label; 8. searching for associations; 9. AI talent portrayal; 10. a name; 11. the year and month of birth; 12. sex; 13. a household residence/residence; 14. contact means/mailbox/WeChat; 15. school/school calendar; 16. the specialty of study; 17. job category; 18. a skill tag; 19. expected salary one; 20. working experience I; 21. a project name; 22. a project introduction; 23. project experience; 24. job title/certificate; 25. employer evaluation; 26. evaluating the star level; 27. identity authentication; 28. member authentication; 29. the order status; 30. case prompting; 31. issuing the HR employment information of the enterprise; 32. technical requirements of an employment department; 33. personnel requirements of an employment department; 34. managing the demand by a employment department; 35. a post label database; 36. development ability; 37. JAVA development; 38. constructing a database; 39. a technical capability; 40. a programming capability; 41. communication ability; 42. working experience II; 43. marital status; 44. a place of residence; 45. expected salary two; 46. working experience III; 47. a study calendar/degree; 48. a tissue component; 49. investigating the background; 50. subject to the arrangement; 51. compliance with the specification; 52. keeping the staff in a rule; 53. job leaving frequency; 54. a management capability; 55. a coordination capability; 56. (ii) an organizational capacity; 57. matching of individuals with positions; 58. matching of individuals to teams; 59. matching of individuals to organizations; 60. matching score values; 61. a human unit; 62. a free job; 63. knowledge of the individual; 64. the skill of the individual; 65. the capabilities of the individual; 66. work return; 67. a work mover; 68. recruitment rigid condition; 69. matching degree of behavior style; 70. matching degree of value view; 71. team assistance capability; 72. team knowledge capabilities; 73. team fusion ability; 74. team organizational ability; 75. company culture matching degree; 76. company value view matching degree; 77. matching degree of team style; 78. leading style matching degree; 79. job hunting will; 80. market supply and demand relationship.
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.
Referring to fig. 1 to 13, in the embodiment of the present invention, a software recommendation system includes a resume free job owner 1, an enterprise HR industrial information publishing 31, a matching score 60, an AI talent portrait 9, and a post label database 35, an output end of the resume free job owner 1 is connected to an input end of an upload 2, an output end of the upload 2 is connected to an input end of an AI resume text analysis 3, an output end of the AI resume text analysis 3 is connected to an input end of a labeler 4, which can support the free job owner to upload a PDF resume file, the system performs field and form text analysis on the resume file and outputs the resume file as a text format, the system automatically fills in basic information of a system user, an output end of the labeler 4 is connected to an input end of a free career user label 5, a free career label 6, and a free career behavior label 7, and can perform labeler processing on the analyzed text information, the first type is user information parsing and labeling of the free-job operator, comprising: name, year and month of birth, gender, place of residence/place of residence, contact/mailbox/WeChat, university name, institute specialty, etc. The second type is professional information parsing and labeling of the free-job operator, and comprises the following steps: the system comprises a position category, skill labels, expected salaries, work experience, project names, project introduction, project experience and the like, wherein the output ends of a free occupational user label 5 and a free occupational label 6 and a free occupational behavior label 7 are mutually connected with the input end of a search correlation 8, the output end of the search correlation 8 is mutually connected with the input end of an AI portrait 9, the analyzed free occupational mathematical modeling of the label of the free occupational can be established, and an accurate user portrait is obtained through the label data of the free occupational, so that a foundation is laid for accurate position matching of enterprises.
Preferably, the liberty occupational user tags 5 include name 10, year and month of birth 11, gender 12, residence/residence 13, contact/mailbox/WeChat 14, school/academic calendar 15, and academic specialty 16, to clearly show the liberty occupational user's basic information.
Preferably, the free occupational labels 6 include a position category 17, a skill label 18, a desired salary 19, a work experience 20, a project name 21, a project profile 22, and a project experience 23, which clearly show the conditions of the free occupational user.
Preferably, the discretionary occupational behavior tags 7 include job titles/certificates 24, employer ratings 25, star ratings 26, identity certificates 27, membership certificates 28, order status 29, and case prompts 30 to clearly demonstrate the occupational's criteria.
