CN108052376A - The multiple spot packaging method and system of mobile platform crowdsourcing task - Google Patents
The multiple spot packaging method and system of mobile platform crowdsourcing task Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
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Abstract
The invention discloses the multiple spot packaging methods and system of mobile platform crowdsourcing task, comprise the following steps：Step (1)：The preparation that task is packaged：The crowdsourcing mission bit stream of labor service crowdsourcing platform and the information of mission requirements person are gathered, crowdsourcing mission bit stream is visualized and pre-processed；Step (2)：The data collected are analyzed, the influence factor that analyzing influence mobile platform crowdsourcing task is packaged.Step (3)：Determine multiple spot task packaging method：The influence factor that being obtained according to step (2) for task is packaged determines that multiple spot task is packaged condition, carries out task packing.Step (4)：Multiple spot task packaging method is tested and assessed.According to the method for step (3), multiple spot task packing is carried out to the data that step (1) obtains.
Description
Technical field
The invention belongs to the technical field of network data excavation more particularly to the multiple spot packing sides of mobile platform crowdsourcing task
Method and system.
Background technology
Self-service labor service crowdsourcing platform based on mobile Internet provides various business inspections and information search clothes for enterprise
Business, research cost can be greatlyd save compared to traditional market survey mode, and is effectively guaranteed survey data authenticity,
Shorten the cycle of investigation.And the key element that can platform effectively operate is task price.There are many factor of influence task price,
When concentration is compared in the position of task, multiple tasks are united packing and issuing, a simple task is possibly converting to
Wholesale task can not only save substantial amounts of resource, time and cost, and can reduce task and overstock, and accelerate task complete
Into.Therefore, rational packaging method is designed, is of great significance to the task price of mobile Internet labor service crowdsourcing platform.
In conclusion existing mobile Internet labor service crowdsourcing platform is fixed a price using single task, multitask is not accounted for
The influence to price is packaged, also without a kind of practicable crowdsourcing task packing scheme.How to determine that effective task is packaged
Method still lacks effective solution.
The content of the invention
The present invention is to solve the above-mentioned problems, it is proposed that a kind of multiple spot packaging method of mobile platform crowdsourcing task and is
System.The influence factor that present invention analysis multiple spot task is packaged, the feasible distance of the distance between task and mission requirements person are made
The foundation being packaged for task；It determines packing condition, multiple spot packing is carried out to qualified task；After calculating the packing of multiple spot task
Price coefficient, as adjustment mobile platform crowdsourcing task price parameter.
To achieve these goals, the present invention adopts the following technical scheme that：
The multiple spot packaging method of mobile platform crowdsourcing task, comprises the following steps：
Step (1)：The preparation that task is packaged：Gather crowdsourcing mission bit stream and the mission requirements person of labor service crowdsourcing platform
Information, crowdsourcing mission bit stream is visualized and pre-processed；
Step (2)：The data collected are analyzed, analyzing influence mobile platform crowdsourcing task be packaged influence because
Element；
Step (3)：Determine multiple spot task packaging method：The influence factor that being obtained according to step (2) for task is packaged, determines
Multiple spot task is packaged condition, carries out task packing；
Step (4)：According to the method for step (3), multiple spot task packing is carried out to the data that step (1) obtains.
The crowdsourcing mission bit stream, including：Crowdsourcing mission number, crowdsourcing task price, the longitude and latitude of crowdsourcing task and crowd
The implementation status of bag task.
The information of the mission requirements person, including：The position longitude and latitude of mission requirements person, the task of mission requirements person are got
Amount, the credit value of mission requirements person.
In the step (1), crowdsourcing mission bit stream is visualized and pre-processed：
Step (1-1)：According to the crowdsourcing mission bit stream of acquisition, extraction task price draws histogram according to different prices,
Visualization processing is carried out, obtains task price distribution map；
Step (1-2)：Coarse localization is carried out according to the longitude and latitude of crowdsourcing task, the city position of crowdsourcing task is visual
Change；
Step (1-3)：Finely positioning is carried out according to the longitude and latitude of crowdsourcing task, the counties and districts position of crowdsourcing task is visual
Change, obtain the actual geographic position of each task；
Step (1-4)：Pretreatment：It determines whether there is data and there is exception, and abnormal task pricing data is rejected.
The abnormal data, such as repeated data, such as longitude and latitude missing data, such as price is beyond the number of setting range
According to.
