CN114943443A

CN114943443A - Work order distribution method, device, equipment and storage medium

Info

Publication number: CN114943443A
Application number: CN202210545527.7A
Authority: CN
Inventors: 李姗姗; 许建宏; 李涛; 方虬
Original assignee: China United Network Communications Group Co Ltd
Current assignee: China United Network Communications Group Co Ltd
Priority date: 2022-05-19
Filing date: 2022-05-19
Publication date: 2022-08-26

Abstract

The application discloses a work order distribution method, a device, equipment and a storage medium, which relate to the field of cloud computing, and the work order distribution method comprises the following steps: acquiring work order characteristic information, wherein the work order characteristic information is used for representing information technology IT problem type information, IT system level information and user portrait information of an IT problem influencing user corresponding to a work order; calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing user through a preset algorithm, wherein the work order service index value is used for representing the service level required by the work order; sending a work order to a target processing node; the problem that the work order distribution method of the traditional IT problem is low in efficiency is solved.

Description

Work order distribution method, device, equipment and storage medium

Technical Field

The present application relates to the field of cloud computing, and in particular, to a work order allocation method, apparatus, device, and storage medium.

Background

Information Technology (IT) problems existing in production and operation of telecommunication operators refer to various IT problems such as IT system problems found by front-line IT personnel such as marketing delivery personnel and operation management personnel in working scenes such as business marketing acceptance, daily management, production, operation and maintenance and the like or problems and errors in system use. With the evolution of the IT architecture of the telecom operator to the middle station architecture, the traditional IT problem work order distribution method cannot meet the IT architecture requirement of the existing telecom operator.

The traditional IT problem work order distribution method is generally distributed manually, depends on the experience of operation and maintenance personnel, and is low in efficiency.

Disclosure of Invention

The embodiment of the application provides a work order distribution method, a work order distribution device, equipment and a storage medium, and solves the problem that the work order distribution method of the traditional IT problem is low in efficiency.

In order to achieve the technical purpose, the embodiment of the application adopts the following technical scheme:

in a first aspect, an embodiment of the present application provides a work order allocation method, including:

acquiring work order characteristic information, wherein the work order characteristic information is used for representing information technology IT problem type information, IT system level information and user portrait information of an IT problem influencing user corresponding to a work order;

calculating a work order service index value according to IT system level information and user portrait information of IT problems influencing users through a preset algorithm, wherein the work order service index value is used for representing the service level required by a work order;

sending a work order to a target processing node; each processing node corresponds to one processing person, the target processing node corresponds to a target processing person, the target processing person is selected from a list of processing persons corresponding to the IT problem type information, and the processing person score of the target processing person is matched with the work order service index value.

In the embodiment of the application, the work order characteristic information is obtained firstly, then the work order service index value used for representing the service level required by the work order is calculated according to the IT system level information and the user portrait information of the IT problem influence user through a preset algorithm, finally the work order is sent to the target processing node, the target processing node corresponds to the target processing person, the target processing person is selected from the list of the processing persons corresponding to the IT problem type information, the score of the processing person of the target processing person is matched with the work order service index value, the processing capability corresponding to the processing node allocated to the work order can meet the work order processing requirement, the automatic allocation of the work order is realized, and the matching degree of the work order allocation and the processing person and the work order allocation efficiency are improved.

In one embodiment, the method further comprises:

under the condition of receiving an automatic processing instruction sent by a target processing node, inquiring a solution of a work order from a preset knowledge base according to the work order; the preset knowledge base is generated by constructing a knowledge graph through a historical work order and a solution of the historical work order;

and calling the operation and maintenance service to execute a solution so as to solve the IT problem corresponding to the work order.

In one embodiment, user profile information includes a range of issues affecting users, a type of issue affecting users, and a propensity for an issue to cause a user to complain;

calculating a work order service index value according to IT system level information and user portrait information of IT problems influencing users by a preset algorithm, wherein the work order service index value comprises the following steps:

the problem influence user range, the problem influence user type, the problem cause user complaint tendency and the IT system level information are respectively converted into binary codes through a preset conversion rule;

and converting the binary codes into quantized data which can be used for comparing sizes through a preset conversion algorithm to obtain a work order service index value.

In one embodiment, the work order service indicator value is calculated by the following equation:

wherein S represents the index value of the work order service, k represents the type of the work order characteristic information corresponding to the binary code, a _i Represents any one of the code values in the binary code, and i represents the number of codes in the binary code.

In one embodiment, prior to sending the work order feature information to the target processing node, the method further comprises:

acquiring a work order solving efficiency index and a work order solving quality index of a processing person;

and calculating the score of the processor according to the work order solution efficiency index and the work order solution quality index by a preset scoring algorithm.

In one embodiment, obtaining work order characterization information includes:

sending a preset work order template to the operation and maintenance node; the operation and maintenance node corresponds to the operation and maintenance personnel, and the preset work order template requires the operation and maintenance personnel to input the following information: problem description, problem error prompt screenshot, problem reproduction video and an IT system with problems;

receiving a preset work order template which is input;

and analyzing the IT problem type information represented by the input preset work order template, the IT system level information and the user portrait information of the IT problem influencing users through a preset analysis algorithm to obtain work order characteristic information.

In one embodiment, the method further comprises:

and sending the work order characteristic information to a new target processing node under the condition that the received times of sending the order returning information by the target processing node meet a preset order returning threshold value.

In one embodiment, the method further comprises:

recording the processing time of the target processing node for processing the work order characteristic information;

and when the processing time exceeds the preset reminding time limit, generating reminding information and sending the reminding information to the target processing node.

In a second aspect, an embodiment of the present application provides a work order distribution apparatus, including:

the acquisition module is used for acquiring work order characteristic information which is used for representing information technology IT problem type information, IT system level information and user portrait information of an IT problem influencing user corresponding to the work order;

the calculation module is used for calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm, and the work order service index value is used for representing the service level required by the work order;

the sending module is used for sending the work order to the target processing node; each processing node corresponds to one processing person, the target processing node corresponds to a target processing person, the target processing person is selected from a list of processing persons corresponding to the IT problem type information, and the processing person score of the target processing person is matched with the work order service index value.

