CN111105120A

CN111105120A - Work order processing method and device

Info

Publication number: CN111105120A
Application number: CN201811269923.1A
Authority: CN
Inventors: 沙泓州; 易山; 刘章勋; 聂福海; 韩冰
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2018-10-29
Filing date: 2018-10-29
Publication date: 2020-05-05
Anticipated expiration: 2038-10-29
Also published as: CN111105120B

Abstract

The embodiment of the application provides a work order processing method and a work order processing device, wherein the method comprises the following steps: after an alarm work order of a first client side is generated, historical behavior information corresponding to the alarm work order is obtained, and the processing priority of the alarm work order is determined according to the historical behavior information and a pre-trained work order priority recognition model; and processing the alarm work order according to the processing priority of the alarm work order. According to the method and the device, the processing priority of the alarm work order is identified by acquiring the historical behavior information of the alarm work order, and then the alarm work order is processed according to the processing priority, so that the alarm event with the real alarm intention can be processed preferentially, the processing efficiency of real alarm is improved, and the utilization efficiency of customer service resources is improved.

Description

Work order processing method and device

Technical Field

The application relates to the technical field of work order processing, in particular to a work order processing method and device.

Background

With the continuous development of science and technology, automobiles gradually enter the lives of people and become indispensable travel tools for most families, and with the increase of automobile holding capacity, the demands of people on travel convenience, the theme of saving and protecting environment and the like, the network appointment industry is rapidly developed, and the travel modes of people are gradually changed.

In order to improve the safety in the process of using the network appointment car, an alarm function can be added to network appointment car software. However, in the process of increasing the usage amount of the network appointment vehicles, more and more alarm data are received by the network appointment platform. Through analyzing the user and the customer service data, most of alarm information or users using the alarm function do not have real alarm appeal, and the alarm data is generated by wrong use of the alarm function possibly only because the users feel novelty or because of understanding mistakes or wrong touch and other reasons, so that limited customer service resources are occupied by a large number of false alarm events, real alarm event work orders are overstocked, and extremely high potential safety hazards exist.

Disclosure of Invention

In view of this, the present application provides a work order processing method and a work order processing apparatus, which can determine a processing priority of an alarm work order according to historical behavior information of the alarm work order, so as to implement priority processing on the alarm work order with a real alarm intention, and improve processing efficiency of the real alarm work order.

In one aspect, an embodiment of the present application provides a work order processing method, where the method includes:

after an alarm work order of a first client side is generated, obtaining historical behavior information corresponding to the alarm work order;

determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model;

and processing the alarm work order according to the processing priority of the alarm work order.

In one embodiment, after determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model, the method comprises the following steps:

according to the processing priority of the alarm work order, inserting the alarm work order into a queue position corresponding to the processing priority in a work order pool to be processed;

the processing the alarm work order according to the processing priority of the alarm work order comprises the following steps:

and taking out the alarm work order from the to-be-processed work order pool for processing according to the queue position of the alarm work order in the to-be-processed work order pool.

In one embodiment, the determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model includes:

performing feature processing on the historical behavior information to obtain model input features corresponding to the alarm work order after the feature processing is performed;

and inputting the model input characteristics into a pre-trained work order priority recognition model to obtain the processing priority of the alarm work order.

In some embodiments of the present application, performing feature processing on the historical behavior information includes performing at least one of the following:

counting each preset historical behavior to obtain a statistical value of the historical behavior characteristic corresponding to each historical behavior;

determining whether the first client and the second client meet before alarming based on the position information of the first client and the second client; the first client is a service requester terminal, the second client is a service provider terminal, or the first client is a service provider terminal, and the second client is a service requester terminal;

and determining a scene where the first client initiates an alarm based on the alarm time of the first client and the time information respectively corresponding to different order states.

In some embodiments of the present application, the method further comprises:

acquiring alarm work order sample information, wherein the alarm work order sample information comprises historical behavior information corresponding to an alarm work order sample and the processing priority of the alarm work order sample;

and training the work order priority identification model based on the alarm work order sample information.

In the above embodiment, the processing priority of the alarm work order sample may be determined according to the following steps:

acquiring the alarm authenticity information of the alarm work order sample and the safety affair grading information of the alarm work order sample;

and determining the processing priority of the alarm work order sample according to the alarm authenticity information and the safety affair grading information.

