Team building system

Abstract

The invention provides a team building system. The team building system provides a publishable and queriable platform for talent data of employees in all regions in an enterprise and information of a team collected for solving temporary tasks in the enterprise, and assists task publishers and employees in the enterprise in effective matching based on pre-constructed occupational demand dimensions. And the problem of information asymmetry between internal talents of an enterprise and staged tasks is effectively solved. According to the team building system provided by the invention, on one hand, the situation that internal talents of an enterprise cannot timely discover tasks matched with own capabilities due to lack of channels is broken through, and on the other hand, proper talents can be quickly and accurately screened out for the tasks through an intelligent matching mechanism, so that the team building period is shortened, and the task execution efficiency is improved. In addition, the team building system also achieves business, finance and manpower, and provides an efficient and convenient solution for talent flow and task promotion in an enterprise.

Description

Technical Field

[0001] The technical solution provided in this application relates to the field of team building or talent allocation within an enterprise, specifically to a team building system. Background Technology

[0002] In today's nationwide companies, the challenges of talent resource allocation and the uneven regional development of talent are particularly prominent. On the one hand, while companies have extensive nationwide operations, poor internal information flow leads to many talented individuals remaining idle while awaiting suitable assignments due to a lack of clear guidance. This is especially true in branches in specialized business areas or remote regions, where there is a significant disconnect between task demands and talent supply. On the other hand, when facing rapidly changing market and business demands and needing to build teams to complete phased tasks / specific projects, companies struggle to quickly match suitable talent, resulting in slow project progress and even missed development opportunities. This situation not only wastes corporate human resources but also prevents the full utilization of talent's potential, further exacerbating the imbalance between the regional distribution of talent and project / task progress within the company. Therefore, breaking down information barriers and optimizing the matching mechanism between talent and tasks has become a crucial issue that nationwide companies urgently need to address. Summary of the Invention

[0003] This application addresses the problem that existing internal talent resource allocation within enterprises is insufficient to meet the needs of project / phased task execution. It provides a team-building system. This system utilizes network technology combined with semantic reasoning models to achieve accurate identification of internal talent and efficient matching with project / phased task requirements. This team-building system not only helps positions with task requirements find suitable talent promptly, improving the efficiency of talent resource utilization, but also provides functions such as task acceptance, accounting, and payment settlement, enabling management of the formed team throughout the entire task lifecycle.

[0004] The team building system in this application includes a talent entry module, a talent pool, a talent posting module, a talent marketplace, a task posting module, a task marketplace, and a team building module.

[0005] The talent entry module is used to input talent data of internal personnel. Based on the talent data entered by each person, it extracts corresponding talent tags from each preset career requirement dimension using keywords, thereby constructing a talent tag group for each internal personnel. The talent data of each person and its corresponding talent tag group are then stored in a talent database. The talent posting module allows internal personnel to choose whether to post their talent data and talent tag group on the company's intranet talent marketplace. The task posting module allows various departments within the company to initiate phased tasks based on their needs and recruit talent to form teams. The team building module allocates a virtual workspace for team members to work in each posted phased task, and assists the task poster in forming teams to complete the corresponding phased tasks based on each internal personnel's talent tag group.

[0006] Furthermore, the preset professional requirements dimensions include: education, resume, project experience, professional skills, qualification certificates, personality, age, whether it is a remote expert, and current geographical location. The task posting module requires task posters to specify the task requirements for their posted phased tasks. These requirements include: a description of the phased task, requirements for target talent, work mode, team formation format, team location, and task budget. The work mode options include at least full-time and part-time; the team formation format includes at least remote / online collaboration and on-site centralized collaboration.

[0007] Furthermore, the team building module accesses the task marketplace and the talent market through preset interfaces, providing a first set of interfaces for internal personnel to search for tasks in the task marketplace that match their skills and experience, and to recommend themselves to join the corresponding teams. The team building module also provides a second set of interfaces for task publishers to search for and invite suitable talents to join the teams they wish to build in the talent market, based on the characteristics of the phased tasks they publish and the talent requirements.