Step (2) step is：
Step (2-1)：Relation between analysis task；
Step (2-2)：Relation between analysis task and mission requirements person；
In the step (2-1), the relationship step between analysis task is：
Step (2-1-1)：Using the coordinate position of task, the air line distance between calculating task.
Step (2-1-2)：Determine other task quantity in each task setting distance range.
Step (2-1-2) includes：
Step (2-1-2-1) determines analyst coverage：The point centered on each task location sets circle of the radiation radius as R
For analyst coverage；
Step (2-1-2-2)：Each task scope is selected as other tasks in R, statistics is obtained in each task scope
Other business numbers.That is, for arbitrary task i, all task j are found so thatThe number M of statistics task ji-task。
Step (2-1-3)：Being obtained according to step (1) for task and corresponding task price, calculate the valency between going out on missions
Lattice are poor.
Step (2-1-3) calculation formula is：ΔPij=| Pi-Pj| (5)
Wherein, PiIt is the task price of task i, PjIt is the task price of task j.
In the step (2-2), the relationship step between analysis task and mission requirements person is：
Step (2-2-1)：Calculating task and the actual range of mission requirements person：According to the task of step (1) acquisition and appoint
The latitude and longitude coordinates for demander of being engaged in, the actual range between calculating task and mission requirements person；
Step (2-2-2)：Determine the number of demander in each task setting distance range.
Step (2-2-3) is taken office according to (2-2-2's) as a result, calculating mission requirements person in each task setting distance range
The average distance of business.
Air line distance between step (2-1-1) any two the task i, jFormula be：
Dy=(GLATj-GLATi)×ec×π/180.0 (2)
Dx=(GLONj-GLONi)×ed×π/180.0 (3)
Ec=Eb+ (Ea-Eb) × (90-GLATi)/90 (4)
Wherein, GLATiThe latitude of expression task i positions, GLONiThe longitude of expression task i positions, GLATjTable
Show the latitude of task j positions, GLONjThe longitude of expression task j positions, dy represent perpendicular between task i, j positions
To distance, dx represents the lateral separation between task i, j positions；Ed is GLATiThe parallel of latitude radius at place, ec are used for modifying factor
For the continually changing earth radius length of latitude；Ea represents equatorial radius, and Eb represents polar radius.
In step (2-2-1), the air line distance between arbitrary task i and arbitrary mission requirements person j is calculatedStep
Suddenly it is：
Dy=(BWDj-GLATi)×ec×π/180.0 (7)
Dx=(BJDj-GLONi)×ed×π/180.0 (8)
Ec=Eb+ (Ea-Eb) × (90-GLATi)/90 (9)
Wherein, GLATiThe latitude of expression task i positions, GLONiThe longitude of expression task i positions, BWDjTable
Show the latitude of mission requirements person j positions, BJDjRepresent the longitude of mission requirements person j positions, dy represents task location
Vertical distance between mission requirements person position, dx represent the lateral separation between task location and mission requirements person position；
Ed is the parallel of latitude radius where GLAT, and ec is for amendment because the continually changing earth radius length of latitude；Ea represents equator
Radius, Eb represent polar radius.
Step (2-2-2) includes：
Step (2-2-2-1)：Determine analyst coverage：The point centered on each task location sets circle of the radiation radius as R
For analyst coverage；
Step (2-2-2-2)：The mission requirements person in each task scope R is selected, statistics is obtained in each task scope
Mission requirements person's number Muser.That is, for arbitrary task i, all mission requirements person j are found so thatStatistics
The number M of mission requirements person ji-user。
The step (2-2-3) calculates arbitrary task i average distance formula of mission requirements person in the range of formulating：
Wherein, Mi-userIt is mission requirements person's number in the range of task i that step (2-2-2-2) obtains.It is step
Suddenly the air line distance between the task i that (2-2-1) is obtained and the mission requirements person j that it is included.
Step (3) includes：
Step (3-1)：Determine the distance condition that task is packaged；Task is packaged condition：The distance between two tasks are small
Price difference between the feasible distance L and task of mission requirements person is less than given threshold θ.That is, for any two task
I, j meetAnd Δ Pij≤θ。
Step (3-2)：Determine the supply and demand condition that task is packaged.Calculate in each task scope mission requirements person's number and its
The ratio Ψ of his task quantity.As Ψ ＜ 1, task number is more than mission requirements person's number, is carried out according to the condition of (3-1) more
Point task is packaged；Conversely, as Ψ >=1, mission requirements person's number is more than surrounding task number, is packaged without multiple spot task.
