CN109242275A - Method for allocating tasks, device and storage medium - Google Patents
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Abstract
The present invention relates to big data processing, disclose a kind of method for allocating tasks, and this method passes through the description information that analysis task reports task in request first, determines the type of task；Then the specified object for processing the generic task is filtered out from all specified objects as the subsequent scoring screening step of second user progress；The corresponding historical data of timeliness of task in request is reported then according to task, is calculated the scoring for reflecting the level of skill of each second user, is selected the highest second user of the scoring of preset quantity；Finally preferentially selecting User Status is online second user as target object, assigns the task to the target object.The present invention is also disclosed that a kind of electronic device and computer storage medium.Using the present invention, the accuracy of task distribution can be improved, improve task treatment effeciency.
Description
Technical field
The present invention relates to technical field of data processing more particularly to a kind of method for allocating tasks, electronic device and computer
Readable storage medium storing program for executing.
Background technique
With the development of company/enterprise, company/enterprise reports the classification of task, quantity also to will increase, for example, maintenance,
The events such as system maintenance, network, mailbox.It is at present to be randomly assigned processing people to the processing mode of reported event, it is understood that there may be place
Reason people's is good at the field problem not corresponding with reported event classification, because the field that processing people is good at largely determines
The treatment effeciency of reported event, therefore, the mode for being randomly assigned processing people's processing reported event need to improve.
Summary of the invention
In view of the foregoing, the present invention provides a kind of method for allocating tasks, electronic device and computer readable storage medium,
Main purpose is the accuracy rate distributed by raising task, improves task treatment effeciency.
To achieve the above object, the present invention provides a kind of method for allocating tasks, this method comprises:
S1, the receiving the first user submission of the task report request, report request to the task according to default classifying rules
Corresponding task is classified, and marks the first label for the task；
S2, the second label for obtaining specified object, it is one corresponding to filter out the second label comprising first label
Or multiple specified objects are as second user；
S3, when there are multiple second users, obtain the scoring reference index of the multiple second user, commented according to default
Divider then calculates the scoring of the multiple second user, filters out the highest second user of scoring of preset quantity；
S4, obtain the preset quantity second user preset kind, described preset judge according to default judgment rule
The User Status of the second user of quantity, comprising: online, stealthy, offline；And
S5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to
The target object, and allocation result is fed back into the first user and target object.
In addition, the device includes: memory, processor the present invention also provides a kind of electronic device, deposited on the memory
Containing the task distribution program that can be run on the processor can when the task distribution program is executed by the processor
Realize the arbitrary steps in method for allocating tasks as described above.
In addition, to achieve the above object, it is described computer-readable the present invention also provides a kind of computer readable storage medium
It include task distribution program in storage medium, it can be achieved that task as described above when the task distribution program is executed by processor
Arbitrary steps in distribution method.
Method for allocating tasks, electronic device and computer readable storage medium proposed by the present invention, firstly, being appointed by analysis
Business reports the description information of task in request, determines the type of task, and mark the first label, accurately determines task type,
For subsequent allocations, optimization process people lays the foundation；Then, it is filtered out from all specified objects and processes the specified of the generic task
Object carries out subsequent scoring screening step as second user, filters out the specified object without the generic task process experience, helps
In raising task treatment effeciency；Finally, report the attribute information of task in request to determine the timeliness of task according to task, and according to
Second user historical data corresponding with task timeliness calculates the scoring for reflecting the level of skill of each second user, convenient for the
Two users are managed, and improve the accuracy of task distribution；The highest second user of scoring of preset quantity is filtered out, and is determined
Its User Status, preferentially selecting User Status is online second user as target object, assigns the task to the target pair
As through the above steps, improving the accuracy of task distribution, distributing high-quality processing people for task, help to improve task processing
Efficiency.
Detailed description of the invention
Fig. 1 is the flow chart of method for allocating tasks preferred embodiment of the present invention；
Fig. 2 is the running environment schematic diagram of electronic device of the present invention；
Fig. 3 is the schematic diagram of electronic device preferred embodiment of the present invention；
Fig. 4 is the program module schematic diagram of task distribution program in Fig. 3.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present invention provides a kind of method for allocating tasks.It is method for allocating tasks preferred embodiment of the present invention shown in referring to Fig.1
Flow chart.This method can be executed by a device, which can be by software and or hardware realization.
In the present embodiment, method for allocating tasks includes step S1-S5.
S1, the receiving the first user submission of the task report request, report request to the task according to default classifying rules
Corresponding task is classified, and marks the first label for the task.
It is illustrated below using electronic device as executing subject.First user is that submission task reports reporting for request
People, the first label are the class label for characterizing task type.There are when event to be reported, need to be that event to be reported is raw by first user
At the description information of event to be reported, to the concrete condition, coverage, urgency level etc. for describing event to be reported, then
Description information based on event to be reported generates task and reports request, wherein task reports the description in request including task to believe
Breath, that is, the task reports the description information for requesting corresponding event to be reported.
In order to report the corresponding task of request to distribute to optimization process people the task, when receiving the first user submission
After task reports request, task description information need to be analyzed, and classification belonging to judgement task.
In the present embodiment, in step S1 it is described " according to default classifying rules to the task report request it is corresponding
Task is classified, and marks the first label for the task " include:
Read the description information that the task reports carrying in request for task；
Using preparatory trained term vector model, target feature vector is extracted from the description information；
Based on preset distance algorithm, the target feature vector and multiple specified spies for carrying class label are calculated separately
The distance between vector sample is levied, the smallest specific characteristic vector sample of distance of the first preset quantity is filtered out；And
Obtain the class label that the smallest specific characteristic vector sample of distance of first preset quantity carries, selection weight
Again most class labels is counted, marks the first label as the task generic, and for the task.
Above-mentioned trained term vector model (word2vec model) in advance is based on default corpus and generates, for example, Chinese
Wikipedia corpus.