In the above embodiment, training the work order priority recognition model based on the alarm work order sample information may include:

performing feature processing on historical behavior information corresponding to the alarm work order sample to obtain model input features corresponding to the alarm work order sample after the feature processing is performed;

and training the work order priority recognition model based on the processing priority of the alarm work order sample as a model output result and the model input characteristics corresponding to the alarm work order sample.

In some embodiments, after training the work order priority recognition model based on the processing priorities of the alarm work order samples as a result of model output and the model input features corresponding to the alarm work order samples, the method further comprises:

and periodically acquiring updated alarm work order sample information, and optimizing the work order priority identification model based on the updated alarm work order sample information.

In some embodiments, the historical behavior information includes at least one of the following characteristics:

the system comprises identity information of the alarm work order related personnel, home and company addresses of the alarm work order related personnel, a user account level of the first client, complaint information of the alarm work order related personnel, order cancellation information of the alarm work order related personnel, order cancelled information of the alarm work order related personnel, consumption information of the alarm work order related personnel, historical alarm information of the alarm work order related personnel, historical order information of the alarm work order related personnel, alarm time information corresponding to the alarm work order, time information of each state of a travel order corresponding to the alarm work order, and position information of the alarm work order related personnel.

On the other hand, the embodiment of the present application further provides a work order processing apparatus, including:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring historical behavior information corresponding to an alarm work order after the alarm work order of a first client is generated;

the determining module is used for determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model;

and the processing module is used for processing the alarm work order according to the processing priority of the alarm work order.

In one embodiment, the work order processing apparatus further comprises:

the inserting module is used for inserting the alarm work order into a queue position corresponding to the processing priority in a to-be-processed work order pool according to the processing priority of the alarm work order;

the processing module is specifically configured to: and taking out the alarm work order from the to-be-processed work order pool for processing according to the queue position of the alarm work order in the to-be-processed work order pool.

In an embodiment, the determining module is further specifically configured to:

In some embodiments of the present application, when performing feature processing on the historical behavior information, the determining module is specifically configured to perform at least one of the following processes:

determining whether the first client and the second client meet before alarming based on the position information of the first client and the second client, wherein the first client is a service requester terminal, the second client is a service provider terminal, or the first client is the service provider terminal, and the second client is the service requester terminal;

In some embodiments of the present application, the work order processing apparatus further comprises:

the second acquisition module is used for acquiring alarm work order sample information, and the alarm work order sample information comprises historical behavior information corresponding to the alarm work order sample and the processing priority of the alarm work order sample;

and the training module is used for training the work order priority recognition model based on the alarm work order sample information.

In the foregoing embodiment, the second obtaining module is specifically configured to determine the processing priority of the alarm work order sample according to the following steps:

In the above embodiment, the training module is further specifically configured to:

In some embodiments, the work order processing apparatus further comprises:

and the optimization module is used for periodically acquiring updated alarm work order sample information and optimizing the work order priority identification model based on the updated alarm work order sample information.

On the other hand, an embodiment of the present application further provides an electronic device, including: the system comprises a processor, a storage medium and a communication bus, wherein the storage medium stores machine-readable instructions executable by the processor, when the electronic device runs, the processor and the storage medium communicate through the communication bus, and the processor executes the machine-readable instructions to execute the steps of the work order processing method.

On the other hand, the embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the above-mentioned work order processing method.

The embodiment of the application identifies the processing priority of the alarm work order by acquiring the historical behavior information of the alarm work order, and the alarm work order is processed based on the processing priority of the alarm work order, so that the alarm event with the real alarm intention can be processed preferentially, the processing efficiency of the real alarm is improved, the utilization efficiency of customer service resources is improved, the problems that the alarm event work order quantity is large, the alarm event with the real alarm intention is overstocked, the alarm event cannot be processed in time and potential safety hazards exist in the prior art can be solved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a system block diagram in a scenario in which a work order processing method provided in an embodiment of the present application is applied;

FIG. 2 is a schematic diagram of exemplary hardware and software components of an electronic device that may implement the concepts of the present application, according to some embodiments of the present application;

FIG. 3 is a flowchart of a work order processing method according to an embodiment of the present application;

FIG. 4 is a flow chart of a work order processing method according to another embodiment of the present application;

fig. 5 is one of the structural diagrams of the work order processing apparatus according to the embodiment of the present application;

fig. 6 is a second structural diagram of a work order processing apparatus according to an embodiment of the present application.

Detailed Description

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of protection of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.