In one embodiment, the apparatus further comprises a query module and a call module.

And the query module is used for querying the solution of the work order to the preset knowledge base according to the work order under the condition of receiving the automatic processing instruction sent by the target processing node. The preset knowledge base is generated by constructing a knowledge graph through historical work orders and solutions of the historical work orders.

And the calling module is used for calling the operation and maintenance service to execute the solution so as to solve the IT problem corresponding to the work order.

In one embodiment, the user profile information includes a range of issues affecting users, a type of issue affecting users, and a propensity for the issue to cause a user to complain.

The calculating module 820 is specifically configured to:

and respectively converting the problem influence user range, the problem influence user type, the problem cause user complaint tendency and the IT system level information into binary codes by preset conversion rules.

In one embodiment, the work order service indicator value is calculated by the following formula:

wherein S represents a work order service index value, k represents the type of the work order characteristic information corresponding to the binary code, a _i Represents any one of the code values in the binary code, and i represents the number of codes in the binary code.

In one embodiment, the obtaining module 810 is further configured to obtain a work order solution efficiency index and a work order solution quality index of the processing person before sending the work order feature information to the target processing node.

And the calculating module 820 is further configured to calculate the score of the handler according to the work order solution efficiency index and the work order solution quality index through a preset scoring algorithm.

In an embodiment, the obtaining module 810 is specifically configured to:

and sending a preset work order template to the operation and maintenance node. The operation and maintenance node corresponds to the operation and maintenance personnel, and the preset work order template requires the operation and maintenance personnel to input the following information: problem description, problem error prompt screenshots, problem recurrence videos, and IT systems where problems occur.

And receiving the preset work order template which is input.

And analyzing the IT problem type information, the IT system level information and the user portrait information of the IT problem influencing users represented by the input preset work order template through a preset analysis algorithm to obtain work order characteristic information.

In an embodiment, the sending module 830 is further configured to send the work order feature information to a new target processing node when the number of times that the target processing node sends the order refund information is received meets a preset order refund threshold.

In one embodiment, the apparatus further comprises a recording module and a generating module.

And the recording module is used for recording the processing time of the target processing node for processing the work order characteristic information.

And the generating module is used for generating reminding information when the processing time exceeds the preset reminding time limit.

The sending module 830 is further configured to send a reminding message to the target processing node.

In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the work order assignment method as provided in the first aspect above.

In a fourth aspect, the present application provides a computer-readable storage medium storing an implementation program for information transfer, where the program is executed by a processor to implement the work order allocation method provided in the first aspect.

In a fifth aspect, the present application provides a computer program product for causing a computer to perform the method as provided in the first aspect above when the computer program product is run on the computer.

The beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect in the present application may refer to the beneficial effect analysis of the first aspect, and are not described herein again.

Drawings

Fig. 1 is a schematic structural diagram of a work order distribution system according to an embodiment of the present disclosure;

fig. 2 is a schematic diagram illustrating an execution flow of a problem self-service acceptance module according to an embodiment of the present disclosure;

fig. 3 is a schematic diagram illustrating an execution flow of a work order service SLA module according to an embodiment of the present application;

fig. 4 is a schematic diagram of a binary encoding according to an embodiment of the present application;

fig. 5 is a schematic diagram illustrating an execution flow of a personnel ability matching module according to an embodiment of the present application;

fig. 6 is a schematic flowchart of an execution of an intelligent problem diagnosis module according to an embodiment of the present application;

fig. 7 is a schematic flowchart of a work order allocation method according to an embodiment of the present application;

fig. 8 is a schematic structural diagram of a work order distribution device according to an embodiment of the present disclosure;

fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.

It is to be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions; nor is it to be understood that relative importance is indicated or implied or that the number of technical features indicated is implicitly indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present embodiment, "a plurality" means two or more unless otherwise specified. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

Traditional IT problem work order is generally dispatched by the manual work, relies on the operation and maintenance personnel experience, and efficiency is lower, embodies in following several aspects: problem positioning requires interaction between operation and maintenance personnel and users for many times, and user dissatisfaction is easily caused; the work order is supported slowly, and the response speed depends on manual input seriously; the work order cross system and the cross unit transfer need manual intervention, and the transfer time is long; the work order problem treatment depends on the experience of operation and maintenance personnel, and the problem repair is time-consuming and labor-consuming; user service awareness cannot be quantified, and differentiated services are not provided.

In order to solve the above problem, an embodiment of the present application provides a work order allocation method, where the work order allocation method is applied to a work order allocation system provided in the embodiment of the present application, and as shown in fig. 1, the work order allocation system may include: the system comprises an Artificial Intelligence (AI) basic platform, a problem self-Service acceptance module, a Service Level Agreement (SLA) module, a personnel ability matching module and a problem intelligent diagnosis module.

The following describes an AI base platform in the work order distribution system shown in fig. 1, where the AI base platform is used to:

the method provides machine learning framework, algorithm, software and hardware training environment and the like which are common in the industry, and provides data acquisition, data labeling, off-line model training and optimization, problem knowledge base construction and model deployment capabilities by docking a data center. Specifically, IT solidifies the IT problems and solutions appearing in the daily operation and maintenance into knowledge, and expresses and retrieves the knowledge through the knowledge map to form a problem knowledge base (such as a system problem knowledge base, an enterprise problem knowledge base or an industry problem knowledge base); and the solution output by the problem knowledge base is matched with the operation and maintenance service, and the operation and maintenance service of different solutions can be configured in advance. The operation and maintenance service is called to perform adaptation, issuing, execution, feedback management and the like on the network/middle station operation instruction, so that the execution of the solution is realized. And automatic data restoration, automatic parameter configuration, system troubleshooting and the like are supported. Training and optimizing the intention recognition model to automatically accept the problems, and deploying the intention recognition model to an automatic acceptance module.