The calculation method of above-mentioned distance has very much, for example, Euclidean distance algorithm, standardization Euclidean distance algorithm, Manhattan
Distance algorithm etc..
In the present embodiment, above-mentioned specific characteristic vector sample is obtained by following steps:
The appointed task description information for carrying class label is obtained, each appointed task description letter of term vector model extraction is utilized
Cease character pair vector；According to the mapping relations of appointed task description information and class label, each appointed task description letter is determined
Cease the corresponding class label of corresponding feature vector；And according to the corresponding feature vector of each appointed task description information and its right
The class label answered determines specific characteristic vector sample.
By calculating the distance between target feature vector and specific characteristic vector sample, target signature feature vector is judged
A possibility that with the similarity between specific characteristic vector sample, distance is bigger, and similarity is lower, belongs to same category is smaller；
On the contrary, similarity is bigger apart from smaller, a possibility that belonging to same category, is bigger.
It should be noted that selecting each class label corresponding when existing simultaneously the highest class label of two frequencys
Specific characteristic vector sample in target feature vector apart from the corresponding class label of reckling as target feature vector
Class label.
The description information of task in request is reported using above-mentioned steps analysis task, and marks the first label for the task,
By accurately analyzing the task category of the task, helps to handle people for the task optimal scheme, improve the treatment effeciency of task.
S2, the second label for obtaining specified object, it is one corresponding to filter out the second label comprising first label
Or multiple specified objects are as second user.
Above-mentioned specified object is processing people all in task reporting system, and the second label is that characterization second user is handled
The task type of historic task, second user be it is processed reported with task request in the identical historic task of task category finger
Determine object.
Wherein, each specified object may correspond to one or more second labels.For example, the second label may include: " to have
Gauze network ", " wireless network ", " terminal security " etc..
The purpose of the step is, by from specified pair filtered out in the second label comprising the first label in specified object
Specified pair of the identical historic task of task category in request is reported as second user, filtering out untreated with task
As helping to improve the treatment effeciency of task.
S3, when there are multiple second users, obtain the scoring reference index of the multiple second user, commented according to default
Divider then calculates the scoring of the multiple second user, filters out the highest second user of scoring of preset quantity.
In the present embodiment, task report further include in request task attribute information, " obtaining described more in step S3
The scoring reference index of a second user, the scoring of the multiple second user is calculated according to default code of points " include:
The attribute information that the task reports task in request is obtained, the target of the task is determined according to the attribute information
Timeliness；
The subscriber identity information for obtaining the multiple second user reads the multiple second according to the subscriber identity information
User's scoring reference index corresponding with the target timeliness within a preset time, based on scoring reference index generation each the
The sample data of two users；
The sample data of each second user is normalized, and to the sample data Jing Guo normalized into
Row principal component analysis extracts principal component of the contribution rate of accumulative total more than the second preset quantity of preset threshold；And
It obtains the corresponding characteristic value of principal component of second preset quantity and is weighted, calculate separately each second and use
The scoring at family.
In the present embodiment, the step of described " the target timeliness of the task is determined according to the attribute information " includes:
Read the influence degree and coverage in the attribute information；And
According to the mapping relations of the combination of influence degree and coverage and timeliness, the influence in the attribute information is determined
The corresponding target timeliness of the combination of degree and coverage.
Specifically, above-mentioned target timeliness reports the attribute of task in request by task for characterizing task urgency level
Information determines.
In the attribute information of the task, include: task coverage and task influence degree.Wherein, coverage
(influence number) includes: " small (1 people) ", " in (2 to 5 people) ", " (6 to 15 people) bigger than normal " and " big (more than 15 people) "；Influence journey
Degree includes: " regular event ", " having substantially no effect on office ", " influencing office to a certain extent " and " can not handle official business ".
Before receiving the task that the first user submits and reporting request, Different Effects degree and coverage are predefined
Combine corresponding timeliness comprising: response timeliness and solution timeliness, and the timeliness list of elements is generated, for example, when in the timeliness list of elements
Effect includes: P1, P2, P3, P4, respectively indicates different urgency levels.
It determines that above-mentioned task reports in request after the corresponding target timeliness of task using the above-mentioned timeliness list of elements, utilizes second
The identity information of user obtains the history of second user within a preset time from default channel (for example, task reporting system) and appoints
Business data, and data extraction is carried out to above-mentioned historic task data, determine scoring reference index corresponding with the target timeliness.
Specifically, scoring reference index includes: that second user is related to the first label in preset time (for example, half a year)
Average daily task amount, average daily production capacity, week task amount, week production capacity, monthly task amount, monthly production capacity, response in overall timeliness
Fix-rate in rate, overall timeliness, response rate, target solve fix-rate and user's satisfaction rate etc. in timeliness and refer in target response timeliness
Mark, These parameters can reflect level of skill of the second user about the first label.Using above-mentioned scoring reference index, generate each
The r of second user ties up sample data D, D=[x1,x2,…,xi,…,xr], wherein xiFor i-th of index in scoring reference index
Value, that is, i-th dimension data.
In the present embodiment, the step of described " sample data of each second user is normalized " includes:
0 mean value standardization is carried out to every one-dimensional data in the sample data.
By taking the sample data of some second user as an example, 0 mean value standard is carried out to every one-dimensional data in sample data
The calculation formula of change are as follows:
fi=(xi-mean(xi))/σ(xi)
Wherein, xiFor the i-th dimension data in sample data, fiFor i-th dimension data normalization treated value, mean (xi)
For the mean value of i-th dimension data in the sample data of multiple second users, σ (xi) it is i-th in the sample data of multiple second users
The standard deviation of dimension data.
In the present embodiment, described " principal component analysis to be carried out to the sample data Jing Guo normalized, is extracted accumulative
Contribution rate be more than preset threshold the second preset quantity principal component " the step of include:
The sample data after normalized is obtained, the covariance of the sample data after normalized is calculated
Matrix；Eigenvalues Decomposition is carried out to the covariance matrix, obtains multiple characteristic values and corresponding feature vector；And according to institute
The size for stating multiple characteristic values carries out descending sort, select the forward corresponding feature of characteristic value of sequence of the second preset quantity to
Amount is used as principal component.