Step (3-3)：Calculate the radius of the task bag newly formed.Computational methods are to find the central point of task bag,
The circle of all tasks in task bag can be being covered using the central point in the concentric circles in the center of circle, to find, is taking the radius of the circle to appoint
The radius of business bag.
Mission requirements person's feasible distance in step (3-1) is the maximum distance of the packing task of mission requirements person's setting.
Beyond the task of this distance, mission requirements person will not go to complete substantially.
Given threshold θ in step (3-1) is set as needed.
The calculation formula of Ψ is in step (3-2)：For arbitrary task i,
The multiple spot packaging system of mobile platform crowdsourcing task, including：Memory, processor and storage are on a memory simultaneously
The computer instruction run on a processor completes the step of as above either method when the computer instruction is run by processor
Suddenly.
Beneficial effects of the present invention：
By the influence factor of analysis task packaging method, analyzed using multiple spot packaging method under different task is the present invention
It is no to need to carry out and how to be packaged.In the case of by task cooperative packing and issuing, the covering model of new task bag is formd
Enclose radius.And according to the quota sum of demander in the range of task number and service, by the scope that this ratio-dependent is task bag
Interior supply and demand ratio, ratio during with reference to balance between supply and demand compares, to carry out the task packing manner under the task packaging model of system
Analysis.
Compared to traditional market sale mode, the present invention fully ensure that the validity of task packaging method, also can be big
The big task that shortens transfers the cycle, and gives more perfect task Distribution dynamics, and therefore, the present invention has very important reality
Meaning.
Description of the drawings
The accompanying drawings which form a part of this application are used for providing further understanding of the present application, and the application's shows
Meaning property embodiment and its explanation do not form the improper restriction to the application for explaining the application.
Fig. 1 is that the present invention is based on the work flow diagrams of multiple spot packaging model；
Fig. 2 is scene graph when two tasks of the invention are packaged；
Fig. 3 is scene graph when three tasks of the invention are packaged；
Fig. 4 is that the present invention is packaged number distribution map；
Fig. 5 is that demander number of the present invention is more than peripheral tasks number distribution figure；
Fig. 6 is that peripheral tasks number of the present invention is more than demander number distribution figure；
Fig. 7 is task price distribution map of the present invention；
Fig. 8 is task location distribution map of the present invention.
Specific embodiment
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.It is unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
In the case where there is no conflict, the feature in the embodiment and embodiment in the application can be mutually combined.It ties below
Closing attached drawing, the invention will be further described with embodiment.
Embodiment one
As background technology is introduced, the present invention to solve the above-mentioned problems, provides a kind of multiple spot task packaging method.
The influence factor that the present invention is packaged by analysis task completes specific example using multiple spot packaging method, and according to test and appraisal
Effect tests the effect of multiple spot task packaging method.
To achieve these goals, the present invention adopts the following technical scheme that：
Multiple spot task packaging method, as shown in Figure 1, step：
(1) preparation that task is packaged：Gathered data information, to the information architecture data visualization and structure collected
Data prediction judges whether carry out task packing；
(2) analyze multiple spot task and be packaged influence factor：The data collected are analyzed, the influence that analysis task is packaged
Factor is formulated by the influence factor of analysis task packing；
(3) multiple spot task packaging method is determined：The influence factor that being obtained according to step (2) for task is packaged, determines multiple spot
Task is packaged condition, carries out task packing.
(4) the effect test and appraisal of multiple spot task packaging method：According to the task packaging model that the multiple spot of formulation is packaged, test and appraisal are appointed
The validity and convenience of business packaging model.
In this example, in the case of by task cooperative packing and issuing, with Hongqiao in Shanghai's resident's walking distance in 2015
As with reference to radius, radius foundation is packaged in this, as task.Different task coverage is calculated using geometrical relationship, and weight occurs
Close the scope radius of stylish task bag.In the range of the task bag newly formed, task in the range of calculating task number and service
Whether demander quota sum carries out multiple spot task packing according to the supply and demand ratio in the ratio-dependent of the two this task scope.