The following describes a problem self-service acceptance module in the work order distribution system shown in fig. 1, where the problem self-service acceptance module is configured to:

the IT operation and maintenance personnel are required to submit relevant information of the IT questions on line through a question and answer robot guide session and a work order template recommendation mode in the self-service acceptance module, such as order numbers, question description, question error prompt screenshots, question reproduction videos and an IT system with problems. And then, formatting the work order by using the intention recognition model, and supporting the online processing of all links such as end-to-end full-flow self-service acceptance of the IT problem, intelligent processing, work order satisfaction evaluation and the like.

Further, an execution flow of the problem self-service acceptance module is shown in fig. 2, and includes:

1. the problem self-service acceptance module requires operation and maintenance personnel to define the work order template field in advance. The field requiring operation and maintenance staff to submit online in the work order template comprises the following steps: problem order numbering, simple problem description, problem error prompt screenshot, problem reproduction video and problem occurrence system.

2. And formatting the work order and perfecting the work order information. Automatically acquiring data center data according to the problem order number to portray a user, extracting keywords for problem character description in a work order template, performing image feature analysis on an error prompt screenshot and a problem reproduction video in the work order template, finally finishing formatting and sorting of submitted work order template contents, and outputting the following work order feature information: the problem belongs to an IT support domain, the problem affects the range of users, the problem affects the types of the users, and the problem causes the complaint tendency of the users.

Further, the work order characteristic information is explained:

the IT support domain to which the problem belongs is determined before the system is put into production and operation, and the IT support domain to which the system problem belongs is divided into three categories according to the IT support domain to which the system belongs:

the public business problems comprise IT problems of public product application, approval, configuration and the like. And the government and enterprise business problems comprise IT problems of government and enterprise business acceptance, accounting, resource allocation and the like. Production Operation type problems include IT problems related to a service Support System (BSS), a Management Support System (MSS), an Operation Support System (OSS), and a Decision Support System (DSS).

The problem affects the user range: the method is classified according to the range of users influenced by IT problems, and mainly comprises three categories of nationwide users, partial users and individual users.

The problem affects the user type: the method is classified according to the types of users influenced by IT problems, and mainly comprises three types, namely major users, major users and common users.

The problem leads to a user complaint tendency: the classification refers to classification of potential complaint risk conditions of users caused by IT problems, and is mainly divided into three categories, namely complaint tendency of users, complaint tendency of users and immediate processing which is not required when users wait.

3. And calling the capacity of the intelligent diagnosis module, inquiring a solution, and executing the solution through the operation and maintenance service to solve the IT problem corresponding to the work order.

4. Evaluation of work order satisfaction: and after the problem is processed, the operation and maintenance personnel perform closed order evaluation on the solution result.

The following describes a work order service SLA module configured to:

calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users; and recording the manual processing duration of the processing node, sending early warning and warning notices to the overtime work orders or overtime work orders, and dispatching the work orders returned for multiple times.

Further, in the work order distribution system, an execution flow of the work order service SLA module is shown in fig. 3, and includes:

(1) and analyzing the formatted work order and inputting the work order as the data of the work order service index value.

(2) Binary coding is carried out on the analysis result in the step 1 by adopting an integer variable function int12, the binary coding is shown in fig. 4, and the binary coding is represented in a form of IT system level information coding (3bit) + problem influence user range coding (3bit) + problem influence user type coding (3bit) + problem cause user complaint tendency coding (3 bit).

(3) And converting the 12-bit binary code into a decimal integer to obtain the work order service index value.

In the binary coding representation, when each bit takes a value of 0, the representation is not the type, and when the value takes a value of 1, the representation is the type. For example: the 3bit is 100 when the IT system level is the core system, 010 when the IT system level is the important system, and 001 when the IT system level is the general system.

(4) According to the size of the work order service index value, the work order service index is divided into three levels, including: general, urgent; the higher the work order service index level, the higher the processing priority. For example, when the IT system level of the work order is an important system, the problem affecting user range is a partial user, the problem affecting user type is a common user, and the problem causes a user complaint tendency to be a complaint tendency, the binary code of the work order characteristic is represented as follows: 010-.

(5) And setting different manual processing time limit requirements aiming at different work orders. As shown in table 1, the manual processing time limit requirement may include the following items:

TABLE 1

Specifically, the method comprises the following steps:

the intelligent diagnosis scheme evaluation time limit: the processing time from the first order dispatch of the work order to the feasibility evaluation of the intelligent diagnosis solution by the operation and maintenance personnel to the evaluation suggestion given by the operation and maintenance personnel or the upgrading to the difficult and complicated work order is long.

Time limit of difficult work order response: the processing time from the time when the difficult work order is claimed to the time when the operation and maintenance personnel replies the solution or puts forward the BUG BUG/demand research and judgment requirement is long.

BUG/demand study and judgment time limit: and the operation and maintenance personnel transfer the difficult work orders which are preliminarily judged as system BUG or requirement problems to the research and development team, enter a research and judgment link, and all the research and development team experts finish judgment operation and give an analysis conclusion and transfer the work orders to the accumulated time of the operation and maintenance personnel.

BUG/demand conclusion reply time limit: and transferring the difficult work orders judged to be the BUG or the demand problem to the operation and maintenance personnel from the research and development team to the operation and maintenance personnel for replying the temporary solution of the user.

(6) And monitoring the work order, detecting manual processing time length data and work order returning times of each link of the IT problem work order flow from the database, and calculating the distribution condition of the manual processing time length time vector of the work order.

(7) And (4) judging whether the manual processing time length distribution of each link in the work order flow reaches a time limit threshold or a time limit requirement, if not, continuing to execute the step 8, and if so, jumping to the step 9.

Illustratively, the time limit threshold may be set to three-quarters of the time limit requirement for the corresponding manual handling.