It should be noted that the sequence of the second preset quantity (for example, k, wherein k is positive integer) of selection is forward
Characteristic value need to meet preset condition, for example, contribution rate of accumulative total is more than or equal to preset threshold (for example, 85%).Wherein, k feature
It is worth corresponding feature vector and is respectively as follows: ω1,ω2,…,ωk, then using the k corresponding feature vectors of characteristic value as master
Ingredient, wherein each principal component can explain multiple scoring reference indexs.
K principal component ω is extracted using above-mentioned steps1,ω2,…,ωkAfterwards, it is named according to the physical meaning of each principal component
For yield, proficiency, efficiency etc..
Assuming that the corresponding characteristic value of k principal component is respectively as follows: λ1, λ2…λk, which is weighted, is calculated
To the scoring of each second user.It should be noted that the scoring that above-mentioned steps meter obtains is the scoring for the first label, it is used for
Reflect level of skill and treatment effeciency of the second user in processing about the task of the first label.
In the present embodiment, the calculation formula of scoring are as follows:
Wherein, F (ω1,ω2,…,ωk) be each second user scoring, | ωi| it is the corresponding value of i-th of principal component, λi
For the corresponding characteristic value of i-th of principal component.
The scoring that each second user is calculated using above-mentioned steps arranges each second user according to scoring sequence
Sequence filters out the sequence of preset quantity (for example, 5) near preceding second user.
S4, obtain the preset quantity second user preset kind information, according to the judgement of default judgment rule
The User Status of the second user of preset quantity, wherein User Status includes: online, stealthy, offline.
Above-mentioned preset kind information includes: the information such as operation note, conference journey, the attendance positioning of appointing system.
In the present embodiment, in step S4 it is described " according to default judgment rule judge the preset quantity second use
The User Status at family " includes:
When the second user does not have operation note on appointing system within a preset time, the second user is judged
State be it is offline, otherwise judge whether the second user has conference journey in current time；
When the second user is when current time has conference journey, judge the User Status of the second user to be stealthy,
Otherwise, judge whether attendance location information of the second user on the day of is not inconsistent with its preset attendance location information；And
When attendance location information of the second user on the day of and its preset attendance location information are not inconsistent, judgement should
The state of second user be it is offline, otherwise, judge that the User Status of the second user is online.
Above-mentioned preset time may be configured as 2h, if second user is in 2h in appointing system (for example, task management system)
On without operation note, directly judgement User Status is offline；Otherwise, the meeting row of second user is inquired from meeting schedule system
Journey, and from attendance checking system inquire second user attendance location information, if user does not have conference journey in current time and examines
Diligent location information is consistent with default attendance location information, judges that the User Status of second user is online.
S5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to
The target object, and allocation result is fed back into the first user and target object.
After the User Status of the highest second user of scoring for determining above-mentioned preset quantity using above-mentioned steps, according to
Line, stealthy, offline sequence select a second user as target object, by task from the second user of preset quantity
It reports the task in request to distribute to target object, and is sent to the first user and mesh based on allocation result is generated prompt information
Mark object.
It should be noted that when according to the second label filtration go out second user only one when, then after not needing progress
Task directly using the second user as target object, and is reported the task in request to distribute to by continuous scoring screening step
Target object, and the first user and target object are sent to based on allocation result is generated prompt information.
In other embodiments, step S5 further include:
When second user identical there are multiple User Status in the second user of preset quantity, obtain respectively multiple
The waiting task amount of the identical second user of User Status；And
Selected from the identical second user of the multiple User Status the smallest second user of waiting task amount as
Target object.
Further, this screening factor of the waiting task quantity also can be replaced the position of each second user:
The location information for obtaining the identical second user of multiple User Status calculates separately position and the institute of each second user
The task of stating reports the distance of the position of task in request；And
It is selected from the identical second user of the multiple User Status apart from the corresponding second user of minimum value as mesh
Mark object.
When the User Status of the highest second user of scoring of preset quantity is identical, currently pending task amount is selected most
Few second user, alternatively, helping to improve task processing effect as target object apart from the smallest second user with task
Rate.
In other embodiments, this method further include:
When the assigned task of target object refusal processing, one is reselected according to online, stealthy, offline sequence
Second user reassigns to the new target object as new target object, by the task, and allocation result is fed back to
First user and new target object；Or
If target object does not respond assigned task in target response timeliness, alternatively, if target object is not in target
The assigned task of ageing treatment is solved, warning information is generated.
For example, it is P1 that the task, which reports the corresponding target timeliness of request, the task of preset P1 timeliness rank responds timeliness
It is 15 minutes, if target object responded the task in 15 minutes, illustrates to be responded in timeliness.
Further, this method further include:
The task processing result for receiving target object feedback, feeds back to the first user for the task processing result, and connect
The service to target object for receiving the first user feedback is scored；
The second label of the first tag update target object of task in request is reported according to the task.
That is, target object is every when having handled one and reporting task, the first user evaluates target object, and
Using the corresponding class label of task as corresponding second label of target, and its second tally set is updated.
The method for allocating tasks that above-described embodiment proposes, first by accurately determining task type, most for subsequent allocations
Good processing people lays the foundation；Then the specified object without the generic task process experience is filtered out, task processing effect is helped to improve
Rate；The scoring for reflecting the level of skill of each second user is finally calculated, convenient for being managed to second user, improves task distribution
Accuracy；The highest second user of scoring of preset quantity is filtered out, and User Status is preferentially selected to use for online second
Family assigns the task to the target object as target object, through the above steps, improves the accuracy of task distribution, to appoint
Business distributes high-quality processing people, helps to improve task treatment effeciency.
The present invention also provides a kind of electronic devices.
