Intelligent matching method for workers based on user demand priority
By matching gig job information with recruitment personnel priority settings through platform algorithms, the problem of applicants finding it difficult to find suitable gig jobs has been solved, thereby improving recruitment efficiency and resource utilization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-15
- Publication Date
- 2026-03-31
AI Technical Summary
In gig recruitment, job seekers often struggle to find suitable gig work after submitting numerous resumes. Recruiters have to expend a lot of manpower and resources to screen resumes, resulting in the inefficient use of human resources and the inability of skilled job seekers to fully utilize their talents.
The platform's algorithm intelligently matches job postings to applicants based on their data profiles, and allows recruiters to set service priorities, enabling applicants to choose their preferred matching method and improving matching efficiency.
This approach effectively matches applicants with recruiters, improves recruitment efficiency, makes full use of human resources, and ensures that applicants can better utilize their talents.
Smart Images
Figure CN121766946A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of gig worker demand matching technology, and more specifically to a gig worker intelligent matching method based on user demand priority. Background Technology
[0002] In the current gig job recruitment process, job seekers need to spend a significant amount of time finding suitable positions, while recruiters also need to expend considerable human, material, and financial resources to screen suitable workers. The most basic task is to eliminate applicants who do not meet the basic requirements and select suitable workers for different positions, thereby achieving a reasonable match between human and human resources. However, different people have a certain degree of subjectivity in their understanding of the job, resulting in different interpretations. In addition, job seekers often have the mentality of mass-submitting resumes, so they often still do not find suitable gig jobs after submitting a large number of resumes. Recruiters also have to spend a lot of human and material resources to screen resumes, leading to the inefficient use of human resources. This also results in many skilled and talented job seekers being unable to fully utilize their talents and thus failing to find gig jobs. Summary of the Invention
[0003] The purpose of this invention is to provide a gig work intelligent matching method based on user demand priority, in order to solve the problem mentioned in the background art where job seekers still cannot find suitable gig work after submitting a large number of resumes, while the recruiting party also has to spend a lot of human and material resources to screen resumes, resulting in the inefficient use of human resources and the inability of many skilled and talented job seekers to better utilize their talents, thus leading to the phenomenon of not being able to find gig work.
[0004] To achieve the above objectives, the present invention provides the following technical solution: A gigabit matching method based on user demand priority includes: Applicants should edit their information according to their own qualifications; Applicants should choose the matching method based on their circumstances; Applicants send matching requirements; Send notifications to both the recruiters and applicants who are successfully matched. The applicant completes the service, and the recruiter settles the payment. The platform creates data profiles based on the order acceptance status of job applicants; Recruiters input their service needs in a priority order; Orders are driven by intelligent matching based on applicant data profiles.
[0005] As a preferred option, applicants should be job seekers who need part-time work. Applicants need to write down their age, health status, skills, expectations for the job, working hours, work location, payment method, start and end time, etc., and send them to the platform. In addition to text descriptions, applicants can also describe their situation by shooting short videos or recording voice messages.
[0006] As a preferred option, job seekers can choose to manually search for part-time jobs or have the platform automatically match them with part-time jobs, depending on their circumstances.
[0007] As a preferred option, when job seekers choose the platform's automatic matching system for gig workers, the platform will create a data profile based on the information provided by the job seeker and automatically match them with suitable candidates from the orders placed by recruiters on the platform. After the matching is completed, the platform will send a notification to both the recruiter and the job seeker. Subsequently, the job seeker completes the services requested by the recruiter, and after the recruiter settles the payment, the order is marked as complete and entered into the database. This order will be merged with the data profile previously created by the platform based on the job seeker to create a new data profile, which will be used as the basis for subsequent automatic matching.
[0008] As a preferred option, when job seekers choose to manually match gigs, the platform will list the gigs posted by recruiters. Job seekers then need to choose from these orders according to their own requirements. The platform will send a notification to both the recruiter and the job seeker if a match is successfully made. After the job seeker completes the service required by the recruiter and the recruiter settles the payment, the order is marked as complete and entered into the database. This order will be merged with the data profile previously created by the platform based on the job seeker to form a new data profile. Subsequent automatic matching will use the latest data profile as a blueprint.
[0009] Preferably, after the platform creates a data profile based on the order acceptance status of job applicants, the data will be incorporated into the platform's overall data so as to be merged with the priority classification data required by the recruiters, thereby enabling the platform to push orders more intelligently.
[0010] Preferably, the recruiter is the person who posts the gig job and becomes the employer of the applicant after the matching is completed. When posting gig jobs to the platform, the recruiter can make priority adjustments to the applicant's age, health status, skills, expectations for the job, working hours, working location, payment method, start and end time, and other items during the matching process.