(8) And (5) judging whether the work order flow reaches a work order back-off frequency threshold value, if not, jumping to the step 6, and if so, jumping to the step 10.

(9) And sending early warning and warning notice to the time-out work order.

Illustratively, an urging reminder can be sent to the processing node according to a certain frequency aiming at an overtime work order in the modes of short message, mail, online group and the like; and (4) aiming at the overtime work order, except for sending the prompt handling prompt, a handler corresponding to the processing node needs to feed back the reason of the overtime.

(10) And calling the capability of the personnel capability matching module aiming at the multiple work orders of the returned work orders, and throwing the work orders again to the matched processing nodes for processing.

The following describes a person ability matching module, which is used to:

and according to the work order service index value, determining a target handler matched with the work order service index value, and distributing the work order to a target processing node corresponding to the target handler for the target handler to process the work order.

Further, the flow executed by the human ability matching module is shown in fig. 5, and includes:

(1) historical data of the worker solution work order capability is read from a database, and the three dimensions including the personnel capability label, the problem response efficiency and the service quality can be considered, so that the work order solution efficiency index and the work order solution quality index of a processor are finally obtained.

For example, the work order resolution efficiency indicators may include: 2 hours acceptance timeliness rate, 1 working day solution rate, average delivery duration and other indexes. The quality index of work order solution may include: and evaluating the indexes such as satisfaction degree and work order resolution rate of the work order.

(2) And calculating the capability score of the processing person in real time according to the work order solution efficiency index and the work order solution quality index.

(3) The personnel ability score is fully divided into 100 scores, and the personnel ability grades are divided into different grades according to the scores, such as the grade of Xinrui, backbone and expert. For example, when the human ability score is not less than 80 minutes, the human ability level is expert; when the personnel ability score is not less than 60 minutes, the personnel ability level is a backbone level; when the human ability score is below 60 minutes, the human ability level is a new sharp level.

(4) And analyzing the formatted work order, and determining the IT support domain to which the problem of the work order belongs and the qualitative classification of the problem. The personnel competency label data includes an IT support domain to which the adequacy issue belongs, and a qualitative classification of the adequacy issue. And matching the personnel capacity label with the work order attribute, and selecting the personnel with higher matching degree as the alternative personnel.

(5) And calling the ability of the SLA module to determine the work order service index level of the work order, and matching the personnel ability level of the alternative processor with the work order service index level.

Illustratively, in order to improve the work order processing efficiency, the matching principle is as follows: the expert preferentially processes the work orders with the work order service index level as urgent, the backbone personnel preferentially processes the work orders with the work order service index level as urgent, and the new keen personnel preferentially processes the work orders with the work order service index level as general; meanwhile, the upward compatibility principle is considered, and under the condition that the personnel capacity is in short supply, low-level other personnel can process the work orders with higher work order service index levels.

(6) And allocating the work order to the alternative personnel with the highest personnel capacity score and the highest matching degree to finish automatic order dispatching.

The following describes the problem intelligent diagnosis module, which is used for:

and under the condition of receiving an automatic processing instruction sent by the target processing node, generating a solution of the work order by using a knowledge graph technology, or throwing the work order to perform manual processing.

Further, the flow executed by the problem intelligent diagnosis module may be as shown in fig. 6, and includes:

1. and reading the input preset work order template from the database, wherein the input preset work order template is formatted chemical order information.

2. And classifying the causes of the problems by utilizing a decision tree model according to the information such as the problem order number, the problem characteristics, the IT support domain to which the problems belong and the like of the formatted work order information, namely determining the type information of the IT problems.

Illustratively, the IT issue type information may include the IT support domain to which the issue of the work order belongs and the qualitative classification of the issue. The handler may also preset tag data that may include the IT support domain to which the adequacy issue belongs, the qualitative classification of the adequacy issue. The problem qualitative classification is mainly divided into a consultation operation class, a data restoration class, a parameter configuration class, a program BUG class, a requirement rule class and a platform architecture class, wherein:

the consulting operation class: problems arise from the operation.

Data repair class: non-program BUG problem data repair.

Parameter configuration class: problems caused by parameter mismatch, errors, etc.

Program BUG type: which is characterized as a problem of program defects.

Requirement rules: the system has the problem of doubtful system realization due to clear requirement numbers.

Platform architecture class: the problem that the platform architecture and the system capability are not satisfied and cannot be solved temporarily.

3. And inquiring a solution from the enterprise problem knowledge base according to the problem characteristics of the work order and the problem qualitative classification data.

The enterprise problem knowledge base is used for solidifying problem work order information, solutions and operation and maintenance services appearing in daily operation and maintenance into knowledge, and the knowledge is expressed and retrieved by adopting a knowledge map technology and utilizing a map database and a machine learning technology.

4. And calling the service SLA module capability to calculate the work order service index level and monitor the work order flow.

5. And calling the capability of the personnel capability matching module, calculating the matching degree of the work order service index level and the personnel capability, and getting the solution off to the handler with capability matching.

6. And (4) judging the feasibility of the solution by the processor, if the solution is feasible, continuing to the step 7, and if the solution is not feasible, jumping to the step 8.

7. And matching the solution with an operation and maintenance scene, and automatically processing the work order problem after matching.

The solution output by the problem knowledge base is matched with the operation and maintenance service, and the operation and maintenance service of different solutions can be configured in advance. The operation and maintenance service is called to perform adaptation, issuing, execution, feedback management and the like on the network/middle desk operation instruction, so that the execution of the solution is realized, and the IT problem corresponding to the work order is solved.

8. Upgrading the problem to a difficult problem, updating formatted chemical order information, marking the type of the work order as a difficult work order, and leading the current processor to be responsible for problem processing.

9. And receiving a problem processing result, calling the capability of an AI basic platform, correcting the enterprise problem knowledge base, optimizing the model and finishing IT problem knowledge storage.