In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

To enable those skilled in the art to use the present disclosure, the following embodiments are presented in conjunction with a specific application scenario, "network appointment alarm event". It will be apparent to those skilled in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Although the present application is described primarily in the context of a network appointment alarm event, it should be understood that this is merely one exemplary embodiment. The application can be applied to any other traffic type. For example, the present application may be applied to different transportation system environments, including terrestrial, marine, or airborne, among others, or any combination thereof. The vehicle of the transportation system may include a taxi, a private car, a windmill, a bus, a train, a bullet train, a high speed rail, a subway, a ship, an airplane, a spacecraft, a hot air balloon, or an unmanned vehicle, etc., or any combination thereof. The present application may also include any service system for online car appointments, such as a system for generating or receiving orders, a service system for transactions between drivers and passengers. Applications of the system or method of the present application may include web pages, plug-ins for browsers, client terminals, customization systems, internal analysis systems, or artificial intelligence robots, among others, or any combination thereof.

It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.

The terms "passenger," "requestor," "service person," "service requestor," and "customer" are used interchangeably in this application to refer to an individual, entity, or tool that can make an alarm or instead of an alarm. The terms "driver," "provider," "service provider," and "vendor" are used interchangeably in this application to refer to an individual, entity, or tool that may be alerted. The term "user" in this application may refer to an individual, entity or tool that requests a service, subscribes to a service, provides a service, or facilitates the provision of a service. For example, the user may be a passenger, a driver, an operator, etc., or any combination thereof. In the present application, "passenger" and "passenger terminal" may be used interchangeably, and "driver" and "driver terminal" may be used interchangeably.

One aspect of the present application relates to a work order processing system. The system can identify the processing priority of the alarm work order by acquiring the historical behavior information of the alarm work order, so that the alarm event with the real alarm intention can be processed preferentially, the backlog of the real alarm work order is reduced, and the real alarm processing efficiency is improved, thereby solving the problems that the number of the alarm work orders is large, the alarm work orders with the real alarm intention are backlogged, the alarm work orders cannot be processed in time and potential safety hazards exist in the prior art.

It is worth noting that before the application is proposed, the amount of alarm information in the network appointment car is increased sharply, but most of alarm information or users using the alarm function have no real alarm appeal, so that limited customer service resources are occupied by a large number of irrelevant alarm events, a real alarm event work order with the real alarm appeal is overstocked, timely processing cannot be achieved, and extremely high potential safety hazards exist. However, according to the work order processing method provided by the embodiment of the application, the obtained historical behavior information of the alarm work order can be analyzed by using the pre-trained work order priority recognition model, the processing priority of the alarm work order is determined, and then the processing sequence of the alarm work order is adjusted according to the determined processing priority of the alarm work order, so that the alarm work order with real alarm intention is processed preferentially, and the processing efficiency of real alarm is improved.

Fig. 1 is a block diagram of a system 100 in a scenario in which a work order processing method according to an embodiment of the present application is applied. For example, the system 100 may be an online transportation service platform for transportation services such as taxi cab, designated drive service, express, carpool, bus service, driver rental, or regular service, or any combination thereof. The system 100 may include one or more of a server 110, a network 120, a service requester terminal 130, a service provider terminal 140, and a database 150, and the server 110 may include a processor therein that performs operations of instructions.

In one implementation, the work order processing method of the embodiment of the present application may be applied to the server 110 of the system 100. In the embodiment of the present application, the first client may refer to the service requester terminal 130 in the system 100, or may refer to the service provider terminal 140.

In some embodiments, the server 110 may be a single server or a group of servers. The set of servers can be centralized or distributed (e.g., the servers 110 can be a distributed system). In some embodiments, the server 110 may be local or remote to the terminal. For example, the server 110 may access information and/or data stored in the service requester terminal 130, the service provider terminal 140, or the database 150, or any combination thereof, via the network 120. As another example, the server 110 may be directly connected to at least one of the service requester terminal 130, the service provider terminal 140, and the database 150 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform; by way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (community cloud), a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof. In some embodiments, the server 110 may be implemented on an electronic device 200 having one or more of the components shown in FIG. 2 in the present application.

In some embodiments, the server 110 may include a processor. The processor may process information and/or data related to the service request to perform one or more of the functions described herein. For example, the processor may determine a processing priority for the alarm work order based on the alarm request obtained from the service requester terminal 130. In some embodiments, a processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a Processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set computer (Reduced Instruction Set Computing, RISC), a microprocessor, or the like, or any combination thereof.