[0011] Compared with the prior art, the beneficial effects of the present invention are: This intelligent gig job matching method, based on user needs and priority, uses the platform's algorithm to intelligently match job information to applicants. Applicants can also search for gig jobs themselves based on their personal circumstances. Recruiters can also prioritize their service requirements. This ensures that both parties receive feedback from qualified applicants and recruiters, achieving effective matching, improving the efficiency of both the application and recruitment processes, and making full use of human resources. Attached Figure Description
[0012] Figure 1 This is a schematic diagram of the job matching process of the present invention. Implementation
[0013] 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 some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0014] Please see Figure 1 This invention provides multiple technical solutions: 1. When a user uses the platform for the first time and selects the platform's automatic matching method: Step 101: Applicants edit their information based on their own qualifications.
[0015] Specifically, applicants need to compile their own information, including age, health status, skills, job expectations, work hours, work location, payment method, start and end dates, etc., and send it to the platform. In addition to text descriptions, applicants can also describe themselves by shooting short videos or recording voice messages. This will help the platform create an initial data profile of the applicants based on this information, which will facilitate the subsequent matching process.
[0016] Step 102: Applicants select matching method.
[0017] Specifically, applicants can choose whether the platform will automatically match them or they will match them manually, which increases their autonomy in accepting orders.
[0018] Step 103: The platform automatically matches.
[0019] Specifically, the platform uses algorithms and existing data profiles to intelligently match job seekers with available orders, automatically matching them with suitable candidates from the orders placed by recruiters on the platform.
[0020] Step 104: The applicant sends the application to the matching requirements.
[0021] Specifically, job applicants confirm the gig work orders automatically matched with recruiters by the platform.
[0022] Step 105: The platform matches applicants based on their information.
[0023] Specifically, after applicants confirm their selection of the platform's automatic matching, the platform will use the constructed algorithm and the applicant's existing data profile to find and match qualified candidates from the orders placed by recruiters on the platform. When applicants undergo the initial automatic matching, the platform will perform an initial matching based on the initial data profile created from the information uploaded by the applicants.
[0024] Step 106: Send a notification to the successfully matched recruiters and applicants.
[0025] Specifically, once the platform successfully matches an order, it will send text and voice notifications to both the recruiter and the applicant to inform them of the successful match.
[0026] Step 107: The applicant completes the task, and the recruiter settles the payment.
[0027] Specifically, after the applicant completes the order agreed upon with the recruiter, the recruiter settles the payment according to the payment method selected by the applicant, and the order is then completed.
[0028] Step 108: The platform creates a data profile based on the order acceptance status of job applicants.
[0029] Specifically, once the applicant completes the services required by the recruiter and the recruiter settles the payment, the order is marked as complete and entered into the database. This order will be merged with the data profile previously created by the platform based on the applicant to form a new data profile. In subsequent automatic matching, the latest data profile will be used as a blueprint to improve the applicant's data profile, thereby helping the applicant to be better matched with gig workers in the future.
[0030] Step 109: Recruiters input their service needs in order of priority.
[0031] Specifically, when recruiters post gig jobs on the platform, they can prioritize applicants based on factors such as age, health, skills, job expectations, work hours, location, payment method, and start and end times. The platform's algorithm intelligently filters out unqualified service providers, reducing ineffective work and improving matching efficiency. This ensures that both applicants and recruiters receive feedback from qualified candidates during the matching process, saving both parties time and resources.
[0032] Step 110: Intelligently match and push orders based on applicant data profiles.
[0033] Specifically, after the platform creates a data profile based on the order acceptance status of job applicants, this data is incorporated into the platform's overall data. This data is then merged with the priority tier data requested by the recruiters, allowing the platform to push orders more intelligently. This ensures that the orders pushed to job applicants in the subsequent order acceptance process are orders that closely match their expectations.
[0034] The entire automatic order matching process is now complete, and job applicants can start accepting orders again.
[0035] When a user uses the platform for the first time and chooses to manually match the data: Step 101: Applicants edit their information based on their own qualifications.
[0036] Specifically, applicants need to compile their own information, including age, health status, skills, job expectations, work hours, work location, payment method, start and end dates, etc., and send it to the platform. In addition to text descriptions, applicants can also describe themselves by shooting short videos or recording voice messages. This will help the platform create an initial data profile of the applicants based on this information, which will facilitate the subsequent matching process.
[0037] Step 102: Applicants select matching method.
[0038] Specifically, applicants can choose whether the platform will automatically match them or they will match them manually, which increases their autonomy in accepting orders.
[0039] Step 111: Manually match applicants.
[0040] Specifically, when job seekers choose to manually match themselves with gig workers, the platform will list the gig jobs posted by recruiters, and job seekers can choose to accept jobs according to their own requirements.
[0041] Step 112: Applicants can choose to accept orders based on their own requirements.