For example, task, using multiple spot packaging model in the present invention is just packaged, reformulated by a kind of task price type of In Guangzhou Area
New task pricing model considers mission requirements person's number and other number of tasks purpose ratios in each task radiation scope
Relation when the ratio between the two is more than or equal to 1, takes traditional task pricing scheme；Conversely, take multitask packing scheme.It will
Models coupling after traditional task pricing model is packaged with task uses, by effect of testing and assessing, to observe multiple spot packaging model
Test and appraisal situation.
In the step (1), preparation concretely comprises the following steps：
(1-1) basic assumption：Task is taken to build the basic assumption of model, the beam worker of invention when fixing a price in this example
Work be give tacit consent to each task difficulty level it is identical, without considering bad weather, take pictures and the influences such as refused, each task radiation radius
It is identical.
(1-2) data visualization：According to model mentioned above, this example carries out packing processing for task price, right
In data visualization structure using the data of In Guangdong Province.Histogram is established, obtains the distribution of task price of task price such as
Shown in Fig. 1.Fig. 7 can be seen that task price and be concentrated mainly between 65.0-75.0, between occurring between 75.0-85.0
Disconnected, thus analysis can obtain, and the task quantity of low price is relatively more, and the task negligible amounts of high price.Fig. 8 sees that the distribution gone out on missions is appointed
Business is mainly distributed on five cities in Guangdong Province：Shenzhen, Dongguan City, Guangzhou, Foshan City, Qingyuan City.
(1-3) data prediction：According to the longitude and latitude of task, carry out coordinate and be accurately positioned, data visualization is drawn
City carries out counties and districts' division, show that there are one task coordinate, it is abnormal thus only to judge that this data exists for Qingyuan City, therefore this hair
The bright task data Qingyuan City is rejected.According to task price distribution figure in Fig. 7, the number of tasks that price is 80.0 and 85.0 is found
Mesh is less, therefore temporarily the task data for being priced at the two prices is rejected, and is in addition analyzed.
Step (2)：The data collected are analyzed, analyzing influence mobile platform crowdsourcing task be packaged influence because
Element.
Step (2) step is：
Step (2-1)：Relation between analysis task；
Step (2-2)：Relation between analysis task and mission requirements person；
In the step (2-1), the relationship step between analysis task is：
Step (2-1-1)：Using the coordinate position of task, the air line distance between calculating task.
Air line distance between step (2-1-1) any two the task i, jFormula be：
Dy=(GLATj-GLATi)×ec×π/180.0 (2)
Dx=(GLONj-GLONi)×ed×π/180.0 (3)
Ec=Eb+ (Ea-Eb) × (90-GLATi)/90 (4)
Wherein, GLATiThe latitude of expression task i positions, GLONiThe longitude of expression task i positions, GLATjTable
Show the latitude of task j positions, GLONjThe longitude of expression task j positions, dy represent perpendicular between task i, j positions
To distance, dx represents the lateral separation between task i, j positions；Ed is GLATiThe parallel of latitude radius at place, ec are used for modifying factor
For the continually changing earth radius length of latitude；Ea represents equatorial radius, and Eb represents polar radius.
Step (2-1-2)：Determine other task quantity in each task setting distance range.
Step (2-1-2) includes：
Step (2-1-2-1) determines analyst coverage：The point centered on each task location sets circle of the radiation radius as R
For analyst coverage；
Step (2-1-2-2)：Each task scope is selected as other tasks in R, statistics is obtained in each task scope
Other business numbers.That is, for arbitrary task i, all task j are found so thatThe number M of statistics task ji-task。
Step (2-1-3)：Being obtained according to step (1) for task and corresponding task price, calculate the valency between going out on missions
Lattice are poor.
Step (2-1-3) calculation formula is：ΔPij=| Pi-Pj| (5)
Wherein, PiIt is the task price of task i, PjIt is the task price of task j.
In the step (2-2), the relationship step between analysis task and mission requirements person is：
Step (2-2-1)：Calculating task and the actual range of mission requirements person：According to the task of step (1) acquisition and appoint
The latitude and longitude coordinates for demander of being engaged in, the actual range between calculating task and mission requirements person；
In step (2-2-1), the air line distance between arbitrary task i and arbitrary mission requirements person j is calculatedStep
Suddenly it is：
Dy=(BWDj-GLATi)×ec×π/180.0 (7)
Dx=(BJDj-GLONi)×ed×π/180.0 (8)
Ec=Eb+ (Ea-Eb) × (90-GLATi)/90 (9)
Wherein, GLATiThe latitude of expression task i positions, GLONiThe longitude of expression task i positions, BWDjTable
Show the latitude of mission requirements person j positions, BJDjRepresent the longitude of mission requirements person j positions, dy represents task location
Vertical distance between mission requirements person position, dx represent the lateral separation between task location and mission requirements person position；
Ed is the parallel of latitude radius where GLAT, and ec is for amendment because the continually changing earth radius length of latitude；Ea represents equator
Radius, Eb represent polar radius.
