CN109583617A - A kind of dissemination method of crowdsourcing task - Google Patents
A kind of dissemination method of crowdsourcing task Download PDFInfo
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- CN109583617A CN109583617A CN201811460110.0A CN201811460110A CN109583617A CN 109583617 A CN109583617 A CN 109583617A CN 201811460110 A CN201811460110 A CN 201811460110A CN 109583617 A CN109583617 A CN 109583617A
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Abstract
The invention discloses a kind of crowdsourcing task dissemination methods, crowdsourcing platform is submitted into crowdsourcing to be treated work in the form of a series of crowdsourcing workflow comprising crowdsourcing tasks requestor, crowdsourcing platform sends the task in crowdsourcing workflow to task delivery system；Task delivery system optimizes processing to the parameters of task in workflow, and crowdsourcing worker reserves according to mission bit stream and self-condition and executes some task in crowdsourcing workflow, finally after crowdsourcing worker completes corresponding task, result is fed back into crowdsourcing platform, crowdsourcing platform merges the completion of each task in crowdsourcing workflow as a result, and will be finally completed result and feed back to requestor.The present invention is optimized by constraint solving or heuristic to each property parameters of task and the judgement to task publication condition, improves the completion quality of crowdsourcing workflow, shortens and complete the time used in workflow, improve work efficiency.
Description
Technical field
The present invention relates to a kind of crowdsourcing task dissemination method, the determination side of task parameters in especially a kind of crowdsourcing task publication
Method.
Background technique
Currently, more complicated crowdsourcing work can generally be split as multiple subtasks and with crowdsourcing in crowdsourcing environment
The form of workflow handles them.Each workflow can be regarded as a directed acyclic graph, each height therein
Task is distributed on crowdsourcing platform according to its successive and cosequence and is executed by crowdsourcing worker.And each crowd in crowdsourcing workflow
The setting of the parameters such as reward, time when packet task is published will affect crowdsourcing workflow and correspond to being performed integrally for crowdsourcing work
Quality (complete cost, complete overdue situation etc.).
In this regard, the optimal value of the task parameters in crowdsourcing task RELEASE PROBLEM is determined that problem specification is by first technology
It is each to find it by objective function and constraint condition for the value of task parameters for the constraint solving problem of one quadratic programming
From globally optimal solution, with promoted crowdsourcing work be performed integrally effect.Its secondary plan constraint method for solving can pass through about
Beam solver is realized, and available more accurate global optimum's result.But it is only carried out to a small number of crowdsourcing workflows
It when optimization, can complete to solve in the acceptable time range of crowdsourcing environment, with the increase of amount of constraint, optimizing the time will
It is exponentially increased.In addition, we have found after testing, asking when some constraint solvers can only quickly cope with small-scale
Topic, can not handle extensive problem within the acceptable time.When number of tasks amount becomes larger, when not only needing more to execute
Between, but also need more storage allocations.
And in the crowdsourcing environment of reality, after task is distributed on crowdsourcing platform by demander, it is often desired to which task is most
Received and completed by worker fastly.If parametric solution this during expend the long time if, it will influence whole work
Make process, also reduces working efficiency.
Summary of the invention
In view of the above-mentioned problems, the invention proposes the optimal value determination sides of the task parameters in a kind of publication of crowdsourcing task
Method is analyzed by the daily record data for completing task to crowdsourcing platform, determine in crowdsourcing workflow each attribute of crowdsourcing task it
Between relationship, and then each property parameters of task are optimized by constraint solving or heuristic.
The technical scheme of the present invention is realized as follows:
A kind of crowdsourcing task dissemination method, comprising the following steps:
Crowdsourcing to be treated is worked and is mentioned in the form of a series of crowdsourcing workflow comprising crowdsourcing tasks by S1, requestor
Crowdsourcing platform is given, crowdsourcing platform sends the task in crowdsourcing workflow to task delivery system；
S2, task delivery system optimize processing, the task delivery system to the parameters of task in workflow
Including data analysis module, task parameters optimization module and task release module；
S3, task delivery system are sent out according to the task publication condition of task parameters and the setting of crowdsourcing platform after optimization processing
Cloth task, and mission bit stream is shown to crowdsourcing worker；
S4, crowdsourcing worker reserve according to mission bit stream and self-condition and execute some task in crowdsourcing workflow；
Result after crowdsourcing worker completes corresponding task, is fed back to crowdsourcing platform, crowdsourcing platform merges crowdsourcing workflow by S5
In each task completion as a result, and result will be finally completed feeding back to requestor.
