CN111309459A - Working platform for service resource pre-scheduling - Google Patents
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Abstract
The invention provides a working platform for service resource pre-scheduling, which is characterized by comprising a primary matching module, a secondary matching module and a scheduling module, wherein the primary matching module is used for adjusting the skill range of a packet receiver according to a predefined scheduling strategy; the secondary matching module is used for predicting task requirements, determining a skill range required by the task requirements and generating a predefined scheduling strategy according to the predicted task requirements; the third-stage matching module is used for confirming the packet receiving party and the packet sending party which receive the predefined scheduling strategy, and according to the confirmed task list and the packet receiving party to be distributed; the task selection module is used for acquiring a target task from the task list based on the adjusted skill range of the to-be-distributed packet receiver; and the task sending module is used for sending the target task to the packet receiving party to be distributed. The invention aims to provide a working platform for service resource pre-scheduling aiming at the defects of the prior art, and the working platform is used for allocating service resources to the field with larger service requirements, so that the waste of the service resources is reduced, and the service efficiency is improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a working platform for service resource pre-scheduling.
Background
The work platform is an internet platform which provides various work management related services in a crowdsourcing mode. The packet sender issues work task requirements to a work platform, the platform decomposes the tasks, searches matched packet receivers from a platform talent library according to the skill requirements of each subtask, and distributes the subtasks to the proper packet receivers; the packet receiving party starts working after receiving the assigned subtasks, and submits working results to the platform after the subtasks are completed; and the packet sender and the packet receiver receive the task delivery result and examine the task delivery result. When the packet sender issues the tasks, the task cost is managed on the platform, and after the tasks are delivered and accepted, the platform and the packet receiver settle accounts.
In the operation process of the working platform, the influence of certain phenomena, such as sales promotion of merchants, festival celebration and other activities, often causes a large number of tasks to be issued on the working platform in a short period, and relatively, the number of the bag receiving parties is insufficient, so that the task queue to be distributed is easy to overlong. At this time, if the task allocation is carried out according to the conventional strategy, the packet receiving party with the critical skill can not be dispatched in time, so that the efficiency of platform task allocation and completion is reduced on one hand, and the idle waiting time of part of the packet receiving party is prolonged on the other hand.
Disclosure of Invention
The invention aims to provide a working platform for service resource pre-scheduling aiming at the defects of the prior art, and the working platform is used for allocating service resources to the field with larger service requirements, so that the waste of the service resources is reduced, and the service efficiency is improved.
The invention provides a working platform for service resource pre-scheduling, which is characterized by comprising a primary matching module, a secondary matching module, a tertiary matching module, a task selection module and a task sending module,
the primary matching module is used for adjusting the skill range of the packet receiving party according to a predefined scheduling strategy;
the secondary matching module is used for predicting task requirements, determining a skill range required by the task requirements and generating a predefined scheduling strategy according to the predicted task requirements;
the third-stage matching module is used for confirming the packet receiving party and the packet sending party which receive the predefined scheduling strategy, and according to the confirmed task list and the packet receiving party to be distributed;
the task selection module is used for acquiring a target task from the task list based on the adjusted skill range of the to-be-distributed packet receiver;
and the task sending module is used for sending the target task to the packet receiving party to be distributed.
In the above technical solution, the primary matching module is configured to obtain skill information of the package receiving party, determine a service type to which the package receiving party belongs based on the skill information, and determine a skill range of the package receiving party in the service type.
In the technical scheme, the task selection module is configured to acquire a skill range required by the task in the task list, judge whether the skill range is included in a skill range of a receiver, and judge that the task is a target task which is to be marked as the receiver.
In the technical scheme, the secondary matching module is used for acquiring industry information, analyzing possible events, predicting task demand activities in advance according to the events and determining skill ranges of the tasks; the second-level matching module is preset with a corresponding skill range of the task demand activity.
In the above technical solution, the third-stage matching module is configured to initiate a query to a packet sender and a packet receiver associated with the predicted task demand, determine that the queried packet receiver is the packet receiver under a predefined scheduling policy, determine that the queried packet sender is the packet sender in the predefined scheduling policy, and generate the task in the task list.
In the technical scheme, the third-level matching module is used for acquiring and judging the skill range of the packet receiver, and if the skill range of the packet receiver is within the skill range required by the predicted task requirement, the packet receiver is determined to be under the predefined scheduling strategy; the third-level matching module is used for acquiring tasks issued by the packet issuing party, determining the packet issuing party to be the packet issuing party in the predefined scheduling policy if the tasks issued by the packet issuing party are within the predicted task demand skill range, and determining the tasks issued by the packet issuing party to be the tasks in the predefined scheduling policy.