It is the running environment schematic diagram of the preferred embodiment of electronic device 1 of the present invention referring to shown in Fig. 2.
In the present embodiment, electronic device 1 can carry out data transmission with the first client 21 and the second client 22.First
Client 21 is the terminal device that the first user uses, for submitting task to report request, receiving task allocation result and feedback
Service scoring etc., is equipped with corresponding first client-side program of task distribution program 10 and (does not mark in figure in the first client 21
Note)；Second client 22 is the terminal device that second user uses, for receiving task distribution and feedback task processing result
Deng being equipped with corresponding second client-side program (being not marked in figure) of task distribution program 10 in the second client 22.
It is the schematic diagram of 1 preferred embodiment of electronic device of the present invention referring to shown in Fig. 3.
In the present embodiment, electronic device 1 can be server, smart phone, tablet computer, portable computer, on table
The terminal device having data processing function such as type computer, the server can be rack-mount server, blade type service
Device, tower server or Cabinet-type server.
The electronic device 1 includes memory 11, processor 12 and network interface 13.
Wherein, memory 11 include at least a type of readable storage medium storing program for executing, the readable storage medium storing program for executing include flash memory,
Hard disk, multimedia card, card-type memory (for example, SD or DX memory etc.), magnetic storage, disk, CD etc..Memory 11
It can be the internal storage unit of the electronic device 1, such as the hard disk of the electronic device 1 in some embodiments.Memory
11 are also possible to be equipped on the External memory equipment of the electronic device 1, such as the electronic device 1 in further embodiments
Plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card dodge
Deposit card (Flash Card) etc..Further, memory 11 can also both include the internal storage unit of the electronic device 1 or wrap
Include External memory equipment.
Memory 11 can be not only used for the application software and Various types of data that storage is installed on the electronic device 1, such as appoint
Distribution program 10 of being engaged in etc., can be also used for temporarily storing the data that has exported or will export.
Processor 12 can be in some embodiments a central processing unit (Central Processing Unit,
CPU), controller, microcontroller, microprocessor or other data processing chips, the program for being stored in run memory 11
Code or processing data, such as task distribution program 10 etc..
Network interface 13 optionally may include standard wireline interface and wireless interface (such as WI-FI interface), be commonly used in
Communication connection is established between the electronic device 1 and other electronic equipments, such as.First client (being not marked in figure), second
Client (is not marked in figure).
Fig. 3 illustrates only the electronic device 1 with component 11-13, it will be appreciated by persons skilled in the art that Fig. 3 shows
Structure out does not constitute the restriction to electronic device 1, may include than illustrating less perhaps more components or combining certain
A little components or different component layouts.
Optionally, the electronic device 1 can also include user interface, user interface may include display (Display),
Input unit such as keyboard (Keyboard), optional user interface can also include standard wireline interface and wireless interface.
Optionally, in some embodiments, display can be light-emitting diode display, liquid crystal display, touch control type LCD and show
Device and Organic Light Emitting Diode (Organic Light-Emitting Diode, OLED) touch device etc..Wherein, display
It is properly termed as display screen or display unit, for showing the information handled in the electronic apparatus 1 and for showing visually
User interface.
In 1 embodiment of electronic device shown in Fig. 3, appoint as storage in a kind of memory 11 of computer storage medium
The program code for distribution program 10 of being engaged in when processor 12 executes the program code of task distribution program 10, realizes following steps:
A1, the receiving the first user submission of the task report request, report request to the task according to default classifying rules
Corresponding task is classified, and marks the first label for the task.
It is illustrated below using electronic device 1 as executing subject.First user is that submission task reports reporting for request
People, the first label are the class label for characterizing task type.There are when event to be reported, need to be that event to be reported is raw by first user
At the description information of event to be reported, to the concrete condition, coverage, urgency level etc. for describing event to be reported, then
Description information based on event to be reported generates task and reports request, wherein task reports the description in request including task to believe
Breath, that is, the task reports the description information for requesting corresponding event to be reported.
In order to report the corresponding task of request to distribute to optimization process people the task, when receiving the first user submission
After task reports request, task description information need to be analyzed, and classification belonging to judgement task.
In the present embodiment, in step A1 it is described " according to default classifying rules to the task report request it is corresponding
Task is classified, and marks the first label for the task " include:
Read the description information that the task reports carrying in request for task；
Word segmentation processing is carried out to the description information, obtains the lexical set of the description information；
According to preset analysis rule, the keyword of the description information is determined from the lexical set；And
According to the mapping relations of preset keyword and class label, the corresponding class label of the description information is determined,
And the first label is marked for the task.
Before carrying out word segmentation processing to foregoing description information, label data (for example, picture, link), image mark are removed
The extraneous datas such as note.Then, the text data of reservation is segmented by participle tool, is generated with the initial word of space-separated
Collect conjunction.It carries out stop words to initial lexical set according to preset stop words vocabulary to handle, after stop words will be gone to handle
Lexical set of the lexical set as the description information.
The determination method of above-mentioned keyword has very much, for example, utilizing term frequency-inverse document frequency index (TF-IDF) algorithm meter
It counts stating the significance level of each vocabulary in lexical set in, then selects the higher vocabulary of significance level as keyword etc..
For example, preset keyword includes: that the keywords such as " wireless signal ", " AP " are corresponding with the mapping relations of class label
Class label be " wireless network "；The corresponding class of keywords such as " attachment ", " outlook ", " calendar synchronization ", " pst file "
Distinguishing label is " mailbox problem "；The corresponding class label of keywords such as " standardization ", " index ", " Huang screen ", " information security " is
" PC standardization ".
The description information of task in request is reported using above-mentioned steps analysis task, and marks the first label for the task,
By accurately analyzing the task category of the task, helps to handle people for the task optimal scheme, improve the treatment effeciency of task.
A2, the second label for obtaining specified object, it is one corresponding to filter out the second label comprising first label
Or multiple specified objects are as second user.