Further, data analysis module described in step S2 is responsible for the information of crowdsourcing worker on crowdsourcing platform and complete
At task history work statistical information analyzed and handled, the module complete three main functions be respectively as follows: to appoint
Business, worker and Work stream data model, and determine the value range of each task parameters and determine the cost of completion task
The coefficient value of objective function.
Further, the statistical information of the history work includes at least: the type of task, when the distribution of task waits
Between, the reservation waiting time of task and task remuneration；The information of the crowdsourcing worker includes at least: each crowdsourcing worker's is unique
ID, worker is acceptable to complete some task given minimum distribution time and acceptable minimum remuneration.
Further, optimal value solution side of the task parameters optimization module described in step S2 to crowdsourcing task parameters
Method is divided into following two categories:
It is a quadratic programming (quadratic by the problem specification when algorithm workflow negligible amounts to be processed
Programming, QP) problem solved, and the objective function of this QP problem is to make to complete all tasks in crowdsourcing workflow
Totle drilling cost is minimum, i.e., the sum of remuneration of worker minimum is paid after the completion of all tasks；Including two added to the time
Class constraint, the constraint of the 1st class adds constraint to the distribution time of all tasks on all paths, when ensure that the distribution of each task
Between length not will cause final overdue, even longest path, can also be protected in time；2nd class is constrained to institute
When having the distribution for not having started all follow-up works for receiving to handle or on issued task and its place path at present
Between and subscription time addition constraint, this kind of constraint, which ensure that, to be caused final overdue because the reservation waiting time is too long；
When workflow quantity is more, parametric solution is carried out using heuristic strategies, the heuristic strategies include four
Kind, every kind of emphasis is different, is respectively as follows:
Strategy 1, the distribution time of task and subscription time are minimum on the most path of task in workflow, other tasks with
Machine determines the value of distribution time and subscription time；
Strategy 2, the distribution time of task and subscription time are maximum on the least path of task in workflow, other tasks with
Machine determines the value of distribution time and subscription time；
Strategy 3 is directly the smallest value for distributing the time in the desirable range of all task choosings, in subscription time selection
Value；
Strategy 4, the distribution time of task and subscription time are set as to make connect after it is published on platform
By the most value of worker's number of task.
Further, task release module described in step S2, which passes through, judges whether the parameter of current task setting meets crowd
The task of packet platform setting issues condition, determines whether the task is issued；The condition of the task publication includes two, first
It is that task of the task in workflow before present position has been fully completed, Article 2 is that the parameter of task setting will not be made
It is overdue at workflow；When the task while meeting above-mentioned two condition, which is issued by task delivery system；If be unsatisfactory for
First, task needs that its all task previous is waited to be fully completed；If being unsatisfactory for Article 2, task needs, which again pass by, appoints
Parameter optimization module of being engaged in solves, and will solve obtained new optimal value and is arranged to the parameters of task, guarantees each of task
Parameter setting not will cause overdue.
The beneficial effects of the present invention are: it is analyzed, is determined many by the daily record data for completing task to crowdsourcing platform
Relationship in packet workflow between each attribute of crowdsourcing task, and then each attribute of task is joined by constraint solving or heuristic
Number optimizes and the judgement to task publication condition, improves the completion quality of crowdsourcing workflow, shortens and complete work
The time used is flowed, is improved work efficiency.
Detailed description of the invention
Fig. 1 is the dissemination method flow chart of crowdsourcing task of the present invention.