Network 120 may be used for the exchange of information and/or data. In some embodiments, one or more components in the system 100 (e.g., the server 110, the service requester terminal 130, the service provider terminal 140, and the database 150) may send information and/or data to other components. For example, the server 110 may obtain a service request from the service requester terminal 130 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or combination thereof. Merely by way of example, Network 130 may include a wired Network, a Wireless Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a WLAN, a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a ZigBee Network, a Near Field Communication (NFC) Network, or the like, or any combination thereof. In some embodiments, network 120 may include one or more network access points. For example, network 120 may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of system 100 may connect to network 120 to exchange data and/or information.

In some embodiments, the user of the service requestor terminal 130 may be someone other than the actual demander of the service. For example, the user a of the service requester terminal 130 may use the service requester terminal 130 to initiate a service request for the service actual demander B (for example, the user a may call a car for his friend B), or receive service information or instructions from the server 110. In some embodiments, the user of the service provider terminal 140 may be the actual provider of the service or may be another person than the actual provider of the service. For example, user C of the service provider terminal 140 may use the service provider terminal 140 to receive a service request serviced by the service provider entity D (e.g., user C may pick up an order for driver D employed by user C), and/or information or instructions from the server 110. In some embodiments, "service requester" and "service requester terminal" may be used interchangeably, and "service provider" and "service provider terminal" may be used interchangeably.

In some embodiments, the service requester terminal 130 may comprise a mobile device, a tablet computer, a laptop computer, or a built-in device in a motor vehicle, etc., or any combination thereof. In some embodiments, the mobile device may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home devices may include smart lighting devices, control devices for smart electrical devices, smart monitoring devices, smart televisions, smart cameras, or walkie-talkies, or the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart lace, smart glass, a smart helmet, a smart watch, a smart garment, a smart backpack, a smart accessory, and the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a Personal Digital Assistant (PDA), a gaming device, a navigation device, or a point of sale (POS) device, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, virtual reality glass, a virtual reality patch, an augmented reality helmet, augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include various virtual reality products and the like. In some embodiments, the built-in devices in the motor vehicle may include an on-board computer, an on-board television, and the like. In some embodiments, the service requester terminal 130 may be a device having a location technology for locating the location of the service requester and/or service requester terminal.

In some embodiments, the service provider terminal 140 may be a similar or identical device as the service requestor terminal 130. In some embodiments, the service provider terminal 140 may be a device with location technology for locating the location of the service provider and/or the service provider terminal. In some embodiments, the service requester terminal 130 and/or the service provider terminal 140 may communicate with other locating devices to determine the location of the service requester, service requester terminal 130, service provider, or service provider terminal 140, or any combination thereof. In some embodiments, the service requester terminal 130 and/or the service provider terminal 140 may transmit the location information to the server 110.

Database 150 may store data and/or instructions. In some embodiments, the database 150 may store data obtained from the service requester terminal 130 and/or the service provider terminal 140. In some embodiments, database 150 may store data and/or instructions for the exemplary methods described herein. In some embodiments, database 150 may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write Memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), Double data Rate Synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), Thyristor-Based Random Access Memory (T-RAM), Zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), Programmable ROMs (PROMs), Erasable Programmable ROMs (PERROMs), Electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, database 150 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.

In some embodiments, a database 150 may be connected to the network 120 to communicate with one or more components in the system 100 (e.g., the server 110, the service requester terminal 130, the service provider terminal 140, etc.). One or more components in system 100 may access data or instructions stored in database 150 via network 120. In some embodiments, the database 150 may be directly connected to one or more components in the system 100 (e.g., the server 110, the service requester terminal 130, the service provider terminal 140, etc.); alternatively, in some embodiments, database 150 may also be part of server 110.

In some embodiments, one or more components in the system 100 (e.g., the server 110, the service requestor terminal 130, the service provider terminal 140, etc.) may have access to the database 150. In some embodiments, one or more components in system 100 may read and/or modify information related to a service requestor, a service provider, or the public, or any combination thereof, when certain conditions are met. For example, server 110 may read and/or modify information for one or more users after receiving a service request.