The technical scheme comprises a task receiving terminal, a task issuing terminal and a server, wherein the contracting party issues skill information through the task receiving terminal and receives a target task; the primary matching module, the secondary matching module, the tertiary matching module, the task selection module and the task sending module are integrated in a server, and the server is used for setting a predefined scheduling strategy; and the packet sending party issues the tasks through the task issuing terminal.
In the technical scheme, the task selection module analyzes all tasks to be distributed, and can distribute two or more candidate tasks of a packet receiver based on the skill requirement of each task; and selecting a target task from the candidate tasks to send to the packet receiver.
In the technical scheme, among the at least two candidate tasks, the task with the skill range closest to the subcontractor is selected as the target task, or the task with the skill range same as that of the subcontractor is selected as the target task, or the target task is randomly selected from the at least two candidate tasks.
The invention collects market and industry information in real time, predicts the service requirements which may be generated, and selects a proper scheduling strategy according to different scenes or conditions so as to optimize the task allocation process aiming at certain scenes or conditions. And determining a packet sending party and a packet receiving party under a scheduling strategy according to the predicted task requirements, so as to meet the requirements of both a supply party and a demand party. The invention preferentially distinguishes tasks which need to be solved urgently and skills which are needed by the tasks correspondingly according to the requirements of the packet sender, and reduces the range of the packet receiver according to the needed skills. The invention can adjust the skill range of the packet receiving party in advance by predicting the demand characteristics of the potential tasks, so that the predicted tasks can be quickly matched with the proper packet receiving party when being issued, thereby improving the scheduling efficiency of platform service resources and simultaneously improving the utilization rate of the service resources.
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FIG. 1 is a schematic of the present invention;
fig. 2 is a schematic diagram of the application of the present invention.
Detailed Description
The invention will be further described in detail with reference to the following drawings and specific examples, which are not intended to limit the invention, but are for clear understanding.
As shown in FIG. 1, the present invention provides a working platform for service resource pre-scheduling, which is characterized in that it comprises a primary matching module, a secondary matching module, a tertiary matching module, a task selection module and a task transmission module,
the primary matching module is used for adjusting the skill range of the packet receiving party according to a predefined scheduling strategy;
the secondary matching module is used for predicting task requirements, determining a skill range required by the task requirements and generating a predefined scheduling strategy according to the predicted task requirements;
the third-stage matching module is used for confirming the packet receiving party and the packet sending party which receive the predefined scheduling strategy, and according to the confirmed task list and the packet receiving party to be distributed;
the task selection module is used for acquiring a target task from the task list based on the adjusted skill range of the to-be-distributed packet receiver;
and the task sending module is used for sending the target task to the packet receiving party to be distributed.
In the above technical solution, the primary matching module is configured to obtain skill information of the package receiving party, determine a service type to which the package receiving party belongs based on the skill information, and determine a skill range of the package receiving party in the service type. In some embodiments, the recipient is a user who receives and completes a task. For example, the package receiver may be a designer (in an industrial design business scenario), an engineer (in a software development business scenario), or the like. The contracting party in one scenario may be the issuing party, or a user in the role of another engineer (in a software development business scenario) in another scenario, and the application should not be limited in this respect. In some embodiments, the skill scope may be professional, functional, or any technical field, and may contain all skills that may provide business services. In some embodiments, a traffic type may include one or more skill ranges over a certain time period. The skill range of any particular contracting party within the service type may be determined by the skills of the contracting party. Specifically, skill information of the contracting party can be acquired, and then the service type to which the contracting party belongs can be determined. The skill range of the contracting party may then be determined within the service type.
In the technical scheme, the secondary matching module is used for acquiring industry information, analyzing possible events, predicting task demand activities in advance according to the events and determining skill ranges of the tasks; the second-level matching module is preset with a corresponding skill range of the task demand activity. In one embodiment, a business activity (e.g., a mall promotion, etc.) may be obtained to determine whether a task-requiring activity (e.g., an activity web page development, etc.) is about to occur. In another embodiment, bulk transaction information for an industry may be obtained to determine if an industrial design task demand activity is about to occur. It should be understood that the task need activity can also be predicted by other means, and the application is not limited to particular aspects of the predicted task need activity.
Once the task demanding activity is predicted, the next is to determine the skill range required by the task demanding activity. Different task-demanding activities may correspond to different methods for determining their corresponding skill ranges. These methods may be designed and stored on the terminal/server. When a specific task demanding activity is predicted, the terminal/server may first determine which task demanding activity it is, and then find the corresponding method to determine the range of skills that may be required by the specific task demanding activity.