Preferably, the output end of the enterprise HR employment information release 31 is connected with the input end of the labeling 4, the output end of the labeling 4 is respectively connected with the input ends of the employment department technical requirement 32, the employment department personnel requirement 33 and the employment department management requirement 34, the output ends of the employment department technical requirement 32, the employment department personnel requirement 33 and the employment department management requirement 34 are connected with the input end of the search association 8, the output end of the search association 8 is connected with the input end of the post label database 35, the post requirements can be released to the enterprise which is resident on the platform according to the requirements of the system rules, each post forms an accurate post requirement portrait and is stored in the post label database, the database is constantly and dynamically changed, when a new post requirement database accumulates one piece of data, when the post is closed, the database is reduced by one piece of data.
Preferably, the technical requirements 32 of the employment department comprise development ability 36, JAVA development 37, database construction 38, technical ability 39, programming ability 40, communication ability 41 and second work experience 42, and the technical requirements required by the employment department of the enterprise can be clearly displayed.
Preferably, the employment personnel requirements 33 include marital status 43, residence 44, expected salaries two 45, work experience three 46, scholars/degrees 47, organization components 48, and background surveys 49, which clearly show the employment personnel's specific personnel requirements for the caretaker.
Preferably, the employment management requirements 34 include compliance arrangements 50, compliance specifications 51, employee codes 52, job frequency 53, management capabilities 54, coordination capabilities 55, and organizational capabilities 56, which clearly demonstrate the requirements set by the employment management requirements.
Preferably, the input end of the matching score 60 is respectively connected with the output ends of the matching 57 of the individual and the position, the matching 58 of the individual and the team and the matching 59 of the individual and the organization, the output end of the matching score 60 is connected with the input end of the employing unit 61, the output end of the employing unit 61 is connected with the input end of the free operator 62, and the comprehensive scoring of the career can be realized through the matching score.
Preferably, the person-to-job match 57 includes the person's knowledge 63, the person's skills 64, the person's competencies 65, work remuneration 66, work motivation 67, and recruitment stiffness condition 68, by which scoring of the person-to-job match is achieved.
Preferably, the person-to-team matches 58 include behavioral style matches 69, value-to-view matches 70, team assistance 71, team knowledge 72, team fusion 73, and team organization 74, which enable scoring of person-to-team matches through these scoring criteria.
Preferably, the matches 59 of the individual and the organization include a company culture matching degree 75, a company value and view matching degree 76, a team style matching degree 77, a leader style matching degree 78, a job-seeking intention 79 and a market supply and demand relationship 80, and the matching of the individual and the organization can be scored through the scoring standards.
The working principle of the invention is as follows:
when in use, the resume free-job operator 1 analyzes the fields and form texts of the resume file and outputs the fields and form texts into a text format through uploading 2PDF resume files, the resume file is automatically filled in basic information of a system user, the resume information can be labeled and divided into a free-professional user label 5, a free-professional occupational label 6 and a free-professional behavior label 7 through AI resume text analysis 3, a specific AI talent portrait 9 is formed, after the resume text is analyzed, an initial talent portrait is formed for the free-job operator 62, after an order of a ape dispatching platform is completed, two parties A and B can perform star-level evaluation 26 of the order, the evaluation result of the free-job operator 62 by an employer is used as a historical owner evaluation 25 of the free-job operator 62 for enriching the initial talent portrait, and the finally formed talent is stored in a talent database by the system for position matching, after the enterprise HR employment information release 31 information release, the enterprise HR employment information release can be labeled 4 to form a employment department technical requirement 32, a employment department personnel requirement 33 and a employment department management requirement 34, a post label database 35 is formed, data communication can be carried out between the post label database 35 and an AI talent portrait 9, so that data communication between a free employee 62 and a user organization 61 is realized, through accurate talent post matching, matching degree grading can be respectively carried out aiming at matching 57 of an individual and a position, matching 58 of the individual and a team and matching 59 of the individual and an organization, a comprehensive post matching score value 60 is obtained, the system automatically pushes a resume with the highest matching degree to the user organization 61, and meanwhile, the system automatically pushes a post with the highest matching degree to the free employee 62, so that accurate post matching is realized.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (10)
1. Software recommendation system, including resume free employee (1), enterprise HR recruitment information release (31), matching score (60), AI talent portrayal (9) and post label database (35), its characterized in that: the output of resume free career (1) and the input interconnect of uploading (2), the output of uploading (2) and the input interconnect of AI resume text analysis (3), the output of AI resume text analysis (3) and the input interconnect of labeller (4), the output of labeller (4) respectively with free career user label (5), free career occupational label (6), the input interconnect of free career action label (7), the output of free career user label (5), free career occupational label (6) free career action label (7) all with the input interconnect of search relevance (8), the output of search relevance (8) and the input interconnect of AI talent portrayal (9).