In some embodiments, the exchange of information by one or more components in system 100 may be accomplished by a request service. The object of the service request may be any product. In some embodiments, the product may be a tangible product or a non-physical product. Tangible products may include food, pharmaceuticals, commodities, chemical products, appliances, clothing, automobiles, homes, or luxury goods, and the like, or any combination thereof. The non-material product may include a service product, a financial product, a knowledge product, an internet product, or the like, or any combination thereof. The internet product may include a stand-alone host product, a network product, a mobile internet product, a commercial host product, an embedded product, or the like, or any combination thereof. The internet product may be used in software, programs, or systems of the mobile terminal, etc., or any combination thereof. The mobile terminal may include a tablet, a laptop, a mobile phone, a Personal Digital Assistant (PDA), a smart watch, a Point of sale (POS) device, a vehicle-mounted computer, a vehicle-mounted television, a wearable device, or the like, or any combination thereof. The internet product may be, for example, any software and/or application used in a computer or mobile phone. The software and/or applications may relate to social interaction, shopping, transportation, entertainment time, learning, or investment, or the like, or any combination thereof. In some embodiments, the transportation-related software and/or applications may include travel software and/or applications, vehicle dispatch software and/or applications, mapping software and/or applications, and the like. In the vehicle scheduling software and/or application, the vehicle may include a horse, a carriage, a human powered vehicle (e.g., unicycle, bicycle, tricycle, etc.), an automobile (e.g., taxi, bus, privatege, etc.), a train, a subway, a ship, an airplane (e.g., airplane, helicopter, space shuttle, rocket, hot air balloon, etc.), etc., or any combination thereof.

Fig. 2 is a schematic diagram of exemplary hardware and software components of an electronic device 200 that may implement the concepts of the present application, according to some embodiments of the present application. For example, the processor 220 may be used on the electronic device 200 and to perform the functions herein.

The electronic device 200 may be a general purpose computer or a special purpose computer, both of which may be used to implement the work order processing method of the present application. Although only a single computer is shown, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.

For example, the electronic device 200 may include a network port 210 connected to a network, one or more processors 220 for executing program instructions, a communication bus 230, and a different form of storage medium 240, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the computer platform may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof. The method of the present application may be implemented in accordance with these program instructions. The electronic device 200 also includes an Input/Output (I/O) interface 250 between the computer and other Input/Output devices (e.g., keyboard, display screen).

For ease of illustration, only one processor is depicted in the electronic device 200. However, it should be noted that the electronic device 200 in the present application may also comprise a plurality of processors, and thus the steps performed by one processor described in the present application may also be performed by a plurality of processors in combination or individually. For example, if the processor of the electronic device 200 executes steps a and B, it should be understood that steps a and B may also be executed by two different processors together or separately in one processor. For example, a first processor performs step a and a second processor performs step B, or the first processor and the second processor perform steps a and B together.

The idea of an embodiment of the present application is further described below from the implementation point of view.

Fig. 3 is a flowchart of a work order processing method provided in an embodiment of the present application, and as shown in fig. 3, the method includes:

s301: after an alarm work order of a first client side is generated, historical behavior information corresponding to the alarm work order is obtained.

In this step, after receiving an alarm request sent by a user through a first client, an alarm work order corresponding to the alarm request may be generated, and then, historical behavior information corresponding to the alarm work order may be acquired.

The first client may be the service requester terminal or the service provider terminal, and correspondingly, the user of the first client may be a passenger or a driver. The alarm request sent by the user through the first client may be an alarm request sent by the user using the first client, or an alarm request associated with the first client and sent by another person instead of the user.

The historical behavior information can be some personal information of the user related to the user sending the alarm request and the use condition of the passing network appointment car. Specifically, the historical behavior information of the alarm work order may include at least one of the following features:

identity information of the alarm work order related personnel, such as basic information of the sex and age of a driver and basic information of the sex and age of a passenger; the home and company address of the person associated with the alarm work order, such as the home and company address of the passenger and/or driver; the user account level of the first client, such as the level information of the service star level of the account of the passenger and/or the driver on the webpage vehicle platform; at least one of complaint information, order cancellation information and order cancellation information of the alarm work order related personnel, such as at least one of complaint information, order cancellation information and order cancellation information of passengers and/or drivers in a preset historical time period; the order preference of the alarm work order related personnel, such as the geographic position information (such as in a school, a supermarket or nearby a hotel) of the historical order taking of the driver, the time preference of the historical order taking and the like; consumption information of the alarm work order related personnel, such as consumption information of passengers in a preset historical time period; historical alarm information of personnel associated with the alarm work order, such as historical alarm information of passengers and/or drivers; historical order information of the alarm work order related personnel, such as historical order information of passengers and/or historical order taking information of drivers; alarm time information corresponding to the alarm work order, such as the specific time of the occurrence of an alarm event; time information of each state of the travel order corresponding to the alarm work order, such as time information of order issuing time, order grabbing time, charging time (time when passengers get on the bus), order ending time and the like of the order; the alarm work order is associated with the location information of personnel, such as the respective location information of the passenger and the driver.