Above-mentioned specified object is processing people all in task reporting system, and the second label is that characterization second user is handled
The task type of historic task, second user be it is processed reported with task request in the identical historic task of task category finger
Determine object.
Wherein, each specified object may correspond to one or more second labels.For example, the second label may include: " to have
Gauze network ", " wireless network ", " terminal security " etc..
The purpose of the step is, by from specified pair filtered out in the second label comprising the first label in specified object
Specified pair of the identical historic task of task category in request is reported as second user, filtering out untreated with task
As helping to improve the treatment effeciency of task.
A3, when there are multiple second users, obtain the scoring reference index of the multiple second user, commented according to default
Divider then calculates the scoring of the multiple second user, filters out the highest second user of scoring of preset quantity.
In the present embodiment, task report further include in request task attribute information, " obtaining described more in step A3
The scoring reference index of a second user, the scoring of the multiple second user is calculated according to default code of points " include:
The attribute information that the task reports task in request is obtained, the target of the task is determined according to the attribute information
Timeliness；
The subscriber identity information for obtaining the multiple second user reads the multiple second according to the subscriber identity information
User's scoring reference index corresponding with the target timeliness within a preset time, based on scoring reference index generation each the
The sample data of two users；
The sample data of each second user is normalized, and to the sample data Jing Guo normalized into
Row principal component analysis extracts principal component of the contribution rate of accumulative total more than the second preset quantity of preset threshold；And
It obtains the corresponding characteristic value of principal component of second preset quantity and is weighted, calculate separately each second and use
The scoring at family.
In the present embodiment, the step of described " the target timeliness of the task is determined according to the attribute information " includes:
Read the influence degree and coverage in the attribute information；And
According to the mapping relations of the combination of influence degree and coverage and timeliness, the influence in the attribute information is determined
The corresponding target timeliness of the combination of degree and coverage.
Specifically, above-mentioned target timeliness reports the attribute of task in request by task for characterizing task urgency level
Information determines.
In the attribute information of the task, include: task coverage and task influence degree.Wherein, coverage
(influence number) includes: " small (1 people) ", " in (2 to 5 people) ", " (6 to 15 people) bigger than normal " and " big (more than 15 people) "；Influence journey
Degree includes: " regular event ", " having substantially no effect on office ", " influencing office to a certain extent " and " can not handle official business ".
Before receiving the task that the first user submits and reporting request, Different Effects degree and coverage are predefined
Combine corresponding timeliness comprising: response timeliness and solution timeliness, and the timeliness list of elements is generated, for example, when in the timeliness list of elements
Effect includes: P1, P2, P3, P4, respectively indicates different urgency levels.
It determines that above-mentioned task reports in request after the corresponding target timeliness of task using the above-mentioned timeliness list of elements, utilizes second
The identity information of user obtains the history of second user within a preset time from default channel (for example, task reporting system) and appoints
Business data, and data extraction is carried out to above-mentioned historic task data, determine scoring reference index corresponding with the target timeliness.
Specifically, scoring reference index includes: that second user is related to the first label in preset time (for example, half a year)
Average daily task amount, average daily production capacity, week task amount, week production capacity, monthly task amount, monthly production capacity, response in overall timeliness
Fix-rate in rate, overall timeliness, response rate, target solve fix-rate and user's satisfaction rate etc. in timeliness and refer in target response timeliness
Mark, These parameters can reflect level of skill of the second user about the first label.Using above-mentioned scoring reference index, generate each
The r of second user ties up sample data D, D=[x1,x1,…,xi,…,xr], wherein xiFor i-th of index in scoring reference index
Value, that is, i-th dimension data.
In the present embodiment, the step of described " sample data of each second user is normalized " includes:
0 mean value standardization is carried out to every one-dimensional data in the sample data.
By taking the sample data of some second user as an example, 0 mean value standard is carried out to every one-dimensional data in sample data
The calculation formula of change are as follows:
fi=(xi-mean(xi))/σ(xi)
Wherein, xiFor the i-th dimension data in sample data, fiFor i-th dimension data normalization treated value, mean (xi)
For the mean value of i-th dimension data in the sample data of multiple second users, σ (xi) it is i-th in the sample data of multiple second users
The standard deviation of dimension data.
In the present embodiment, described " principal component analysis to be carried out to the sample data Jing Guo normalized, is extracted accumulative
Contribution rate be more than preset threshold the second preset quantity principal component " the step of include:
The sample data after normalized is obtained, the covariance of the sample data after normalized is calculated
Matrix；
Eigenvalues Decomposition is carried out to the covariance matrix, obtains multiple characteristic values and corresponding feature vector；And
Descending sort is carried out according to the size of the multiple characteristic value, the feature for selecting the sequence of the second preset quantity forward
It is worth corresponding feature vector as principal component.
It should be noted that the sequence of the second preset quantity (for example, k, wherein k is positive integer) of selection is forward
Characteristic value need to meet preset condition, for example, contribution rate of accumulative total is more than or equal to preset threshold (for example, 85%).Wherein, k feature
It is worth corresponding feature vector and is respectively as follows: ω1,ω2,…,ωk, then using the k corresponding feature vectors of characteristic value as master
Ingredient, wherein each principal component can explain multiple scoring reference indexs.
K principal component ω is extracted using above-mentioned steps1,ω2,…,ωkAfterwards, it is named according to the physical meaning of each principal component
For yield, proficiency, efficiency etc..
Assuming that the corresponding characteristic value of k principal component is respectively as follows: λ1, λ2…λk, which is weighted, is calculated
To the scoring of each second user.It should be noted that the scoring that above-mentioned steps meter obtains is the scoring for the first label, it is used for
Reflect level of skill and treatment effeciency of the second user in processing about the task of the first label.
In the present embodiment, the calculation formula of scoring are as follows:
Wherein, F (ω1,ω2,…,ωk) be each second user scoring, | ωi| it is the corresponding value of i-th of principal component, λi
For the corresponding characteristic value of i-th of principal component.