2. The software recommendation system according to claim 1, wherein: the discretionary officer user tag (5) includes name (10), year and month of birth (11), gender (12), household location/residence (13), contact/mailbox/WeChat (14), school/academic calendar (15), and academic specialty (16).
3. The software recommendation system according to claim 1, wherein: the free job operator career labels (6) comprise a position category (17), a skill label (18), a desired salary first (19), a work experience first (20), a project name (21), a project brief introduction (22) and a project experience (23).
4. The software recommendation system according to claim 1, wherein: the discretionary actor behavior tags (7) include job title/certificate (24), employer rating (25), star rating (26), identity authentication (27), membership authentication (28), order status (29), and case prompt (30).
5. The software recommendation system according to claim 1, wherein: the output of enterprise HR recruitment information issuing (31) and the input interconnect of labeller (4), the output of labeller (4) respectively with recruitment department technical requirement (32), recruitment department personnel demand (33) and recruitment department management demand (34) the input interconnect, the output of recruitment department technical requirement (32), recruitment department personnel demand (33) and recruitment department management demand (34) all with the input interconnect of search association (8), the output of search association (8) and the input interconnect of post label database (35).
6. The software recommendation system according to claim 5, wherein: the technical requirements (32) of the employment department comprise development capacity (36), JAVA development (37), database construction (38), technical capacity (39), programming capacity (40), communication capacity (41) and work experience II (42).
7. The software recommendation system according to claim 5, wherein: the employment department personnel requirements (33) include marital status (43), residence (44), expected salary two (45), work experience three (46), scholars/degrees (47), organization components (48), and background surveys (49).
8. The software recommendation system according to claim 5, wherein: the employment management requirements (34) include compliance arrangements (50), compliance specifications (51), employee rules (52), job leaving frequency (53), management capabilities (54), coordination capabilities (55), and organization capabilities (56).
9. The software recommendation system according to claim 1, wherein: the inputs of the match scores (60) are interconnected with the outputs of the person-to-job matches (57), the person-to-team matches (58), and the person-to-organization matches (59), respectively, the outputs of the match scores (60) are interconnected with the inputs of the employment units (61), the outputs of the employment units (61) are interconnected with the inputs of the free occupiers (62), the person-to-job matches (57) include personal knowledge (63), personal skills (64), personal abilities (65), work remuneration (66), work motivation (67), and recruitment conditions (68), the person-to-team matches (58) include behavioral style matches (69), value-to-view matches (70), team assistance abilities (71), team knowledge abilities (72), team fusion abilities (73), and team organization abilities (74), the matching (59) of the individual and the organization comprises a company culture matching degree (75), a company value and view matching degree (76), a team style matching degree (77), a leader style matching degree (78), a job-seeking intention (79) and a market supply and demand relationship (80).