[0042] Specifically, the platform will list the gig jobs posted by recruiters. Applicants need to browse the list on the platform and then choose to accept the job based on their own requirements.
[0043] Step 113: Applicants manually filter information and make matches.
[0044] Specifically, after job seekers have completed their own search, they can match themselves with suitable part-time jobs.
[0045] Step 114: Send notifications to the successfully matched recruiters and applicants.
[0046] Specifically, once the platform successfully matches an order, it will send text and voice notifications to both the recruiter and the applicant to inform them of the successful match.
[0047] Step 115: The applicant completes the task, and the recruiter settles the payment.
[0048] Specifically, after the applicant completes the order agreed upon with the recruiter, the recruiter settles the payment according to the payment method selected by the applicant, and the order is then completed.
[0049] Step 108: The platform creates a data profile based on the order acceptance status of job applicants.
[0050] Specifically, once the applicant completes the services required by the recruiter and the recruiter settles the payment, the order is marked as complete and entered into the database. This order will be merged with the data profile previously created by the platform based on the applicant to form a new data profile. In subsequent automatic matching, the latest data profile will be used as a blueprint to improve the applicant's data profile, thereby helping the applicant to be better matched with gig workers in the future.
[0051] Step 109: Recruiters input their service requirements in order of priority.
[0052] Specifically, when recruiters post gig jobs on the platform, they can prioritize applicants based on factors such as age, health, skills, job expectations, work hours, location, payment method, and start and end times. The platform's algorithm intelligently filters out unqualified service providers, reducing ineffective work and improving matching efficiency. This ensures that both applicants and recruiters receive feedback from qualified candidates during the matching process, saving both parties time and resources.
[0053] Step 110: Intelligently match and push orders based on applicant data profiles.
[0054] Specifically, after the platform creates a data profile based on the order acceptance status of job applicants, this data is incorporated into the platform's overall data. This data is then merged with the priority tier data requested by the recruiters, allowing the platform to push orders more intelligently. This ensures that the orders pushed to job applicants in the subsequent order acceptance process are orders that closely match their expectations.
[0055] The entire manual order matching process is now complete, and applicants can start accepting orders again.
[0056] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.
[0057] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.
Claims
1. A zero-intelligence matching method based on user demand priority, comprising: The job seeker edits information according to his own conditions; The job seeker selects the matching method according to the situation; The job seeker sends the matching demand; Send a notice to the successful matching of the recruiter and the job seeker; The job seeker completes the service, and the recruiter settles the account; The platform makes a data portrait according to the job seeker's order acceptance; The recruiter inputs the demand for service priority; Intelligent matching according to the job seeker's data portrait to promote orders.
2. The method of claim 1, wherein the method is based on a user demand priority. The job seeker is a job seeker who needs zero work. The job seeker needs to write his own age, health condition, skills, work expectations, work time requirements, work location requirements, settlement method, start and end time, etc. into text information and send it to the platform. In addition to the text description, the job seeker can also describe his own situation through short video shooting and voice recording.
3. The method of claim 1, wherein the method is based on user demand priority. The job seeker can independently choose to manually search for zero work or have the platform automatically match zero work according to the situation.
4. The method of claim 3, wherein the method further comprises: In the case of the job seeker choosing the platform to automatically match zero work, the platform will make a data portrait according to the information left by the job seeker, and find the qualified ones in the orders under the platform recruiter to complete automatic matching. After the matching is completed, the platform will send a notice to the successful matching of the recruiter and the job seeker. After that, the job seeker completes the service required by the recruiter and settles the account with the recruiter. This order is marked as completed and entered into the database. This order will be merged with the data portrait made by the platform according to the job seeker before, and a new data portrait will be integrated. In the subsequent automatic matching, the latest data portrait will be used as the blueprint.
5. The method of claim 3, wherein the method further comprises: In the case of the job seeker choosing to manually match zero work, the platform will list the zero work list published by the recruiter, and then the job seeker needs to choose to match the order according to his own requirements. The platform will send a notice to the successful matching of the recruiter and the job seeker. After that, the job seeker completes the service required by the recruiter and settles the account with the recruiter. This order is marked as completed and entered into the database. This order will be merged with the data portrait made by the platform according to the job seeker before, and a new data portrait will be integrated. In the subsequent automatic matching, the latest data portrait will be used as the blueprint.
6. The method of claim 1, wherein: After the platform makes a data portrait according to the job seeker's order acceptance, its data will be included in the platform's total data, so as to be merged with the recruiter's required priority data, so that the platform can more intelligently push orders.
7. The method of claim 1, wherein the method is based on user demand priority. The recruiter is the one who publishes zero work, and after completing the matching, he is the employer of the job seeker. When the recruiter publishes zero work to the platform, he can adjust the priority of the job seeker's own age, health condition, skills, work expectations, work time requirements, work location requirements, settlement method, start and end time, etc.