Specific embodiment
The specific embodiment of the invention is described in detail with reference to the accompanying drawing:
As shown in Figure 1, a kind of crowdsourcing task dissemination method, comprising the following steps:
Crowdsourcing to be treated is worked and is mentioned in the form of a series of crowdsourcing workflow comprising crowdsourcing tasks by S1, requestor
Crowdsourcing platform is given, crowdsourcing platform sends the task in crowdsourcing workflow to task delivery system；
S2, task delivery system optimize processing, the task delivery system to the parameters of task in workflow
Including data analysis module, task parameters optimization module and task release module；
S3, task delivery system are sent out according to the task publication condition of task parameters and the setting of crowdsourcing platform after optimization processing
Cloth task, and mission bit stream is shown to crowdsourcing worker；
S4, crowdsourcing worker reserve according to mission bit stream and self-condition and execute some task in crowdsourcing workflow；
Result after crowdsourcing worker completes corresponding task, is fed back to crowdsourcing platform, crowdsourcing platform merges crowdsourcing workflow by S5
In each task completion as a result, and result will be finally completed feeding back to requestor.
Further, data analysis module described in step S2 is responsible for the information of crowdsourcing worker on crowdsourcing platform and complete
At task history work statistical information analyzed and handled, the module complete three main functions be respectively as follows: to appoint
Business, worker and Work stream data model, and determine the value range of each task parameters and determine the cost of completion task
The coefficient value of objective function.
Further, the statistical information of the history work includes at least: the type of task, when the distribution of task waits
Between, the reservation waiting time of task and task remuneration；The information of the crowdsourcing worker includes at least: each crowdsourcing worker's is unique
ID, worker is acceptable to complete some task given minimum distribution time and acceptable minimum remuneration.
Further, optimal value solution side of the task parameters optimization module described in step S2 to crowdsourcing task parameters
Method is divided into following two categories:
It is a quadratic programming (quadratic by the problem specification when algorithm workflow negligible amounts to be processed
Programming, QP) problem solved, and the objective function of this QP problem is to make to complete all tasks in crowdsourcing workflow
Totle drilling cost is minimum, i.e., the sum of remuneration of worker minimum is paid after the completion of all tasks；Including two added to the time
Class constraint, the constraint of the 1st class adds constraint to the distribution time of all tasks on all paths, when ensure that the distribution of each task
Between length not will cause final overdue, even longest path, can also be protected in time；2nd class is constrained to institute
When having the distribution for not having started all follow-up works for receiving to handle or on issued task and its place path at present
Between and subscription time addition constraint, this kind of constraint, which ensure that, to be caused final overdue because the reservation waiting time is too long；
When workflow quantity is more, parametric solution is carried out using heuristic strategies, the heuristic strategies include four
Kind, every kind of emphasis is different, is respectively as follows:
Strategy 1, the distribution time of task and subscription time are minimum on the most path of task in workflow, other tasks with
Machine determines the value of distribution time and subscription time；
Strategy 2, the distribution time of task and subscription time are maximum on the least path of task in workflow, other tasks with
Machine determines the value of distribution time and subscription time；
Strategy 3 is directly the smallest value for distributing the time in the desirable range of all task choosings, in subscription time selection
Value；
Strategy 4, the distribution time of task and subscription time are set as to make connect after it is published on platform
By the most value of worker's number of task.
Further, task release module described in step S2, which passes through, judges whether the parameter of current task setting meets crowd
The task of packet platform setting issues condition, determines whether the task is issued；The condition of the task publication includes two, first
It is that task of the task in workflow before present position has been fully completed, Article 2 is that the parameter of task setting will not be made
It is overdue at workflow；When the task while meeting above-mentioned two condition, which is issued by task delivery system；If be unsatisfactory for
First, task needs that its all task previous is waited to be fully completed；If being unsatisfactory for Article 2, task needs, which again pass by, appoints
Parameter optimization module of being engaged in solves, and will solve obtained new optimal value and is arranged to the parameters of task, guarantees each of task
Parameter setting not will cause overdue.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (5)
1. a kind of crowdsourcing task dissemination method, it is characterised in that: the following steps are included:
Crowdsourcing to be treated is worked and is submitted in the form of a series of crowdsourcing workflow comprising crowdsourcing tasks by S1, requestor
Crowdsourcing platform, crowdsourcing platform send the task in crowdsourcing workflow to task delivery system；
S2, task delivery system optimize processing to the parameters of task in workflow, and the task delivery system includes
Data analysis module, task parameters optimization module and task release module；
S3, task delivery system are appointed according to the task publication condition publication of the task parameters and the setting of crowdsourcing platform after optimization processing
Business, and mission bit stream is shown to crowdsourcing worker；
S4, crowdsourcing worker reserve according to mission bit stream and self-condition and execute some task in crowdsourcing workflow；
Result after crowdsourcing worker completes corresponding task, is fed back to crowdsourcing platform, crowdsourcing platform merges each in crowdsourcing workflow by S5
The completion of task will be as a result, and will be finally completed result and feed back to requestor.