10. A software recommendation method is characterized by comprising the following steps:
step one; the resume free caretaker analyzes the field and form text of the resume file and outputs the parsed text into a text format by uploading a PDF resume file, the text is automatically filled in basic information of a system user, the resume information can be labeled and divided into a free caretaker user label, a free caretaker occupation label and a free caretaker behavior label through AI resume text analysis, a specific AI talent portrait is formed, and an initial talent portrait is formed for the free caretaker after the resume text is analyzed;
step two; after the order of the ape dispatching platform is completed, both parties A and B can carry out star-level evaluation on the order, the evaluation result of an employer on a free job operator is used as the evaluation of the historical employer of the free job operator and is used for enriching the original talent portrait, the finally formed talent portrait is stored in a talent database by a system and is used for post matching, after the HR information issuing information of an enterprise is published, the technical requirement of an employment department, the personnel requirement of the employment department and the management requirement of the employment department can be labeled to form a post label database, and data communication can be carried out between the post label database and the AI talent portrait, so that data communication can be realized between the free job operator and the employment unit;
step three; through accurate talent post matching, can match the degree to matching of individual and position, individual and team's matching, individual and the matching of organizing respectively and score, reach a comprehensive people's post and match the score, the highest resume of degree of matching is given personnel unit to the automatic propelling movement of system, and simultaneously, the automatic propelling movement of system matches the highest position of degree and gives freedom operator, realizes accurate people's post matching.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011121523.3A CN112232773A (en) | 2020-10-19 | 2020-10-19 | Software recommendation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011121523.3A CN112232773A (en) | 2020-10-19 | 2020-10-19 | Software recommendation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112232773A true CN112232773A (en) | 2021-01-15 |
Family
ID=74118643
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011121523.3A Pending CN112232773A (en) | 2020-10-19 | 2020-10-19 | Software recommendation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112232773A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113806598A (en) * | 2021-09-23 | 2021-12-17 | 广东省通信产业服务有限公司广州分公司 | Professional talent classification statistical database and method beneficial to cloud search |
| CN113837627A (en) * | 2021-09-28 | 2021-12-24 | 卡斯柯信号有限公司 | Job title review platform and method based on text processing |
| CN113988825A (en) * | 2021-12-28 | 2022-01-28 | 深圳共链科技有限公司 | User portrait based job recommendation method, device, terminal and readable storage medium |
| CN114880573A (en) * | 2022-05-24 | 2022-08-09 | 身边云(北京)信息服务有限公司 | Free-job employee task recommendation method, electronic device and storage medium |
| CN116307489A (en) * | 2023-02-01 | 2023-06-23 | 中博信息技术研究院有限公司 | Visual dynamic analysis method and system based on user behavior modeling |
Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090070126A1 (en) * | 2007-09-10 | 2009-03-12 | Macdaniel Aaron | System and method for facilitating online employment opportunities between employers and job seekers |
| CN101840651A (en) * | 2010-05-06 | 2010-09-22 | 中国人民解放军军事医学科学院卫生装备研究所 | Cardio-pulmonary resuscitation dummy man having simulated thoracic cavity skeletal structure |
| US8548928B1 (en) * | 2001-04-06 | 2013-10-01 | Internet Employment Linkage | Method and system for providing search assistance via a communications network |
| CN104091586A (en) * | 2014-07-15 | 2014-10-08 | 齐鲁师范学院 | Music stand capable of being disassembled and assembled quickly |
| CN204303243U (en) * | 2014-12-19 | 2015-04-29 | 浙江医学高等专科学校 | Ossis irrigation and drainage model |