In the embodiment of the application, through the functional design of each module of the work order distribution system, the automatic distribution of the work orders can be realized, the processing manual capacity corresponding to the processing node of the work order distribution can meet the work order processing requirement, and the matching degree of the work order distribution and the processing manual and the work order distribution efficiency are improved.

Fig. 1-6 illustrate a work order distribution system provided by an embodiment of the present application, which may be installed in a computer, a server, or other electronic device with data processing capability. The server may be a single server, or may be a server cluster including a plurality of servers. In some embodiments, the server cluster may also be a distributed cluster. Based on the work order distribution system, the embodiment of the application also provides a work order distribution method, and fig. 7 shows a flow diagram of the method.

As shown in fig. 7, the method may include the steps of:

and S710, acquiring the characteristic information of the work order.

The work order characteristic information can be obtained from the work order, and is used for representing information technology IT problem type information, IT system level information and user portrait information of IT problem influence users corresponding to the work order.

S720, calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm.

The IT system level information and the user portrait information of the IT problem influence user can represent the service level required by the work order, and the work order service index value representing the service level required by the work order can be calculated by taking the IT system level information and the user portrait information of the IT problem influence user as calculation parameters.

And S730, sending the work order to the target processing node.

Each processing node corresponds to one processing person, the target processing node corresponds to the target processing person, and the target processing person is selected from a list of the processing persons corresponding to the IT problem type information. The handler score of the target handler is matched to the work order service index value.

Illustratively, the IT issue type information may include the IT support domain to which the issue of the work order belongs and the qualitative classification of the issue. The handler may also preset tag data that may include the IT support domain to which the adequacy issue belongs, the qualitative classification of the adequacy issue. And a corresponding list of the handlers can be preset according to the tag data, and the list of the handlers corresponding to the IT problem type information is determined according to the matching compatibility of the IT problem type information and the tag data.

Illustratively, the IT support domain to which the problem of the work order belongs can be divided into three categories:

1) the public business problems comprise IT problems of public product application, approval, configuration and the like.

2) And the government and enterprise business problems comprise IT problems of government and enterprise business acceptance, accounting, resource allocation and the like.

3) The production Operation problem includes IT problems related to a Business Support System (BSS), a Management Support System (MSS), an Operation Support System (OSS), and a Decision Support System (DSS).

Illustratively, the problem qualitative classification can be classified into a consultation operation class, a data repair class, a parameter configuration class, a program BUG class, a requirement rule class, and a platform architecture class, wherein:

(1) the consulting operation class: problems arise from the operation.

(2) Data repair class: and repairing non-program BUG problem data.

(3) Parameter configuration class: problems caused by parameter mismatch, errors, etc.

(4) Program BUG type: which is characterized as a problem of program defects.

(5) Requirement rules: the system has the problem of doubtful system realization due to clear requirement numbers.

(6) Platform architecture class: the problem that the platform architecture and the system capability are not satisfied and cannot be solved temporarily.

In one embodiment, the method may further comprise:

and S740, under the condition that the automatic processing instruction sent by the target processing node is received, inquiring the solution of the work order from the preset knowledge base according to the work order.

The preset knowledge base is generated by constructing a knowledge graph through a historical work order and a solution of the historical work order. Specifically, the IT problem work orders and solutions appearing in daily operation and maintenance can be solidified into knowledge, and the knowledge is expressed and retrieved through the knowledge map to form a knowledge base.

And S750, calling the operation and maintenance service to execute a solution so as to solve the IT problem corresponding to the work order.

Wherein, the operation and maintenance services of different solutions can be configured in advance. The operation and maintenance service is called to perform adaptation, issuing, execution, feedback management and the like on the network/middle desk operation instruction, so that the execution of the solution is realized, and the IT problem corresponding to the work order is solved.

As shown in fig. 4, the problem influence user range is a range of users influenced by the work order recording IT problem, and may be exemplarily divided into: national users, partial users and individual users. The problem influence user type is a user type influenced by the work order record IT problem, and illustratively, the problem influence user type can be divided into three types, namely major users, major users and common users. The problem causes the complaint tendency of the user, namely the situation that the potential complaint risk exists in the user caused by the IT problem of the work order record, which can be exemplarily divided into three types, namely that the user has the complaint tendency, and the user can wait and does not require immediate processing.

Further, as shown in fig. 4, the IT system level information records the importance degree of the IT problem related to the system for the work order, and exemplarily, the information can be divided into three categories, namely, a core system, an important system and a general system.

Based on the above specific division of the user portrait information and the IT system level information, S720: calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm, wherein the calculation comprises the following steps:

s7201, a problem influence user range, a problem influence user type, a problem cause user complaint tendency and IT system level information are respectively converted into binary codes through a preset conversion rule.

The preset conversion rule has the function of converting information into binary codes, and by applying the preset conversion rule, the user scope influenced by problems, the user type influenced by problems, the user complaint tendency caused by problems and the IT system level information can be respectively converted into the binary codes.

Further, based on that the problem affects the user range, the problem affects the user type, the problem causes the user complaint tendency, and the specific classification of IT system level information is different, the converted binary codes are also different, in the binary code conversion expression, when each bit takes a value of 0, the binary code is not the type, and when the value takes a value of 1, the binary code is the type, exemplarily, when the problem affects the user range to be national users, the converted binary code is 100; if the problem affects the user range to some users, the converted binary code is 010. The same principle of the binary coding conversion mode of the information of the IT system level is that problems affect the user type, cause the complaint tendency of the user due to the problems, and are not repeated.

Illustratively, as shown in fig. 4, a problem affects a user range, a problem affects a user type, a problem causes a user complaint tendency, and IT system level information, each of the information may be subdivided into three types, which are 12 types, and during encoding, the information may be encoded into 12-bit binary codes, and the problem affects the user range, the problem affects the user type, the problem causes the user complaint tendency, and the IT system level information occupies 3 bits each, and then the 12-bit binary codes are applied to perform the conversion of the quantized data.