2. according to the method described in claim 1, it is characterized by: data analysis module described in step S2 is responsible for putting down crowdsourcing
The information of crowdsourcing worker and the statistical information of the history work for the task that is completed are analyzed and are handled on platform, which completes three
A main function, which is respectively as follows:, models task, worker and Work stream data, determines the value model of each task parameters
Enclose and determine completion task cost objective function coefficient value.
3. method according to claim 2, which is characterized in that the statistical information of the history work includes at least: task
Type, the distribution waiting time of task, the reservation waiting time of task and task remuneration；The information of the crowdsourcing worker is at least wrapped
Include: unique ID of each crowdsourcing worker, worker is acceptable to complete some task given minimum distribution time and acceptable
Minimum remuneration.
4. according to the method described in claim 1, it is characterized by: task parameters optimization module described in step S2 appoints crowdsourcing
The optimal value method for solving of business parameters is divided into following two categories:
It is a quadratic programming (quadratic by the problem specification when algorithm workflow negligible amounts to be processed
Programming, QP) problem solved, and the objective function of this QP problem is to make to complete all tasks in crowdsourcing workflow
Totle drilling cost is minimum, i.e., the sum of remuneration of worker minimum is paid after the completion of all tasks；Including two added to the time
Class constraint, the constraint of the 1st class adds constraint to the distribution time of all tasks on all paths, when ensure that the distribution of each task
Between length not will cause final overdue, even longest path, can also be protected in time；2nd class is constrained to institute
When having the distribution for not having started all follow-up works for receiving to handle or on issued task and its place path at present
Between and subscription time addition constraint, this kind of constraint, which ensure that, to be caused final overdue because the reservation waiting time is too long；
When workflow quantity is more, parametric solution is carried out using heuristic strategies, the heuristic strategies include four kinds, often
The emphasis of kind is different, is respectively as follows:
Strategy 1, the distribution time of task and subscription time are minimum on the most path of task in workflow, other tasks are true at random
Surely the value of time and subscription time are distributed；
Strategy 2, the distribution time of task and subscription time are maximum on the least path of task in workflow, other tasks are true at random
Surely the value of time and subscription time are distributed；
Strategy 3, can use the value of the smallest distribution time in range directly for all task choosings, and subscription time selects intermediate value；
The distribution time of task and subscription time are set as to make receive after it is published on platform to appoint by strategy 4
The most value of worker's number of business.
5. according to the method described in claim 1, it is characterized by: task release module described in step S2 is current by judgement
Whether the parameter of task setting meets the task publication condition of crowdsourcing platform setting, determines whether the task is issued；The task
The condition of publication includes two, and first is that task of the task in workflow before present position has been fully completed, and second
Item is that not will cause workflow overdue for the parameter of task setting；When the task while meeting above-mentioned two condition, is sent out by task
Distribution system issues the task；If being unsatisfactory for first, task needs that its all task previous is waited to be fully completed；If discontented
Sufficient Article 2, task need to again pass by the solution of task parameters optimization module, will solve obtained new optimal value and be arranged to appointing
It is overdue to guarantee that the parameters setting of task not will cause for the parameters of business.
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Cited By (3)
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| CN111429104A (en) * | 2020-04-03 | 2020-07-17 | 青岛大学 | Crowdsourcing item execution device, method, equipment and readable storage medium |
| CN112000316A (en) * | 2020-08-25 | 2020-11-27 | 橙色云设计有限公司 | Full-factor open type collaborative research and development system and method |
| CN113128897A (en) * | 2021-04-30 | 2021-07-16 | 平安国际融资租赁有限公司 | Crowdsourcing task resource configuration method and device, electronic equipment and storage medium |
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