S302: and determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model.

In this step, after the historical behavior information is obtained, the alarm work order may be identified and determined according to the historical behavior information and a pre-trained work order priority identification model, using the historical behavior information and the work order priority identification model, to determine the processing priority of the alarm work order.

Specifically, the alarm work order is identified through the work order priority identification model, only two categories of identification priorities are required, that is, whether the alarm work order needs to be subjected to priority processing is identified, or multiple categories of identification priorities are required, that is, whether the alarm work order needs to be subjected to priority processing is identified, and which corresponding level of priority processing the alarm work order belongs to can be identified according to a preset level system, such as first-level priority processing, second-level priority processing or third-level priority processing.

S303: and processing the alarm work order according to the processing priority of the alarm work order.

In this step, after the processing priority of the alarm work order is determined, the alarm work order may be processed based on the processing priority.

The alarm work order is processed according to the processing priority of the alarm work order, the alarm work order may be processed according to the processing priority and a corresponding processing sequence, the alarm work order may be processed according to the processing priority and a corresponding processing time, or the alarm work order may be allocated to a processing person of a corresponding level for processing according to the level of the processing person corresponding to the processing priority.

According to the work order processing method, the processing priority of the alarm work order is identified by obtaining the historical behavior information of the alarm work order, the alarm work order is processed based on the processing priority of the alarm work order, so that the alarm event with the real alarm intention can be processed preferentially, the processing efficiency of real alarm is improved, the utilization efficiency of customer service resources is improved, and the problems that the data volume of the alarm event work order is large, the alarm event with the real alarm intention is overstocked, the alarm event cannot be processed in time and potential safety hazards exist in the prior art can be solved.

Fig. 4 is a flowchart of a work order processing method according to another embodiment of the present application, as shown in fig. 4, the method includes:

s401: after an alarm work order of a first client side is generated, historical behavior information corresponding to the alarm work order is obtained.

S402: and determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model.

S403: and inserting the alarm work order into a queue position corresponding to the processing priority in a work order pool to be processed according to the processing priority of the alarm work order.

In this step, after the processing priority of the alarm work order is determined, the alarm work order may be inserted into a queue position corresponding to the processing priority in a to-be-processed work order pool according to the processing priority corresponding to the alarm work order.

Therefore, the processing sequence, the processing time, the processing position and the like of the alarm work order can be adjusted according to the processing priority of the alarm work order, so that the alarm work order with real alarm intention can be processed preferentially, the processing time of the alarm work order is shortened, the situation that the alarm work order is overstocked and cannot be processed in time is avoided, and the potential safety hazard is reduced.

S404: and taking out the alarm work order from the to-be-processed work order pool for processing according to the queue position of the alarm work order in the to-be-processed work order pool.

In actual implementation, each alarm work order is inserted into a corresponding queue position in a work order pool to be processed according to the processing priority; when the alarm work orders are processed, each alarm work order can be taken out from the work order pool to be processed in sequence for processing, and the queue position of each alarm work order in the work order pool to be processed can determine the processing sequence arrangement of the alarm work order.

S401 and S402 may refer to S301 to S302 in the embodiment shown in fig. 3, respectively, and may obtain the same technical effect, which is not described herein again.

Optionally, S402 includes:

performing feature processing on the historical behavior information to obtain model input features corresponding to the alarm work order after the feature processing is performed; and inputting the model input characteristics into a pre-trained work order priority recognition model to obtain the processing priority of the alarm work order.

In this step, after the historical behavior information is obtained, the historical behavior information may be subjected to feature processing, specifically, the behavior information that can be used as a model input feature is extracted from the historical behavior information, then the extracted behavior information is subjected to feature processing, so that a model input feature corresponding to the alarm work order after the feature processing is obtained, and then the model input feature obtained through the processing may be input to a pre-trained work order priority recognition model for recognition, so as to obtain a processing priority of the alarm work order.

Therefore, model input characteristics can be obtained through processing based on original data in the alarm signals input by the user, and then the work order priority identification model identifies the model input characteristics, so that the alarm scene is effectively restored, and the accuracy of alarm work order priority identification is improved.

In a specific implementation, the characteristic processing is performed on the historical behavior information, and includes performing at least one of the following processing:

and counting each preset historical behavior to obtain a statistical value of the historical behavior characteristic corresponding to each historical behavior.