S7202, converting the binary codes into quantized data which can be used for comparing sizes through a preset conversion algorithm, and obtaining a work order service index value.

The preset conversion algorithm has the function of converting binary codes into quantized data which can be used for comparing sizes, and can convert the binary codes into the quantized data which can be used for comparing sizes by applying the preset conversion algorithm, so that the work order service index value is obtained.

In the embodiment of the application, in order to enable the work order service index value to be automatically carried out, a preset conversion rule and a preset conversion algorithm are configured in advance, the problem influences the user range, the problem influences the user type, the user complaint tendency caused by the problem and the IT system level information are respectively converted into binary codes through the preset conversion rule, then the binary codes are converted into quantized data which can be used for comparing the sizes through the preset conversion algorithm, the work order service index value is obtained, the quantization of the work order service index value is realized, and then the work order service index value can be applied to determine a target handler matched with the work order.

s represents a work order service index value, k represents the type of the work order characteristic information corresponding to the binary code, the value range of k is 0-3, and the four types of the work order characteristic information correspond to a problem influence user range, a problem influence user type, a problem cause user complaint tendency and IT system level information respectively; a is _i Represents any one of the code values in the binary code, and i represents the number of codes in the binary code. Based on the formula, the work order service index value of the decimal integer can be calculated according to the binary coding.

Illustratively, the actual value calculated according to the work order service index value may be divided into three levels, i.e., general, urgent and urgent, in which: if the work order service index value is equal to 4, the work order service index value is general; if the work order service index value is greater than 4 and not greater than 8, the emergency is determined; and if the work order service index value is more than 8 and not more than 16, the work order service index value is urgent. According to the work order service index level, corresponding handlers can be matched.

Illustratively, when the IT system level information is an important system, the problem influence user range is a partial user, the problem influence user type is a common user, and the problem causes a user complaint tendency to be a complaint tendency, the binary code is expressed as follows: 010-.

In the embodiment of the application, the binary code is converted into the quantized data which can be used for comparing the sizes by designing the formula with the function of quantizing the binary code, so that the work order service index value is obtained, the quantization of the work order service index value is realized, and further the work order service index value can be applied to determine the target handler matched with the work order.

In one embodiment, before sending the work order characteristic information to the target processing node, the method may further comprise:

and acquiring the work order solution efficiency index and the work order solution quality index of the processing person.

Historical data of the worker solution work order capability is read from a database, and the worker solution efficiency index and the work order solution quality index of a processor can be finally obtained by considering three dimensions including a worker capability label, problem response efficiency and service quality.

For example, the work order resolution efficiency indicators may include: 2 hours acceptance timeliness rate, 1 working day solution rate, average delivery duration and other indexes. The work order solution quality indicators may include: and evaluating the indexes such as satisfaction degree and work order resolution rate of the work order.

Wherein, the meterWhen calculating the score of a person, different indexes b can be applied _j (j is 1 to n), j represents the index type, and n represents the total number of types of the index, for example, the index includes five types in total: the 2-hour acceptance timeliness rate, the 1-working-day solution rate, the average delivery duration, the work order evaluation satisfaction degree and the work order solution rate are determined, and n is 5; different target values B can be preset for each index _j (j is 1 to n) and an index weight W _j (j is 1 to n), according to B _j And W _j The processor score is calculated. Accordingly, the calculation formula of the preset scoring algorithm may be set as:

according to the calculation formula of the preset scoring algorithm, the score of the processor is fully divided into 100 points, and the level of the processor can be divided into three levels, namely, a new sharp level, a backbone level and an expert level according to the score. For example, when the processor score is not less than 80 points, the processor level is expert; when the score of the processor is not less than 60 minutes, the level of the processor is a backbone level; when the processor score is below 60 minutes, the processor level is the new sharp level. And matching with the corresponding work order service index value according to the handler level.

Illustratively, the actual value calculated according to the work order service index value may be divided into three levels, including: if the work order service index value is equal to 4, the work order service index value is general, if the work order service index value is greater than 4 and not greater than 8, the work order service index value is urgent, if the work order service index value is greater than 8 and not greater than 16, the work order service index value is urgent. The work order corresponding to the emergency may be assigned to the expert handler, the work order corresponding to the emergency may be assigned to the backbone handler, and the work order corresponding to the general may be assigned to the new sharp handler. Meanwhile, the upward compatibility principle is considered, and under the condition that a processor is in short supply, a low-level processor can process the work order with higher work order service index value level.

In the embodiment of the application, the score of the processor is calculated based on the work order solution efficiency index and the work order solution quality index of the processor, so that the score of the processor is matched with the comprehensive quality of the processor, the processor with corresponding work order processing capacity can be matched when the score of the processor is applied and matched with the work order service index value, and the work order can be timely solved.

In one embodiment, obtaining work order characterization information includes:

and sending a preset work order template to the operation and maintenance node.

The operation and maintenance node corresponds to operation and maintenance personnel, and the preset work order template requires the operation and maintenance personnel to input the following information: problem description, problem error prompt screenshots, problem recurrence videos, and IT systems where problems occur.

And receiving the preset work order template which is input.

The method comprises the steps of performing keyword extraction on problem description in a preset work order template and an IT system with problems appearing through a Neuro-Linguistic Programming (NLP) algorithm, performing image feature analysis on a problem error prompt screenshot and a problem recurrence video through a digital image processing and identifying algorithm, and finally outputting IT problem type information, IT system level information and user portrait information of an IT problem influencing user.

In the embodiment of the application, the relevant information of the work order is collected through the preset work order template, the unification of the information format is ensured, the unified preset algorithm can be applied to extract the work order characteristic information of the work order module, different algorithms do not need to be respectively preset aiming at various work orders, and the extraction efficiency of the work order characteristic information is improved.