The scoring that each second user is calculated using above-mentioned steps arranges each second user according to scoring sequence
Sequence filters out the sequence of preset quantity (for example, 5) near preceding second user.
A4, obtain the preset quantity second user preset kind information, according to the judgement of default judgment rule
The User Status of the second user of preset quantity, wherein User Status includes: online, stealthy, offline.
Above-mentioned preset kind information includes: the information such as operation note, conference journey, the attendance positioning of appointing system.
In the present embodiment, in step A4 it is described " according to default judgment rule judge the preset quantity second use
The User Status at family " includes:
When the second user does not have operation note on appointing system within a preset time, the second user is judged
State be it is offline, otherwise judge whether the second user has conference journey in current time；
When the second user is when current time has conference journey, judge the User Status of the second user to be stealthy,
Otherwise, judge whether attendance location information of the second user on the day of is not inconsistent with its preset attendance location information；And
When attendance location information of the second user on the day of and its preset attendance location information are not inconsistent, judgement should
The state of second user be it is offline, otherwise, judge that the User Status of the second user is online.
Above-mentioned preset time may be configured as 2h, if second user is in 2h in appointing system (for example, task management system)
On without operation note, directly judgement User Status is offline；Otherwise, the meeting row of second user is inquired from meeting schedule system
Journey, and from attendance checking system inquire second user attendance location information, if user does not have conference journey in current time and examines
Diligent location information is consistent with default attendance location information, judges that the User Status of second user is online.
A5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to
The target object, and allocation result is fed back into the first user and target object.
After the User Status of the highest second user of scoring for determining above-mentioned preset quantity using above-mentioned steps, according to
Line, stealthy, offline sequence select a second user as target object, by task from the second user of preset quantity
It reports the task in request to distribute to target object, and is sent to the first user and mesh based on allocation result is generated prompt information
Mark object.
It should be noted that when according to the second label filtration go out second user only one when, then after not needing progress
Task directly using the second user as target object, and is reported the task in request to distribute to by continuous scoring screening step
Target object, and the first user and target object are sent to based on allocation result is generated prompt information.
In other embodiments, when there are the identical second users of multiple User Status in the second user of preset quantity
When, the least second user of currently pending task amount is selected, alternatively, with task apart from the smallest second user as target pair
As helping to improve task treatment effeciency.
In other embodiments, when the task distribution program is executed by the processor, following steps are also realized:
According to the mapping relations of scoring and grade, the corresponding grade of the scoring of each second user is determined.
According to specific data distribution, capacity sizing standard is formulated, for example, evaluation should when F value is between (a, b)
The such technical ability of second user is steady；When F value is greater than b, evaluates the such technical ability of the second user and be proficient in；When F value is less than a, comment
The such level of skill of the valence second user is general.
In addition, 6 months at quarterly intervals, the scoring of each processing all kinds of technical ability of people is calculated, dynamically updates each processing people's
Technical ability classification and level of skill.COMPREHENSIVE CALCULATING processing people is good at skillset and generates technical ability radar map.For example, some second user
Not only it had been good at A technical ability, but also has been good at B technical ability and C technical ability, the technical ability radar map of this second user can be generated, has intuitively shown its item
Technical ability and relatively it is good at field.
Using above-mentioned steps, it can be achieved that all technical ability classification and the control of level of skill for handling people.
The electronic device 1 that above-described embodiment proposes is subsequent allocations the best of it first by accurately determining task type
Reason people lays the foundation；Then the specified object without the generic task process experience is filtered out, task treatment effeciency is helped to improve；Most
The scoring for reflecting the level of skill of each second user is calculated afterwards, convenient for being managed to second user, improves the standard of task distribution
True property；The highest second user of scoring of preset quantity is filtered out, and User Status is preferentially selected to make for online second user
For target object, the target object is assigned the task to, through the above steps, improves the accuracy of task distribution, for task point
With high-quality processing people, task treatment effeciency is helped to improve.
Optionally, in other examples, task distribution program 10 can also be divided into one or more module,
One or more module is stored in memory 11, and by one or more processors (the present embodiment is processor 12) institute
It executes, to complete the present invention, the so-called module of the present invention is the series of computation machine program instruction for referring to complete specific function
Section.It is the module diagram of task distribution program 10 in Fig. 3 for example, referring to shown in Fig. 4, in the embodiment, task distribution program
10 can be divided into receiving module 110, the first screening module 120, the second screening module 130, judgment module 140 and distribution mould
Block 150, the functions or operations step that the module 110-150 is realized is similar as above, and and will not be described here in detail, exemplary
Ground, such as wherein:
Receiving module 110, the task for receiving the first user submission reports request, according to default classifying rules to described
Task reports the corresponding task of request to classify, and marks the first label for the task；
First screening module 120 filters out comprising first label for obtaining the second label of specified object
The corresponding one or more specified objects of two labels are as second user；
Second screening module 130, the scoring for when there are multiple second users, obtaining the multiple second user are joined
Index is examined, the scoring of the multiple second user is calculated according to default code of points, the scoring for filtering out preset quantity is highest
Second user；
Judgment module 140, the preset kind of the second user for obtaining the preset quantity, according to default judgment rule
Judge the User Status of the second user of the preset quantity, comprising: online, stealthy, offline；And
Distribution module 150 is online, stealthy second user as target object for successively selecting User Status, will
The task distributes to the target object, and allocation result is fed back to the first user and target object.
In addition, the embodiment of the present invention also proposes a kind of computer readable storage medium, the computer readable storage medium
In include task distribution program 10, following operation is realized when the task distribution program 10 is executed by processor:
A1, the receiving the first user submission of the task report request, report request to the task according to default classifying rules
Corresponding task is classified, and marks the first label for the task；
A2, the second label for obtaining specified object, it is one corresponding to filter out the second label comprising first label
Or multiple specified objects are as second user；
A3, when there are multiple second users, obtain the scoring reference index of the multiple second user, commented according to default
Divider then calculates the scoring of the multiple second user, filters out the highest second user of scoring of preset quantity；
A4, obtain the preset quantity second user preset kind, described preset judge according to default judgment rule
The User Status of the second user of quantity, comprising: online, stealthy, offline；And
A5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to
The target object, and allocation result is fed back into the first user and target object.