Step (2-2-2)：Determine the number of demander in each task setting distance range.
Step (2-2-2) includes：
Step (2-2-2-1)：Determine analyst coverage：The point centered on each task location sets circle of the radiation radius as R
For analyst coverage；
Step (2-2-2-2)：The mission requirements person in each task scope R is selected, statistics is obtained in each task scope
Mission requirements person's number Muser.That is, for arbitrary task i, all mission requirements person j are found so thatStatistics
The number M of mission requirements person ji-user。
Step (2-2-3) is taken office according to (2-2-2's) as a result, calculating mission requirements person in each task setting distance range
The average distance of business.
The step (2-2-3) calculates arbitrary task i average distance formula of mission requirements person in the range of formulating：
Wherein, Mi-userIt is mission requirements person's number in the range of task i that step (2-2-2-2) obtains.It is step
Suddenly the air line distance between the task i that (2-2-1) is obtained and the mission requirements person j that it is included.
Step (3)：Determine multiple spot task packaging method：The influence factor that being obtained according to step (2) for task is packaged, determines
Multiple spot task is packaged condition, carries out task packing.
Step (3) includes：
Step (3-1)：Determine the distance condition that task is packaged；Task is packaged condition：The distance between two tasks are small
Price difference between the feasible distance L and task of mission requirements person is less than given threshold θ.That is, for any two task
I, j meetAnd Δ Pij≤θ。
Mission requirements person's feasible distance in step (3-1) is the maximum distance of the packing task of mission requirements person's setting.
Beyond the task of this distance, mission requirements person will not go to complete substantially.
Given threshold θ in step (3-1) is set as needed.
Step (3-2)：Determine the supply and demand condition that task is packaged.Calculate in each task scope mission requirements person's number and its
The ratio Ψ of his task quantity.As Ψ ＜ 1, task number is more than mission requirements person's number, is carried out according to the condition of (3-1) more
Point task is packaged；Conversely, as Ψ >=1, mission requirements person's number is more than surrounding task number, is packaged without multiple spot task.
The calculation formula of Ψ is in step (3-2)：For arbitrary task i,
Step (3-3)：Calculate the radius of the task bag newly formed.Computational methods are to find the central point of task bag,
The circle of all tasks in task bag can be being covered using the central point in the concentric circles in the center of circle, to find, is taking the radius of the circle to appoint
The radius of business bag.
As shown in Fig. 2, two tasks, which are packaged radius, calculates schematic diagram；
When being packaged into a task for two tasks, the task radius newly formed is：
R=d0+r (2)
Wherein, d0For original two tasks line midpoint to one of task distance；R is original task
Radius.
As shown in figure 3, three tasks, which are packaged radius, calculates schematic diagram；
When being packaged for three the meeting condition of the tasks, three task point composition triangles are connected, take barycenter oftriangle
As the center of circle of newly being formed for task, the distance between the center of circle and three original tasks d are calculated1, d2, d3, original task scope
Radius for r, then the scope radius of new task is：
R=max (d1,d2,d3)+r (3)
Step (4)：According to the method for step (3), multiple spot task packing is carried out to the data that step (1) obtains.
In this example, we obtain new task using task packaging model and fix a price, and the present invention, which also considers, above to be retouched
The judgement stated, if packing processing is carried out for task using multiple spot packaging model, so combining a kind of based on multiple linear time
The task pricing model returned proposes following steps：
Calculate the ratio of demander number and other task quantity in each task scope：
Work as ΨiWhen >=1, demander number and peripheral tasks number distribution figure are as shown in figure 5, demander number is more than at this time
Surrounding task number in order to reach balance and stabilization, should take a kind of traditional task based on multiple linear regression model to determine
Valency model.
Work as ΨiWhen≤1, demander number and peripheral tasks number distribution are as shown in fig. 6, task number at this time is more than need
The person's of asking number, in order to complete task as early as possible, it should using the task pricing model of multiple spot packaging model：.