In one embodiment, the work order allocation method further comprises:

In the embodiment of the application, under the condition that the number of times of receiving the receipt information sent by the target processing node accords with the preset receipt threshold value, the work order characteristic information is sent to the new target processing node, the work order which cannot be solved by the target handler corresponding to the current target processing node can be sent to the new target processing node in time for the new target handler to handle, and the work order can be guaranteed to be processed in time.

In one embodiment, the work order assignment method further comprises:

and recording the processing time of the target processing node for processing the work order characteristic information.

Wherein, can preset different and predetermine the time limit of reminding to the grade that the size of different work order service index values corresponds, exemplarily, according to the actual value that work order service index value calculated, can divide it into the third grade, include: if the work order service index value is equal to 4, the work order service index value is general, if the work order service index value is greater than 4 and not greater than 8, the work order service index value is urgent, if the work order service index value is greater than 8 and not greater than 16, the work order service index value is urgent. For a general grade, the preset reminding time limit can be set to be 24 hours; for the emergency level, the preset reminding time limit can be set to be 12 hours; for an emergency level, the preset reminding time limit may be set to 3 hours.

Further, if there is more than one target processing node, each target processing node is equivalent to one link, and a plurality of links can set different preset reminding time limits correspondingly.

In the embodiment of the application, the processing time of the target processing node for processing the work order characteristic information is recorded, and when the processing time exceeds the preset reminding time limit, the reminding information is generated and sent to the target processing node, so that the processing person can be reminded to process the work order in time, and the user experience is optimized.

In one embodiment, at S750: after the operation and maintenance service is called to execute the solution so as to solve the IT problem corresponding to the work order, the method may further include:

and receiving evaluation of a solution result of the IT problem corresponding to the work order sent by the operation and maintenance node.

The evaluation of the solution result can reflect the effectiveness of the operation and maintenance service and the solution, so that the operation and maintenance personnel can update and adjust the operation and maintenance service and the solution.

In the embodiment of the application, the evaluation of the solution result of the IT problem corresponding to the work order sent by the operation and maintenance node is received, and a basis can be provided for the optimization of the operation and maintenance service and the solution.

Fig. 7 illustrates a work order assignment method, and the following describes an apparatus provided in an embodiment of the present application in conjunction with fig. 8 and 9. In order to realize the functions, the work order distribution device comprises a hardware structure and/or a software module which are corresponding to the execution of each function. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative algorithm steps described in connection with the embodiments disclosed herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

According to the method, the work order distribution device can be divided into the functional modules exemplarily. The work order distribution device may divide each function module corresponding to each function, or may integrate two or more functions into one processing module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, in the embodiment of the present application, the division of the module is schematic, and is only one logic function division, and there may be another division manner in actual implementation.

Fig. 8 is a schematic structural diagram of a work order distribution apparatus according to an embodiment of the present application, where each module in the apparatus shown in fig. 8 has a function of implementing each step in fig. 7, and can achieve its corresponding technical effect. As shown in fig. 8, the apparatus may include:

the obtaining module 810 is configured to obtain work order feature information, where the work order feature information is used to represent information technology IT problem type information, IT system level information, and user portrait information where IT problems affect a user, corresponding to a work order.

And the calculating module 820 is used for calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm, wherein the work order service index value is used for representing the service level required by the work order.

A sending module 830, configured to send the work order to the target processing node. Each processing node corresponds to one processor, the target processing node corresponds to a target processor, the target processor is selected from a processor list corresponding to the IT problem type information, and the processor score of the target processor is matched with the work order service index value.

In the embodiment of the application, the work order characteristic information is obtained firstly, then the work order service index value used for representing the service level required by the work order is calculated according to the IT system level information and the user portrait information of the IT problem influence user through a preset algorithm, finally the work order is sent to the target processing node, the target processing node corresponds to the target processing person, the target processing person is selected from the list of the processing persons corresponding to the IT problem type information, the score of the processing person of the target processing person is matched with the work order service index value, the processing person capacity corresponding to the processing node allocated to the work order can meet the work order processing requirement, the automatic allocation of the work order is achieved, and the matching degree of the work order allocation and the processing person and the work order allocation efficiency are improved.

The calculating module 820 is specifically configured to:

In an embodiment, the obtaining module 810 is specifically configured to:

And receiving the preset work order template which is input.

In an embodiment, the sending module 830 is further configured to send the work order feature information to a new target processing node when the number of times that the target processing node sends the order refunding information is received meets a preset order refunding threshold.

Fig. 9 shows a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 9, the apparatus may include a processor 901 and a memory 902 storing computer program instructions.

Specifically, the processor 901 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.

Memory 902 may include mass storage for data or instructions. By way of example, and not limitation, memory 902 may include a Hard Disk Drive (HDD), floppy Disk Drive, flash memory, optical Disk, magneto-optical Disk, tape, or Universal Serial Bus (USB) Drive or a combination of two or more of these. In one example, memory 902 may include removable or non-removable (or fixed) media, or memory 902 may be non-volatile solid-state memory. The memory 902 may be internal or external to the integrated gateway disaster recovery device.

In one example, the Memory 902 may be a Read Only Memory (ROM). In one example, the ROM may be mask programmed ROM, programmable ROM (prom), erasable prom (eprom), electrically erasable prom (eeprom), electrically rewritable ROM (earom), or flash memory, or a combination of two or more of these.

The processor 901 reads and executes the computer program instructions stored in the memory 902 to implement the method in the embodiment shown in fig. 7, and achieve the corresponding technical effects achieved by the embodiment shown in fig. 7 executing the method, which are not described herein again for brevity.

In one example, the electronic device can also include a communication interface 903 and a bus 910. As shown in fig. 9, the processor 901, the memory 902, and the communication interface 903 are connected via a bus 910 to complete communication with each other.

The communication interface 903 is mainly used for implementing communication between modules, apparatuses, units and/or devices in this embodiment of the application.

Bus 910 includes hardware, software, or both to couple the components of the online data traffic billing device to each other. By way of example, and not limitation, a Bus may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (Front Side Bus, FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a Micro Channel Architecture (MCA) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus or a combination of two or more of these. Bus 910 can include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.