| CN206194247U (en) * | 2016-10-17 | 2017-05-24 | 北京医模科技股份有限公司 | Portable cardio -pulmonary resuscitation training model |
| CN109332985A (en) * | 2018-10-29 | 2019-02-15 | 李友新 | A kind of welding for steel structure device |
| CN109754233A (en) * | 2019-01-29 | 2019-05-14 | 上海嘉道信息技术有限公司 | A kind of method and system of intelligent recommendation job information |
| CN110032637A (en) * | 2019-04-16 | 2019-07-19 | 上海大易云计算股份有限公司 | A kind of resume intelligent recommendation algorithm based on natural semantic analysis technology |
| CN110626407A (en) * | 2019-09-29 | 2019-12-31 | 明光市飞洲新材料有限公司 | Conveniently-toppled transport device for attapulgite |
| CN111125343A (en) * | 2019-12-17 | 2020-05-08 | 领猎网络科技(上海)有限公司 | Text analysis method and device suitable for human-sentry matching recommendation system |
| KR20200050236A (en) * | 2018-11-01 | 2020-05-11 | 이창기 | Job matching and management system for daily workers |
| CN111144723A (en) * | 2019-12-17 | 2020-05-12 | 埃摩森网络科技(上海)有限公司 | Method and system for recommending people's job matching and storage medium |
| CN213518882U (en) * | 2020-10-16 | 2021-06-22 | 珠海维尔康生物科技有限公司 | Operation training model for simulating human tissue vertebra characteristics |
| CN213582746U (en) * | 2020-10-24 | 2021-06-29 | 鲍竹青 | Portable cardio-pulmonary resuscitation training model |
| CN213644391U (en) * | 2020-09-25 | 2021-07-09 | 胡英 | Novel coal breaker |
| CN214312323U (en) * | 2020-09-21 | 2021-09-28 | 医视角科技(深圳)有限公司 | Multi-machine interconnection group cardiopulmonary resuscitation first-aid examination model |
| CN214860992U (en) * | 2021-04-28 | 2021-11-26 | 青岛驰健英赛特健康科技有限公司 | Pull-down trainer in reverse hand |
| CN215282310U (en) * | 2020-10-15 | 2021-12-24 | 昆山华崎创为精密机械有限公司 | Die-cutting rule for circular knife die-cutting machine |
| CN114469584A (en) * | 2022-02-10 | 2022-05-13 | 殷慧丽 | Postoperative care device for ophthalmology and using method thereof |
| CN115279093A (en) * | 2022-08-22 | 2022-11-01 | 深圳市铁甲科技有限公司 | Novel wireless remote control power supply controller |
-
2020
- 2020-10-19 CN CN202011121523.3A patent/CN112232773A/en active Pending
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8548928B1 (en) * | 2001-04-06 | 2013-10-01 | Internet Employment Linkage | Method and system for providing search assistance via a communications network |
| US20090070126A1 (en) * | 2007-09-10 | 2009-03-12 | Macdaniel Aaron | System and method for facilitating online employment opportunities between employers and job seekers |
| CN101840651A (en) * | 2010-05-06 | 2010-09-22 | 中国人民解放军军事医学科学院卫生装备研究所 | Cardio-pulmonary resuscitation dummy man having simulated thoracic cavity skeletal structure |
| CN104091586A (en) * | 2014-07-15 | 2014-10-08 | 齐鲁师范学院 | Music stand capable of being disassembled and assembled quickly |
| CN204303243U (en) * | 2014-12-19 | 2015-04-29 | 浙江医学高等专科学校 | Ossis irrigation and drainage model |
| CN206194247U (en) * | 2016-10-17 | 2017-05-24 | 北京医模科技股份有限公司 | Portable cardio -pulmonary resuscitation training model |
| CN109332985A (en) * | 2018-10-29 | 2019-02-15 | 李友新 | A kind of welding for steel structure device |
| KR20200050236A (en) * | 2018-11-01 | 2020-05-11 | 이창기 | Job matching and management system for daily workers |
| CN109754233A (en) * | 2019-01-29 | 2019-05-14 | 上海嘉道信息技术有限公司 | A kind of method and system of intelligent recommendation job information |
| CN110032637A (en) * | 2019-04-16 | 2019-07-19 | 上海大易云计算股份有限公司 | A kind of resume intelligent recommendation algorithm based on natural semantic analysis technology |
| CN110626407A (en) * | 2019-09-29 | 2019-12-31 | 明光市飞洲新材料有限公司 | Conveniently-toppled transport device for attapulgite |
| CN111125343A (en) * | 2019-12-17 | 2020-05-08 | 领猎网络科技(上海)有限公司 | Text analysis method and device suitable for human-sentry matching recommendation system |
| CN111144723A (en) * | 2019-12-17 | 2020-05-12 | 埃摩森网络科技(上海)有限公司 | Method and system for recommending people's job matching and storage medium |
| CN214312323U (en) * | 2020-09-21 | 2021-09-28 | 医视角科技(深圳)有限公司 | Multi-machine interconnection group cardiopulmonary resuscitation first-aid examination model |
| CN213644391U (en) * | 2020-09-25 | 2021-07-09 | 胡英 | Novel coal breaker |
| CN215282310U (en) * | 2020-10-15 | 2021-12-24 | 昆山华崎创为精密机械有限公司 | Die-cutting rule for circular knife die-cutting machine |
| CN213518882U (en) * | 2020-10-16 | 2021-06-22 | 珠海维尔康生物科技有限公司 | Operation training model for simulating human tissue vertebra characteristics |