[0008] Furthermore, based on the task requirements of each phase, the team-building module extracts talent tags from the preset professional needs dimension to serve as query tags for the required personnel. It then searches the talent market for individuals with these query tags as candidate talents. The module matches the talent data of each candidate with the task requirements to obtain recommended talent, and sends recommendation information to the relevant task publisher and recommended talent to facilitate team building.

[0009] Further, the step of matching the talent data of the candidates with the task requirements to obtain corresponding recommended talents includes: calculating the matching result using a semantic reasoning model by comparing the requirements of each query tag in the corresponding task requirements with the corresponding content in the talent data of the candidates for that talent tag; obtaining a matching score for each candidate based on the matching result and a pre-assigned score for each professional requirement dimension; and selecting candidates with scores greater than a preset value as recommended talents. The professional requirement dimension of "current geographical location" has the highest pre-assigned score, and its matching degree is obtained by the following method: calculating the matching degree of this professional requirement dimension by the distance between the candidate's current geographical location and the location of the team in the corresponding task requirements. Preferably, the semantic reasoning model is a third-party semantic reasoning model, including Deepseek and ChaGPT.

[0010] In some embodiments, the team building system further includes a task accounting / acceptance module and a payment and talent evaluation module. Task publishers or corresponding team members can use the task accounting / acceptance module to initiate task acceptance and revenue calculation for individuals. After the task acceptance and revenue calculation are approved, the payment and talent evaluation module will send the corresponding settlement amount to the financial system to complete the payment; afterwards, it provides an interface for task publishers to evaluate or score the performance of relevant team members.

[0011] The team building system provided by this invention offers a platform for communicating talent and task / project needs within an enterprise. By setting talent tags, it assists task publishers and internal personnel in searching for relevant talent or project / task information. Combined with a semantic reasoning model, it helps task publishers and internal talent achieve precise matching to facilitate project / task implementation. This team building system effectively breaks down information barriers between internal talent and task publishers, effectively solving the problem of information asymmetry between talent and tasks, shortening the team building cycle, and improving the efficiency of task / project implementation. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 A schematic diagram of one embodiment of the team building system provided in this application.

[0014] Explanation of reference numerals in the attached figures: 1-Talent Entry Module, 2-Talent Pool, 3-Talent Posting Module, 4-Talent Marketplace, 5-Task Posting Module, 6-Task Marketplace, 7-Team Building Module, 8-Task Receipt Module, 9-Task Calculation / Acceptance Module, 91-Payment and Talent Evaluation Module. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0016] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0017] Figure 1 This is a schematic diagram of the team building system of this application in one embodiment. Figure 1 The team building system 100 shown includes a talent entry module 1, a talent pool 2, a talent posting module 3, a talent marketplace 4, a task posting module 5, a task marketplace 6, a team building module 7, a task verification module 8, a task accounting / acceptance module 9, and a payment and talent evaluation module 91.

[0018] The talent entry module 1 is used to input talent data of internal personnel. Based on the talent data entered by each person, it extracts corresponding talent tags from each preset career requirement dimension using keywords, thereby constructing a talent tag group for each internal personnel. The talent data of each person and its corresponding talent tag group are then linked and stored in the talent database 2. The preset career requirement dimensions include: education, resume, project experience, professional skills, qualification certificates, personality, age, whether a person is a remote expert, and current geographical location. For example, if a person's education is "high school-bachelor's-master's", then the highest education level "master's" can be used as the talent tag content for their "education" dimension; if the person's professional skills are "familiar with Redis programming, proficient in JAVA programming", then "redis, JAVA" can be used as the talent tag content for their "professional skills" dimension. For "resume", the industry and position worked can be extracted as the corresponding talent tag content.

[0019] The talent posting module 3 allows internal staff to choose whether to post their talent data and talent tag groups on the company's intranet talent marketplace 2. Posted talent information is visible / public within the company.