The electronic device may execute the work order allocation method in the embodiment of the present application, so as to achieve the corresponding technical effect of the work order allocation method described in fig. 7.

In addition, in combination with the work order allocation method in the foregoing embodiments, the embodiments of the present application may provide a computer storage medium to implement. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement any of the work order assignment methods in the above embodiments.

In an exemplary embodiment, the present application further provides a computer program product, which when run on a computer, causes the computer to implement the work order allocation method in the above embodiments.

Through the description of the foregoing embodiments, it will be clear to those skilled in the art that, for convenience and simplicity of description, only the division of the functional modules is used for illustration, and in practical applications, the above function distribution may be completed by different functional modules as required, that is, the internal structure of the device may be divided into different functional modules to complete all or part of the above described functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially or partially contributed to by the prior art, or all or part of the technical solutions may be embodied in the form of a software product, where the software product is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above description is only an embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of work order assignment, comprising:

calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm, wherein the work order service index value is used for representing the service level required by the work order;

sending the work order to a target processing node; each processing node corresponds to a processing person, the target processing node corresponds to a target processing person, the target processing person is selected from a processing person list corresponding to the IT problem type information, and the processing person score of the target processing person is matched with the work order service index value.

2. The method of work order distribution as set forth in claim 1, wherein said method further comprises:

under the condition that an automatic processing instruction sent by the target processing node is received, inquiring a solution of the work order according to the work direction preset knowledge base; the preset knowledge base is generated by constructing a knowledge graph through a historical work order and a solution of the historical work order;

and calling operation and maintenance service to execute the solution so as to solve the IT problem corresponding to the work order.

3. The work order assignment method of claim 1, wherein the user representation information includes a problem affecting user scope, a problem affecting user type, and a problem causing user complaint tendencies;

the step of calculating a work order service index value according to the IT system level information and the user portrait information of the IT problem influencing users through a preset algorithm comprises the following steps:

converting the problem influence user range, the problem influence user type, the user complaint tendency caused by the problem and the IT system level information into binary codes respectively through a preset conversion rule;

and converting the binary code into quantized data which can be used for comparing sizes through a preset conversion algorithm to obtain the work order service index value.

4. The work order distribution method of claim 3, wherein the work order service index value is calculated by the following equation:

wherein S represents the work order service index value, k represents the type of the work order characteristic information corresponding to the binary code, a _i And representing any one code value in the binary codes, and i represents the code number of the binary codes.

5. The method of work order distribution according to any of claims 1-4, wherein prior to sending said work order characterization information to a target processing node, said method further comprises:

6. The method of work order assignment as set forth in claim 5, wherein said obtaining work order characterization information comprises:

sending a preset work order template to the operation and maintenance node; the operation and maintenance node corresponds to an operation and maintenance person, and the preset work order template requires the operation and maintenance person to input the following information: problem description, problem error prompt screenshot, problem reproduction video and an IT system with problems;

receiving a preset work order template which is input;

and analyzing the IT problem type information, the IT system level information and the user portrait information of the IT problem influencing users represented by the preset work order template after the input is completed through a preset analysis algorithm to obtain the work order characteristic information.

7. The method of work order distribution as set forth in claim 5, wherein said method further comprises:

and sending the work order characteristic information to a new target processing node under the condition that the received frequency of sending the order returning information by the target processing node meets a preset order returning threshold value.

8. The method of work order distribution as set forth in claim 7, wherein said method further comprises:

and when the processing time exceeds a preset reminding time limit, generating reminding information and sending the reminding information to the target processing node.

9. A work order dispensing apparatus, comprising:

the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring work order characteristic information which is used for representing information technology IT problem type information, IT system level information and user portrait information of an IT problem influencing user corresponding to a work order;

the sending module is used for sending the work order to the target processing node; each processing node corresponds to one processor, the target processing node corresponds to a target processor, the target processor is selected from a processor list corresponding to the IT problem type information, and the processor score of the target processor is matched with the work order service index value.

10. The work order distribution apparatus of claim 9, wherein said apparatus further comprises a query module and a call module;

the query module is used for querying a solution of the work order according to the work direction preset knowledge base under the condition of receiving an automatic processing instruction sent by the target processing node; the preset knowledge base is generated by constructing a knowledge graph through a historical work order and a solution of the historical work order;

11. The work order distribution apparatus of claim 9, wherein the user profile information includes a range of problem-affecting users, a type of problem-affecting users, and a propensity for a problem to cause a user to apply complaints;

the calculation module is specifically configured to:

12. The work order distribution apparatus of claim 11, wherein the work order service index value is calculated by the following equation:

wherein S represents the work order service index value, k represents the type of the work order characteristic information corresponding to the binary code, a _i And i represents the number of codes of the binary codes.

13. The work order distribution apparatus of any of claims 9-12, wherein the obtaining module is further configured to obtain a work order resolution efficiency index and a work order resolution quality index for a processing person before sending the work order feature information to a target processing node;

and the calculating module is also used for calculating the score of the processor according to the work order solution efficiency index and the work order solution quality index through a preset scoring algorithm.

14. The work order distribution apparatus of claim 13, wherein the acquisition module is specifically configured to:

receiving a preset work order template which is input;

15. The work order distribution apparatus of claim 13, wherein the sending module is further configured to send the work order feature information to a new target processing node if the number of times of receiving the return information sent by the target processing node meets a preset return threshold.

16. The work order distribution apparatus of claim 15, wherein said apparatus further comprises a recording module and a generating module;

the recording module is used for recording the processing time of the target processing node for processing the work order characteristic information;

the generating module is used for generating reminding information when the processing time exceeds a preset reminding time limit;

the sending module is further configured to send the reminding information to the target processing node.

17. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing a work order allocation method as claimed in any one of claims 1 to 8.

18. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements the work order assignment method as claimed in any one of claims 1 to 8.