Each preset historical behavior can be behaviors such as complaints, orders cancelled, consumption, alarm situations and the like which occur in the past preset time period of an alarmer and an alarmed person (such as a passenger and a driver) in an alarm event.

Therefore, whether the alarm person frequently has accident-free or malicious complaints or alarms can be analyzed through the statistics of historical behaviors, and the analysis can be used as a measurement dimension for measuring whether the alarm order is a valid order.

Determining whether the first client and the second client meet before the alarm based on the location information of the first client and the second client.

The first client may be the service requester terminal, and the second client may be the service provider terminal; alternatively, the first client may be the service provider terminal, and the second client may be the service requester terminal.

The location information of the first client and the second client may represent the location information of the alarmed person and the location information of the alarmed person in the alarm event.

Thus, whether the alarm person and the alarmed person meet in the alarm event is judged according to the position information of the first client and the second client, and the judgment can be used as a measurement dimension for measuring whether the alarm order is a valid order, for example, when an alarm occurs, if the alarm person and the alarmed person do not meet or are separated, the alarm event can be considered as a false alarm, or only a problem complaint after the order is completed and the like, and a dangerous case does not actually occur, and the alarm event can be considered as a situation without substantial potential safety hazards.

The alarm time of the first client may be the time when an alarm person (such as a passenger or a driver) alarms through the first client.

The different order states may refer to states of order taking, order grabbing, charging starting (in order making), order completion, and the like of the order in the travel event.

Thus, by the time difference between the alarm time and the different states of the order, the difference can describe which states the order has passed when the alarm occurs, and determine the situation of the scene when the alarm event occurs, which can be used as a measure for measuring whether the alarm order is a valid order, for example, if the alarm time and the order completion time have a difference when the alarm event occurs, and the alarm time is far behind the order completion time, which may indicate that the alarm person and the alarmed person have been separated early, the alarm event can be considered as a false alarm, or only a problem complaint after the order is completed, etc., and a dangerous situation does not actually occur, and the alarm event can be considered as a situation without substantial potential safety hazard.

In a specific implementation, in order to more accurately infer a scene during an alarm, the three ways of performing feature processing on the historical behavior information may be simultaneously combined.

In one embodiment, the method further comprises:

acquiring alarm work order sample information, wherein the alarm work order sample information comprises historical behavior information corresponding to an alarm work order sample and the processing priority of the alarm work order sample; and training the work order priority identification model based on the alarm work order sample information.

In this step, before the work order processing apparatus can identify the alarm work order, the work order processing apparatus may train the work order priority identification model by using a classification algorithm of machine learning (for example, methods such as extreme Gradient Boosting (Xgboost), Support Vector Machines (SVMs), or Random Forest (RF)) through a big data learning method using sample data, and specifically, may acquire alarm work order sample information from a sample set including a plurality of alarm work order samples, and train the work order priority identification model according to the alarm work order sample information.

The alarm work order sample information comprises historical behavior information corresponding to the alarm work order sample and the processing priority of the alarm work order sample.

Specifically, the historical behavior information of the alarm work order sample may include at least one of the following features:

The alarm work order sample can be a historical alarm work order which is processed manually and the authenticity of the alarm event is determined manually.

The processing priority of the alarm work order sample is different from the processing priority of the alarm work order, the processing priority of the alarm work order sample is the historical alarm work order with the truth of the alarm being clarified when the historical alarm work order is manually processed, the truth of the alarm is the processing priority of the alarm work order sample when the historical alarm work order sample is used as the sample, and the processing priority of the alarm work order is the truth of the alarm judged by a model obtained by identifying the historical behavior information of the alarm work order through a work order processing priority model.

Specifically, the processing priority of the alarm work order sample may be determined by the following steps:

acquiring the alarm authenticity information of the alarm work order sample and the safety affair grading information of the alarm work order sample; and determining the processing priority of the alarm work order sample according to the alarm authenticity information and the safety affair grading information.

The alarm truth information of the alarm work order sample can be used as a historical alarm order of a training sample, after manual processing, whether an alarm event of the rechecked historical alarm order is real alarm behavior information or not can be marked by whether the label information of the alarm work order sample records that the work order is upgraded or not, and if the label information of the alarm work order sample records that the alarm work order sample is upgraded manually, the alarm truth information of the alarm work order sample can be used for showing that the alarm event of the alarm work order sample is real and effective alarm.