[0020] The task posting module 3 allows task posters within the enterprise to initiate phased tasks and recruit talent to form teams on the task marketplace 6. Phased tasks posted on the task marketplace 6 are visible / public within the company and can be searched by internal personnel. The task posting module 3 requires task posters to specify the requirements of their posted phased tasks. These requirements include: a description of the phased task, requirements for target talent, work mode, team formation format, team location, and task budget. The work mode options include at least full-time and part-time; the team formation format includes at least remote / online collaboration and on-site team building. Optionally, the task posting module 3 provides a dedicated input page for the above information, allowing task posters to input information according to their actual needs.

[0021] The team building module 5 allocates a virtual workspace for team members to work in for each published phased task, and forms teams based on the talent tag groups of each internal employee and the task publisher to complete the corresponding phased tasks. As can be seen from the function of the team building module 5, it needs to communicate with the talent marketplace 2 and the task marketplace 6 to obtain data / information from these two marketplaces. Therefore, a preset interface is set up for the team building module 5 to access the task marketplace 6 and the talent marketplace 2.

[0022] In some embodiments, the team building module 5 provides a first set of interfaces for internal personnel to search for tasks in the task marketplace 6 that match their skills and experience, and to recommend themselves to join the corresponding team. It also provides a second set of interfaces for task publishers to search for and invite suitable talents to join the team they wish to build in the talent market 2 based on the characteristics of the phased tasks they publish and the talent requirements.

[0023] Furthermore, the team building module, based on the task requirements of the five phased tasks, extracts corresponding talent tags from the preset professional requirement dimensions as query tags, and searches the talent market for individuals with the aforementioned query tags as candidate talents (those whose task requirements do not involve professional requirement dimensions are directly ignored). The talent data of each candidate talent is matched with the task requirements to obtain corresponding recommended talents, and recommendation information is sent to the corresponding task publisher and the corresponding recommended talents to facilitate team building.

[0024] Furthermore, the step of matching the talent data of the candidates with the task requirements to obtain corresponding recommended talents includes: calculating the matching result using a semantic reasoning model by comparing the requirements of each of the query tags in the corresponding task requirements with the corresponding content of the talent tags in the talent data of the candidates; obtaining a matching score for each candidate based on the matching result and the pre-assigned score for each professional requirement dimension; and selecting candidates with scores greater than a preset value as recommended talents. For example, ChapGpt or Deepseek can be used to calculate the similarity of related content as the corresponding matching result. Based on the pre-set weights / scores for each talent tag, the corresponding recommended talent score is calculated as the proportion of the score that can be obtained when all talent data under all novelty tags completely match the task; then, this proportion is converted into a percentage value as the corresponding candidate's score.

[0025] Among the aforementioned talent tags / query tags, the "current geographical location" career requirement dimension has the highest pre-assigned score. Its matching degree is obtained by calculating the distance between the candidate's current geographical location and the location of the team in the corresponding task requirement. For example, in the embodiment shown in the table below, for the talent tag "current geographical location," if it is determined to be within the same province, it is assigned 5 points. Preferably, the semantic reasoning ability model is a third-party semantic reasoning model, including Deepseek and ChaGPT.

[0026]

[0027] In some embodiments, the team building system further includes a task accounting / acceptance module 9 and a payment and talent evaluation module 91. Task publishers or corresponding team members can use the task accounting / acceptance module 9 to initiate task acceptance and income calculation for individuals. For example, relevant personnel can initiate acceptance of individual work results / progress in the previously assigned team work virtual space and calculate corresponding compensation. After the acceptance and calculation results are approved, the payment and talent evaluation module 91 is triggered to send the corresponding settlement amount to the financial system to complete the payment, and provides an interface for task publishers to evaluate or score the performance of relevant team members.

[0028] The team building system provided by this invention effectively breaks down the information barriers between talents and task issuers within an enterprise by leveraging artificial intelligence / semantic reasoning models, effectively shortening the matching process between talents and tasks and the team building cycle, and improving the efficiency of task / project implementation.