| CN213582746U (en) * | 2020-10-24 | 2021-06-29 | 鲍竹青 | Portable cardio-pulmonary resuscitation training model |
| CN214860992U (en) * | 2021-04-28 | 2021-11-26 | 青岛驰健英赛特健康科技有限公司 | Pull-down trainer in reverse hand |
| CN114469584A (en) * | 2022-02-10 | 2022-05-13 | 殷慧丽 | Postoperative care device for ophthalmology and using method thereof |
| CN115279093A (en) * | 2022-08-22 | 2022-11-01 | 深圳市铁甲科技有限公司 | Novel wireless remote control power supply controller |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113806598A (en) * | 2021-09-23 | 2021-12-17 | 广东省通信产业服务有限公司广州分公司 | Professional talent classification statistical database and method beneficial to cloud search |
| CN113806598B (en) * | 2021-09-23 | 2024-04-05 | 广东省通信产业服务有限公司广州分公司 | Professional classification statistical database and method facilitating cloud search |
| CN113837627A (en) * | 2021-09-28 | 2021-12-24 | 卡斯柯信号有限公司 | Job title review platform and method based on text processing |
| CN113837627B (en) * | 2021-09-28 | 2024-03-15 | 卡斯柯信号有限公司 | Title review platform and method based on text processing |
| CN113988825A (en) * | 2021-12-28 | 2022-01-28 | 深圳共链科技有限公司 | User portrait based job recommendation method, device, terminal and readable storage medium |
| CN113988825B (en) * | 2021-12-28 | 2022-04-12 | 深圳共链科技有限公司 | User portrait based job recommendation method, device, terminal and readable storage medium |
| CN114880573A (en) * | 2022-05-24 | 2022-08-09 | 身边云(北京)信息服务有限公司 | Free-job employee task recommendation method, electronic device and storage medium |
| CN116307489A (en) * | 2023-02-01 | 2023-06-23 | 中博信息技术研究院有限公司 | Visual dynamic analysis method and system based on user behavior modeling |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112232773A (en) | Software recommendation method and system | |
| Bollinger et al. | Managing organizational knowledge as a strategic asset | |
| Malmelin et al. | Managing creativity in change: Motivations and constraints of creative work in a media organisation | |
| Orna | Practical information policies | |
| Joe et al. | Knowledge loss when older experts leave knowledge-intensive organisations | |
| Bound | Vocational education and training teacher professional development: Tensions and context | |
| Fawcett et al. | Spirituality and organizational culture: Cultivating the ABCs of an inspiring workplace | |
| Schmitt | Supporting the sustainable growth of SMEs with content-and collaboration-based personal knowledge management systems | |
| Xiao et al. | Development of a competency model for real-estate project managers: case study of China | |
| Hewko et al. | Performance management in healthcare: a critical analysis | |
| US20200302397A1 (en) | Screening-based opportunity enrichment | |
| Huang et al. | A network analysis of cross-occupational skill transferability for the hospitality industry | |
| Iles | Talent balancing: Staffing your company for long-term success | |
| Toves et al. | Innovative use of force field analysis: Factors influencing technology-enabled change | |
| Rodrigues et al. | Towards an integrated management information system: A case of the University of Mauritius | |
| Santirojanakul | The development of sports science knowledge management systems through CommonKADS and digital Kanban board | |
| Sari et al. | How important leadership and organizational culture to build working motivation | |
| Ho et al. | The state of human resource (HR) competency research: Charting the research development of HR competencies and examining the signals from industry in New Zealand | |
| Bani | Human Resources’ Capacity to Drive Organizational Change in Ghana | |
| Guimarães et al. | Lean, a tool set or a mind set? A healthcare case study | |
| Karimi et al. | Identifying the Requirements and Functions of Ambidextrous Management of Sports Volunteers | |
| Muthu et al. | Knowledge management in libraries | |
| Busseau | The Upside and Downside of Outsourcing: Investigating the Impact on Permanent Employees | |
| Silvianita et al. | The Influence of Organisational Culture and Knowledge Sharing on Employee Performance at PT XYZ | |
| Andem et al. | Knowledge sharing (KS) strategy and operational performance in University of Uyo Teaching Hospital, Uyo–Nigeria |
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 |