This exemplary application after carrying out task packing, is obtained 201 in totally 483 task datas of Shenzhen and Guangzhou
It is as shown in Figure 4 to be packaged number distribution for a new task bag.
It can show that 2 tasks have 129 new bags after being packaged by Fig. 4,3 tasks have 51 newly after being packaged
Bag, 4 tasks have 19 new bags after being packaged, 5 tasks have 5 new bags after being packaged.Obtain Shenzhen and Guangzhou
In 483 tasks, it is 479 to complete task number, and it is 4 not complete number of tasks, and task completeness is up to 99.2%, it can be seen that, fortune
After multiple spot packaging model, the completeness of task is greatly improved.
In this example, demander and the relation of the task quantity ratio in scope are given, to the shadow of method choice
It rings.It is tested and assessed with appraisement system, when not taking packaging method, it is 1672 to complete number of tasks, and task completeness is up to 81%；It takes
During multiple spot task packaging method, it is 2038 that task, which completes number, and completeness is up to 98.6%, hence it is evident that higher than the former, therefore, it is possible to determine that
The implementation result of the program is preferable.
The foregoing is merely the preferred embodiments of the application, are not limited to the application, for the skill of this field
For art personnel, the application can have various modifications and variations.It is all within spirit herein and principle, made any repair
Change, equivalent substitution, improvement etc., should be included within the protection domain of the application.
Claims (10)
1. the multiple spot packaging method of mobile platform crowdsourcing task, it is characterized in that, comprise the following steps：
Step (1)：The preparation that task is packaged：Gather the crowdsourcing mission bit stream of labor service crowdsourcing platform and the letter of mission requirements person
Breath, is visualized and is pre-processed to crowdsourcing mission bit stream；
Step (2)：The data collected are analyzed, the influence factor that analyzing influence mobile platform crowdsourcing task is packaged；
Step (3)：Determine multiple spot task packaging method：The influence factor that being obtained according to step (2) for task is packaged, determines multiple spot
Task is packaged condition, carries out task packing；
Step (4)：According to the method for step (3), multiple spot task packing is carried out to the data that step (1) obtains.
2. the multiple spot packaging method of mobile platform crowdsourcing task as described in claim 1, it is characterized in that, the crowdsourcing task letter
Breath, including：Crowdsourcing mission number, crowdsourcing task price, the implementation status of the longitude and latitude of crowdsourcing task and crowdsourcing task；
The information of the mission requirements person, including：The position longitude and latitude of mission requirements person, the task of mission requirements person get volume
Degree, the credit value of mission requirements person.
3. the multiple spot packaging method of mobile platform crowdsourcing task as described in claim 1, it is characterized in that, in the step (1),
Crowdsourcing mission bit stream is visualized and pre-processed：
Step (1-1)：According to the crowdsourcing mission bit stream of acquisition, extraction task price is drawn histogram according to different prices, is carried out
Visualization processing obtains task price distribution map；
Step (1-2)：Coarse localization is carried out according to the longitude and latitude of crowdsourcing task, the city position of crowdsourcing task is visualized；
Step (1-3)：Finely positioning is carried out according to the longitude and latitude of crowdsourcing task, counties and districts' position visualization of crowdsourcing task obtains
To the actual geographic position of each task；
Step (1-4)：Pretreatment：It determines whether there is data and there is exception, and abnormal task pricing data is rejected.
4. the multiple spot packaging method of mobile platform crowdsourcing task as described in claim 1, it is characterized in that, step (2) step
Suddenly it is：
Step (2-1)：Relation between analysis task；
Step (2-2)：Relation between analysis task and mission requirements person.
5. the multiple spot packaging method of mobile platform crowdsourcing task as claimed in claim 4, it is characterized in that, the step (2-1)
In, the relationship step between analysis task is：
Step (2-1-1)：Using the coordinate position of task, the air line distance between calculating task；
Step (2-1-2)：Determine other task quantity in each task setting distance range；
Step (2-1-3)：Being obtained according to step (1) for task and corresponding task price, calculate the price difference between going out on missions.