[0029] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; once an item is defined in one figure, it does not need further definition and explanation in subsequent figures.

Claims

1. A team building system, characterized by, The team building system comprises a talent input module, a talent database, a talent publishing module, a talent market, a task publishing module, a task market, a team building module, and a task checking module. The talent input module is used for inputting talent data of enterprise internal personnel, and according to the talent data of each personnel, talent tags are extracted from each preset professional requirement dimension in the form of keywords, and then a talent tag group of each enterprise internal personnel is constructed, and the talent data of each personnel and the corresponding talent tag group are stored in the talent database. The talent publishing module is used for enterprise internal personnel to select whether to publish their talent data and talent tag group in the talent market of the enterprise intranet. The task publishing module is used for each institution in the enterprise to initiate a phased task according to the demand and collect talents to form a team. The team building module allocates a team work virtual space for each launched phased task for team members to work, and forms a team according to the talent tag group of each enterprise internal personnel and auxiliary task publishers to complete the corresponding phased task.

2. The team building system of claim 1, wherein, The preset professional requirement dimension includes education, resume, project experience, professional skill, qualification certificate, personality, age, whether a remote expert, and current geographical location.

3. The team building system of claim 1, wherein, The task publishing module requires the task publisher to describe the task demand of the launched phased task, and the content of the task demand includes phased task description, requirement for target talents, work mode, team building form, team location, and task budget amount.

4. The team building system of claim 3, wherein, The work mode corresponds to at least full-time and part-time, and the team building form includes at least remote / network cooperation and on-site concentration.

5. The team building system of claim 3 or 4, wherein, The team building module accesses the task market and the talent market through a preset interface, provides a first group of interfaces for enterprise internal personnel to search for tasks in the task market that meet their skills and experience, and recommend themselves to join the corresponding team; the team building module also provides a second group of interfaces for the task publishing party to search for and invite suitable talents to join the team to be built in the talent market according to the characteristics of the launched phased task and the required talents.

6. The team building system of claim 5, wherein, The team building module also extracts talent tags of required talents from the preset professional requirement dimension based on the task demand of the phased task, as query tags, searches for personnel with the above query tags in the talent market as candidate talents, matches the talent data of the candidate talents with the task demand one by one to obtain corresponding recommended talents, and sends recommendation information to the corresponding task publisher and the corresponding recommended talents to promote team building.

7. The team building system of claim 6, wherein, The matching of the talent data of the candidate talents with the task requirements to obtain corresponding recommended talents comprises: matching each of the query tags with the requirements in the corresponding task requirements with the model having semantic reasoning capability to calculate the matching results of the corresponding content of the talent tags in the talent data of the candidate talents, obtaining the matching scores of each candidate talent according to the matching results and the scores previously assigned to each professional requirement dimension, and taking the personnel with the scores greater than a preset value as the recommended talents; wherein the score previously assigned to the professional requirement dimension of "current geographical location" is the highest, and the corresponding matching degree is obtained by the following method: obtaining the matching degree of the professional requirement dimension from the distance between the current geographical location of the candidate talent and the region of the team corresponding to the task requirement.

8. The team building system of claim 7, wherein, The model having semantic reasoning capability is a third-party semantic reasoning model, and the third-party semantic reasoning model comprises Deepseek and ChaGPT.

9. The team building system of claim 7, wherein, The team building system further comprises a task accounting / acceptance module; the task publisher or the corresponding team member can initiate the acceptance of the task completed by the individual and the accounting of the income amount by means of the task accounting / acceptance module.

10. The team building system of claim 7, wherein, The team building system further comprises a payment and talent evaluation module; the payment and talent evaluation module issues the corresponding settlement amount to the financial system to complete the payment after the task acceptance and the income amount accounting are approved; and then an operation interface is provided for the task publisher to evaluate or score the performance of the related team members. The team building system further comprises a task accounting / acceptance module; the task publisher or the corresponding team member can initiate the acceptance of the task completed by the individual and the accounting of the income amount by means of the task accounting / acceptance module.

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