The specific implementation of the specific embodiment of the computer readable storage medium of the present invention and above-mentioned method for allocating tasks
Mode is roughly the same, and details are not described herein.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, device, article or the method that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, device, article or method institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, device of element, article or method.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of method for allocating tasks is applied to electronic device, which is characterized in that the described method includes:
S1, the receiving the first user submission of the task report request, report request to correspond to the task according to default classifying rules
Task classify, and for the task mark the first label；
S2, the second label for obtaining specified object, it is one or more corresponding to filter out the second label comprising first label
A specified object is as second user；
S3, when there are multiple second users, obtain the scoring reference index of the multiple second user, according to default scoring advise
The scoring for then calculating the multiple second user filters out the highest second user of scoring of preset quantity；
S4, obtain the preset quantity second user preset kind information, described preset judge according to default judgment rule
The User Status of the second user of quantity, comprising: online, stealthy, offline；And
S5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to the mesh
Object is marked, and allocation result is fed back into the first user and target object.
2. the method for allocating tasks according to claim, which is characterized in that described " according to default judgement rule in step S4
Then judge the User Status of the second user of the preset quantity " include:
When the second user does not have operation note on appointing system within a preset time, the state of the second user is judged
To be offline, otherwise judge whether the second user has conference journey in current time；
When the second user is when current time has conference journey, judge the User Status of the second user to be stealthy, otherwise,
Judge whether attendance location information of the second user on the day of is not inconsistent with its preset attendance location information；And
When attendance location information of the second user on the day of and its preset attendance location information are not inconsistent, judge this second
The state of user be it is offline, otherwise, judge that the User Status of the second user is online.
3. method for allocating tasks according to claim 2, which is characterized in that " obtain the multiple second in step S3
The scoring reference index of user, the scoring of the multiple second user is calculated according to default code of points " include:
The attribute information that the task reports task in request is obtained, when determining the target of the task according to the attribute information
Effect；
The subscriber identity information for obtaining the multiple second user reads the multiple second user according to the subscriber identity information
Scoring reference index corresponding with the target timeliness within a preset time generates each second based on the scoring reference index and uses
The sample data at family；
The sample data of each second user is normalized, and the sample data Jing Guo normalized is led
Constituent analysis extracts principal component of the contribution rate of accumulative total more than the second preset quantity of preset threshold；And
It obtains the corresponding characteristic value of principal component of second preset quantity and is weighted, calculate separately each second user
Scoring.
4. method for allocating tasks according to claim 3, which is characterized in that described " to the sample Jing Guo normalized
Data carry out principal component analysis, extract principal component of the contribution rate of accumulative total more than the second preset quantity of preset threshold " the step of
Include:
The sample data after normalized is obtained, the covariance square of the sample data after normalized is calculated
Battle array；
Eigenvalues Decomposition is carried out to the covariance matrix, obtains multiple characteristic values and corresponding feature vector；And
Descending sort is carried out according to the size of the multiple characteristic value, the characteristic value pair for selecting the sequence of the second preset quantity forward
The feature vector answered is as principal component.
5. method for allocating tasks as claimed in any of claims 1 to 4, which is characterized in that step S5 further include:
When second user identical there are multiple User Status in the second user of preset quantity, multiple user is obtained respectively
The waiting task amount of the identical second user of state；And
Select the smallest second user of waiting task amount as target from the identical second user of the multiple User Status
Object.
6. method for allocating tasks according to claim 5, which is characterized in that this method further include:
When the assigned task of target object refusal processing, one second is reselected according to online, stealthy, offline sequence
User reassigns to the new target object as new target object, by the task, and allocation result is fed back to first
User and new target object；Or
If target object does not respond assigned task in target response timeliness, alternatively, if target object is not solved in target
The assigned task of ageing treatment, generates warning information.
7. a kind of electronic device, which is characterized in that the device includes: memory, processor, and being stored on the memory can be
The task distribution program run on the processor, it can be achieved that as follows when the task distribution program is executed by the processor
Step:
A1, the receiving the first user submission of the task report request, report request to correspond to the task according to default classifying rules
Task classify, and for the task mark the first label；
A2, the second label for obtaining specified object, it is one or more corresponding to filter out the second label comprising first label
A specified object is as second user；
A3, when there are multiple second users, obtain the scoring reference index of the multiple second user, according to default scoring advise
The scoring for then calculating the multiple second user filters out the highest second user of scoring of preset quantity；
A4, obtain the preset quantity second user preset kind, the preset quantity is judged according to default judgment rule
Second user User Status, comprising: it is online, stealthy, offline；And
A5, successively to select User Status be online, stealthy second user as target object, and the task is distributed to the mesh
Object is marked, and allocation result is fed back into the first user and target object.
8. electronic device according to claim 7, which is characterized in that described " according to default judgment rule in step A4
Judge the User Status of the second user of the preset quantity " include:
When the second user does not have operation note on appointing system within a preset time, the state of the second user is judged
To be offline, otherwise judge whether the second user has conference journey in current time；
When the second user is when current time has conference journey, judge the User Status of the second user to be stealthy, otherwise,
Judge whether attendance location information of the second user on the day of is not inconsistent with its preset attendance location information；And
When attendance location information of the second user on the day of and its preset attendance location information are not inconsistent, judge this second
The state of user be it is offline, otherwise, judge that the User Status of the second user is online.