For example, if the task-requiring activity is predicted to be a mall promotion, the terminal/server may determine that the area of influential skill is being developed for a web page. In one approach, the skill range of a mall promotion may be set to web page design and web page development. Based on this approach, the terminal/server may search for skill ranges for the task needs activity, e.g., based on whether the predictions are obtained online, and set these skill ranges as required for the task needs activity. In another example, if the task demand activity is predicted to be a block transaction, the terminal/server may determine a skill range of the block transaction impact. In one approach, an industry association index may be defined to indicate how close an industry association is. Those skilled in the art will appreciate that there are many ways to obtain business information, for example, from an information application on a terminal or server, or from an online information application, a business report. In one embodiment, a software application on a terminal or server executing the methods of the present application may generate its own industry information based on information it collects from users of the software application. It should be understood that the skill range of the task needs activity may also be determined by other means, and the application is not limited to a particular manner of determining the skill range of the task needs activity.
In the technical scheme, the third-level matching module can determine the task and the packet receiver under the predefined scheduling strategy based on the skill range of task demand activities. When a task demand activity occurs, the demand condition within the relevant business type may be affected. Thus, a predefined scheduling policy may be opened within the relevant traffic type. By allocating tasks under a predefined scheduling policy, the task allocation process can be optimized when task demand activities occur.
In one embodiment, the location of the contracting party may be obtained and used to determine whether the contracting party is within the required skill range. The contracting party whose location is within the required skill range may be determined as the contracting party under the predefined scheduling policy. Meanwhile, the task requirement of the contracting party can be obtained and used for determining whether the task requirement of the contracting party is in a required skill range. The contracting parties with task requirements in the required skill range may be determined as contracting parties in a predefined scheduling policy. Thus, a task from a subcontractor in the predefined scheduling policy may be determined as a task in the predefined scheduling policy.
In another embodiment, the server may issue a query to the contracting party and the issuing party whose task requirements are within the required skill range. For example, the query may be "do you agree to take over tasks according to a predefined scheduling policy? "the receiver of the confirmed query is determined as the receiver under the predefined scheduling policy. Similarly, the task of the originator of the validation query is determined to be a task in the predefined scheduling policy.
In the above technical solution, the task selection module is configured to obtain a task issued by a packet sender, and perform task screening according to a predefined scheduling policy to generate a task list to be allocated. In some embodiments, tasks to be allocated according to a predefined scheduling policy may refer to tasks issued by a contracting party. The contracting party is the publishing task, i.e. the user requesting the service. For example, the contracting party may be a device purchaser (in an industrial design business scenario) or may be a customer with software requirements (in a software development scenario), and so forth. The contracting party in one scenario may be the receiving party, or a user of another role in other scenarios, and the application should not be limited in this respect.
In the technical scheme, the task selection module is configured to acquire the professional skills corresponding to the task to be distributed, judge whether the professional skills are included in the skill range of the packet receiver, and judge that the task is the target task which is marked as the packet receiver.
Typically, for crowd-sourced services, the task typically includes required expertise. Thus, the type of traffic that the contracting party (i.e., the service provider) can provide the service should at least cover the expertise during the service provisioning process. In other words, the expertise of the task sent to the subcontractor should be contained within the skill range of the subcontractor.
First, the tasks to be assigned may be analyzed and their corresponding expertise may be obtained. If the professional skills are all within the skill range of the subcontractor, the task may be considered a candidate task for the subcontractor. Similarly, all tasks to be assigned may be analyzed, and two or more candidate tasks for the subcontractor may be obtained based on the skill requirements of each task. Next, among the at least two candidate tasks, a target task may be selected to send to the subcontractor.
To select the target task, any reasonable method may be used. In one embodiment, the target task may be selected by the skill closest to the party to the package. In other words, among the at least two candidate tasks, the task whose skill requires the closest subcontractor is selected as the target task. In another embodiment, a candidate task may be selected as the target task if the skill range of the candidate task is the same as the skill range of the subcontractor. In another embodiment, the target task may be randomly selected from at least two candidate tasks. It should be appreciated that any other reasonable means or rule may be used to select a target task from the candidate tasks, and the application is not limited to a particular manner of determining a target task from the candidate tasks.
As shown in fig. 2, the technical solution further includes a task receiving terminal, a task issuing terminal, and a server, where the receiving party issues skill information and receives a target task through the task receiving terminal; the primary matching module, the task selection module and the task sending module are integrated in a server, and the server is used for setting a predefined scheduling strategy; and the packet sending party issues the tasks through the task issuing terminal. The task receiving terminal and the task issuing terminal can include, but are not limited to, mobile terminals such as smart phones, smart wearable devices, tablet computers, personal digital assistants and the like.