6. the multiple spot packaging method of mobile platform crowdsourcing task as claimed in claim 5, it is characterized in that, step (2-1-2) bag
It includes：
Step (2-1-2-1) determines analyst coverage：The point centered on each task location, the circle for setting radiation radius as R are point
Analyse scope；
Step (2-1-2-2)：Each task scope is selected as other tasks in R, statistics obtains in each task scope other
Business number；For arbitrary task i, all task j are found so thatThe number M of statistics task ji-task。
7. the multiple spot packaging method of mobile platform crowdsourcing task as claimed in claim 4, it is characterized in that, the step (2-2)
In, the relationship step between analysis task and mission requirements person is：
Step (2-2-1)：Calculating task and the actual range of mission requirements person：The task and task obtained according to step (1) needs
The latitude and longitude coordinates for the person of asking, the actual range between calculating task and mission requirements person；
Step (2-2-2)：Determine the number of demander in each task setting distance range；
Step (2-2-3)：According to (2-2-2) as a result, calculating mission requirements person in each task setting distance range arrives task
Average distance.
8. the multiple spot packaging method of mobile platform crowdsourcing task as claimed in claim 7, it is characterized in that,
Step (2-2-2) includes：
Step (2-2-2-1)：Determine analyst coverage：The point centered on each task location, the circle for setting radiation radius as R are point
Analyse scope；
Step (2-2-2-2)：The mission requirements person in each task scope R is selected, statistics obtains appointing in each task scope
Demander number of being engaged in Muser；For arbitrary task i, all mission requirements person j are found so thatStatistics task needs
The number M of the person of asking ji-user。
9. the multiple spot packaging method of mobile platform crowdsourcing task as described in claim 1, it is characterized in that, step (3) includes：
Step (3-1)：Determine the distance condition that task is packaged：Task is packaged condition：The distance between two tasks, which are less than, appoints
Price difference between the feasible distance L and task of demander of being engaged in is less than given threshold θ；For any two task i, j, meetAnd Δ Pij≤θ；
Step (3-2)：Determine the supply and demand condition that task is packaged：Calculate in each task scope mission requirements person's number and other
The ratio Ψ for quantity of being engaged in；As Ψ ＜ 1, task number is more than mission requirements person's number, and carrying out multiple spot according to the condition of (3-1) appoints
Business is packaged；Conversely, as Ψ >=1, mission requirements person's number is more than surrounding task number, is packaged without multiple spot task；
Step (3-3)：Calculate the radius of the task bag newly formed：Computational methods are to find the central point of task bag, with
For the central point in the concentric circles in the center of circle, to find the circle that can cover all tasks in task bag, the radius for taking the circle is task bag
Radius.
10. the multiple spot packaging system of mobile platform crowdsourcing task, it is characterized in that, including：It memory, processor and is stored in
The computer instruction run on reservoir and on a processor completes as above any power when the computer instruction is run by processor
Profit requires the step of the method.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852491A (en) * | 2019-10-23 | 2020-02-28 | 深圳市汇融科技有限公司 | Real estate evaluation management system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870913A (en) * | 2012-12-18 | 2014-06-18 | 国际商业机器公司 | Task assignment server and task assignment method |
| CN103886402A (en) * | 2012-12-20 | 2014-06-25 | 国际商业机器公司 | Method and system for automated incentive computation in crowdsourcing system |
| CN104599085A (en) * | 2015-02-12 | 2015-05-06 | 北京航空航天大学 | User motivating method under crowdsourcing mode and crowdsourcing system |
| CN105447667A (en) * | 2015-11-17 | 2016-03-30 | 成都信息工程大学 | Automatic distribution method of express delivery orders |
-
2017
- 2017-12-22 CN CN201711405761.5A patent/CN108052376A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870913A (en) * | 2012-12-18 | 2014-06-18 | 国际商业机器公司 | Task assignment server and task assignment method |
| CN103886402A (en) * | 2012-12-20 | 2014-06-25 | 国际商业机器公司 | Method and system for automated incentive computation in crowdsourcing system |
| CN104599085A (en) * | 2015-02-12 | 2015-05-06 | 北京航空航天大学 | User motivating method under crowdsourcing mode and crowdsourcing system |
| CN105447667A (en) * | 2015-11-17 | 2016-03-30 | 成都信息工程大学 | Automatic distribution method of express delivery orders |
Non-Patent Citations (1)
| Title |
|---|
| 袁锐莹: "基于用户信息和任务位置的动态打包任务定价模型", 《消费导刊》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110852491A (en) * | 2019-10-23 | 2020-02-28 | 深圳市汇融科技有限公司 | Real estate evaluation management system |
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