9. electronic device according to claim 7 or 8, which is characterized in that the task distribution program is by the processor
When execution, following steps are also realized:
When the assigned task of target object refusal processing, one second is reselected according to online, stealthy, offline sequence
User reassigns to the new target object as new target object, by the task, and allocation result is fed back to first
User and new target object；Or
If target object does not respond assigned task in target response timeliness, alternatively, if target object is not solved in target
The assigned task of ageing treatment, generates warning information.
10. a kind of computer readable storage medium, which is characterized in that include that task is distributed in the computer readable storage medium
Program, it can be achieved that task as described in any one of claim 1 to 6 when the task distribution program is executed by processor
The step of distribution method.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110084498A (en) * | 2019-04-18 | 2019-08-02 | 深圳前海微众银行股份有限公司 | A kind of work dispatching method of server-side, device, computer equipment and storage medium |
| CN110414862A (en) * | 2019-08-05 | 2019-11-05 | 中国工商银行股份有限公司 | Task regulation method and device based on disaggregated model |
| CN110428125A (en) * | 2019-06-14 | 2019-11-08 | 平安科技（深圳）有限公司 | A kind of project evaluation method, apparatus, computer equipment and storage medium |
| CN110443476A (en) * | 2019-07-23 | 2019-11-12 | 国家计算机网络与信息安全管理中心 | The method for allocating tasks and system of knowledge based mark evaluation |
| CN110648047A (en) * | 2019-08-16 | 2020-01-03 | 深圳市轱辘汽车维修技术有限公司 | Task scheduling method, device, system and storage medium |
| CN110942244A (en) * | 2019-11-22 | 2020-03-31 | 北京金山云网络技术有限公司 | Work order distribution method and device, electronic equipment and storage medium |
| CN111198986A (en) * | 2019-12-17 | 2020-05-26 | 中国平安人寿保险股份有限公司 | Information sending method and device, electronic equipment and storage medium |
| CN111639846A (en) * | 2020-05-24 | 2020-09-08 | 中信银行股份有限公司 | Demand processing method and device, electronic equipment and computer readable storage medium |
| CN111784186A (en) * | 2020-07-14 | 2020-10-16 | 武汉空心科技有限公司 | Task allocation method for multi-role user of working platform |
| CN111930476A (en) * | 2019-05-13 | 2020-11-13 | 百度(中国)有限公司 | Task scheduling method and device and electronic equipment |
| CN112308401A (en) * | 2020-10-29 | 2021-02-02 | 多点(深圳)数字科技有限公司 | Task allocation method and device, computer equipment and readable storage medium |
| CN113065780A (en) * | 2021-04-09 | 2021-07-02 | 平安国际智慧城市科技股份有限公司 | Task allocation method, device, storage medium and computer equipment |
| CN114116182A (en) * | 2022-01-28 | 2022-03-01 | 南昌协达科技发展有限公司 | Disinfection task allocation method and device, storage medium and equipment |
| CN118505170A (en) * | 2024-07-19 | 2024-08-16 | 万思信息技术有限公司 | Mobile office service method and platform based on BPM |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1519550A1 (en) * | 2003-09-26 | 2005-03-30 | Avaya Technology Corp. | Method and apparatus for assessing the status of work waiting for service |
| US20110218927A1 (en) * | 2010-03-05 | 2011-09-08 | Oracle International Corporation | Compensation patterns for adjusting long running order management fulfillment processes in an distributed order orchestration system |
| CN107590588A (en) * | 2017-08-24 | 2018-01-16 | 平安科技（深圳）有限公司 | Method for allocating tasks, device and computer-readable recording medium |
| CN107679740A (en) * | 2017-09-28 | 2018-02-09 | 平安科技（深圳）有限公司 | Business personnel's screening and activating method, electronic installation and computer-readable recording medium |
| CN107967555A (en) * | 2017-11-15 | 2018-04-27 | 平安科技（深圳）有限公司 | Employee individual's attendance management-control method, application server and computer-readable recording medium |
-
2018
- 2018-08-21 CN CN201810954379.8A patent/CN109242275A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1519550A1 (en) * | 2003-09-26 | 2005-03-30 | Avaya Technology Corp. | Method and apparatus for assessing the status of work waiting for service |
| US20110218927A1 (en) * | 2010-03-05 | 2011-09-08 | Oracle International Corporation | Compensation patterns for adjusting long running order management fulfillment processes in an distributed order orchestration system |
| CN107590588A (en) * | 2017-08-24 | 2018-01-16 | 平安科技（深圳）有限公司 | Method for allocating tasks, device and computer-readable recording medium |
| CN107679740A (en) * | 2017-09-28 | 2018-02-09 | 平安科技（深圳）有限公司 | Business personnel's screening and activating method, electronic installation and computer-readable recording medium |
| CN107967555A (en) * | 2017-11-15 | 2018-04-27 | 平安科技（深圳）有限公司 | Employee individual's attendance management-control method, application server and computer-readable recording medium |
Non-Patent Citations (1)
| Title |
|---|
| 姚树春 等: "《大数据技术与应用》", 30 June 2018 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110084498A (en) * | 2019-04-18 | 2019-08-02 | 深圳前海微众银行股份有限公司 | A kind of work dispatching method of server-side, device, computer equipment and storage medium |
| CN110084498B (en) * | 2019-04-18 | 2024-07-23 | 深圳前海微众银行股份有限公司 | Service end dispatching method and device, computer equipment and storage medium |
| WO2020211529A1 (en) * | 2019-04-18 | 2020-10-22 | 深圳前海微众银行股份有限公司 | Dispatching method and device for server sides, computer equipment and storage medium |
| CN111930476B (en) * | 2019-05-13 | 2024-02-27 | 百度(中国)有限公司 | Task scheduling method and device and electronic equipment |
| CN111930476A (en) * | 2019-05-13 | 2020-11-13 | 百度(中国)有限公司 | Task scheduling method and device and electronic equipment |
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| CN110648047A (en) * | 2019-08-16 | 2020-01-03 | 深圳市轱辘汽车维修技术有限公司 | Task scheduling method, device, system and storage medium |
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