The task receiving terminal, the task issuing terminal, and the like may be provided with a crowdsourcing service client application (e.g., an industrial design application, a software development application, and the like). The identity of the account in the crowdsourcing service client application used for login may be configured as an identity of the service (e.g., designer, engineer, etc.). Thus, the user of the terminal may be configured as a contracting party or a transmitting party. When the service client application detects that a predefined scheduling policy is enforced, it may first determine the skill range of the user of the terminal, i.e. the skill range of the recipient. Next, based on the skill range, a target task may be obtained from the candidate tasks in the predefined scheduling policy. Then, the target task is transmitted to a user of the terminal (i.e., the recipient), and information of the target task may be displayed on a screen of the terminal.
The server may be a server capable of providing crowdsourced services to clients, such as an industrial design application, a software development application, and the like. The server can detect the packet sender and the packet receiver under a predefined scheduling policy. First, the server determines the skill range of each contracting party. And then, the server acquires the target task of each packet receiver from the tasks to be distributed according to a predefined scheduling strategy based on the determined skill range of each packet receiver. The target task may then be sent to the corresponding recipient. And the server determines a task list according to the task requirement issued by the packet receiving party.
In the above technical solution, the predefined scheduling policy is a policy for allocating tasks according to a predefined rule. In general, there may be at least two ways to assign tasks to the receiver, and an appropriate scheduling policy may be selected according to different scenarios or conditions to optimize the task assignment process for certain scenarios or conditions. For example, when a certain demand activity is predicted, a policy matching the demand activity may be selected to optimize task allocation.
Details not described in this specification are within the skill of the art that are well known to those skilled in the art.
Claims (9)
1. A working platform for service resource pre-scheduling is characterized by comprising a primary matching module, a secondary matching module, a tertiary matching module, a task selection module and a task sending module,
the primary matching module is used for adjusting the skill range of the packet receiving party according to a predefined scheduling strategy;
the secondary matching module is used for predicting task requirements, determining a skill range required by the task requirements and generating a predefined scheduling strategy according to the predicted task requirements;
the third-stage matching module is used for confirming the packet receiving party and the packet sending party which receive the predefined scheduling strategy, and according to the confirmed task list and the packet receiving party to be distributed;
the task selection module is used for acquiring a target task from the task list based on the adjusted skill range of the to-be-distributed packet receiver;
and the task sending module is used for sending the target task to the packet receiving party to be distributed.
2. The work platform for prescheduling service resources as recited in claim 1, wherein the primary matching module is configured to obtain skill information of the contracting party and determine a service type to which the contracting party belongs, and determine a skill range of the contracting party within the service type.
3. The work platform for prescheduling service resources as recited in claim 2, wherein the task selection module is configured to obtain a skill range required by the task in the task list and determine whether the skill range is included in the skill range of the subcontractor, and determine that the task is a target task for marking the task as the subcontractor.
4. The work platform for pre-scheduling of service resources as claimed in claim 3, wherein the secondary matching module is configured to obtain industry information and analyze events that may occur, predict task demand activity in advance according to the events, and determine skill ranges thereof; the second-level matching module is preset with a corresponding skill range of the task demand activity.
5. The work platform for pre-scheduling of service resources according to claim 4, wherein the tertiary matching module is configured to initiate a query to the associated chartered parties and the chartered parties of the predicted task requirements, the chartered party confirming the query is determined to be the chartered party under the predefined scheduling policy, the chartered party confirming the query is determined to be the chartered party in the predefined scheduling policy, and the tasks thereof are generated in the task list.
6. The work platform for service resource pre-scheduling according to claim 4, wherein the third-level matching module is configured to obtain and judge a skill range of the contracting party, and if the skill range of the contracting party is within a skill range required by the predicted task requirement, the contracting party is determined to be under a predefined scheduling policy; the third-level matching module is used for acquiring tasks issued by the packet issuing party, determining the packet issuing party to be the packet issuing party in the predefined scheduling policy if the tasks issued by the packet issuing party are within the predicted task demand skill range, and determining the tasks issued by the packet issuing party to be the tasks in the predefined scheduling policy.
7. The working platform for prescheduling service resources according to claim 1, further comprising a task receiving terminal, a task issuing terminal and a server, wherein the contracting party issues skill information and receives a target task through the task receiving terminal; the primary matching module, the secondary matching module, the tertiary matching module, the task selection module and the task sending module are integrated in a server, and the server is used for setting a predefined scheduling strategy; and the packet sending party issues the tasks through the task issuing terminal.
8. The work platform for prescheduling of service resources as claimed in claim 1, wherein the task selection module analyzes all tasks to be assigned and may assign two or more candidate tasks to the contracting party based on the skill requirements of each task; and selecting a target task from the candidate tasks to send to the packet receiver.
9. The work platform for pre-scheduling of service resources according to claim 7, wherein among the at least two candidate tasks, the task with the skill range closest to the skill range of the contracting party is selected as the target task or the task with the skill range of the candidate task identical to the skill range of the contracting party is selected as the target task or the target task is randomly selected from the at least two candidate tasks.
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