The safety affair grading information of the alarm work order sample can be a historical alarm order as a training sample, after manual processing, the alarm event of the historical alarm order is rechecked to be a real and effective alarm behavior, and the alarm behavior of the historical alarm order is divided into information of alarm emergency situations, such as a first-level alarm situation, a second-level alarm situation and the like, and the safety affair grading information can also be recorded through label information of the alarm work order sample.

Therefore, the accuracy of the processing priority of the alarm work order sample can be ensured, and the accuracy of the trained work order priority processing model for identifying the alarm work order is improved.

In one embodiment, training the work order priority recognition model based on the alarm work order sample information includes:

performing feature processing on historical behavior information corresponding to the alarm work order sample to obtain model input features corresponding to the alarm work order sample after the feature processing is performed; and training the work order priority recognition model based on the processing priority of the alarm work order sample as a model output result and the model input characteristics corresponding to the alarm work order sample.

In this step, after obtaining the historical behavior information of the alarm work order sample, the historical behavior information of the alarm work order sample may be subjected to feature processing, specifically, the behavior information that can be used as a model input feature is extracted from the historical behavior information of the alarm work order sample, the extracted behavior information is subjected to feature processing, so as to obtain a model input feature corresponding to the alarm work order sample after the feature processing is performed, and then, the work order priority recognition model may be trained by using the processing priority of the alarm work order sample as a result of the model output and the model input feature corresponding to the alarm work order sample.

Therefore, the work order priority recognition model is trained by using the characteristics and the processing priority of the real and effective alarm work order sample, the accuracy of the work order priority recognition model in recognizing a new alarm work order can be improved, the training mode is simple and effective, and the sample is convenient to obtain.

In one embodiment, after training the work order priority recognition model based on the processing priority of the alarm work order sample as the output result of the model and the model input features corresponding to the alarm work order sample, the method further comprises:

In this step, the alarm work order sample in the sample set may be updated, the updated alarm work order sample information may be periodically obtained, and then the updated alarm work order sample information is used to train the work order priority recognition model to optimize the work order processing priority model.

Therefore, the work order processing priority model is periodically optimized, and the accuracy of the alarm work order identification of the work order processing priority model can be improved.

According to the work order processing method provided by the embodiment of the application, after the alarm work order of the first client side is generated, historical behavior information corresponding to the alarm work order is obtained; determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model; according to the processing priority of the alarm work order, inserting the alarm work order into a queue position corresponding to the processing priority in a work order pool to be processed; and processing the alarm work order according to the processing priority of the alarm work order. Therefore, the processing priority of the alarm work order is identified by acquiring the historical behavior information of the alarm work order, the position of the alarm work order in the to-be-processed work order pool is adjusted, the alarm work order is processed based on the processing priority of the alarm work order, so that the alarm event with real alarm intention can be processed preferentially, the processing efficiency of real alarm is improved, the utilization efficiency of customer service resources is improved, and the problems that the alarm event work order data volume is large, the alarm event with real alarm intention is overstocked, cannot be processed in time and has potential safety hazards in the prior art can be solved.

Referring to fig. 5 to 6, fig. 5 is a first structural diagram of a work order processing apparatus provided in an embodiment of the present application, and fig. 6 is a second structural diagram of the work order processing apparatus provided in the embodiment of the present application. The work order processing apparatus 500 may implement the steps executed by the work order processing method described above. The device can be understood as the server or the processor of the server, and can also be understood as a component which is independent of the server or the processor and realizes the functions of the application under the control of the server. As shown in fig. 5, the work order processing apparatus 500 includes:

the first obtaining module 510 is configured to obtain historical behavior information corresponding to an alarm work order of a first client after the alarm work order is generated.

And the determining module 520 is configured to determine the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority identification model.

And the processing module 530 is configured to process the alarm work order according to the processing priority of the alarm work order.

In one embodiment, as shown in fig. 6, the work order processing apparatus 500 further comprises:

and the inserting module 540 is configured to insert the alarm work order into a queue position corresponding to the processing priority in the to-be-processed work order pool according to the processing priority of the alarm work order.

The processing module 530 is specifically configured to: and taking out the alarm work order from the to-be-processed work order pool for processing according to the queue position of the alarm work order in the to-be-processed work order pool.

the second obtaining module 550 is configured to obtain alarm work order sample information, where the alarm work order sample information includes historical behavior information corresponding to the alarm work order sample and a processing priority of the alarm work order sample.

And the training module 560 is used for training the work order priority identification model based on the alarm work order sample information.

and the optimization module 570 is used for periodically acquiring the updated alarm work order sample information and optimizing the work order priority identification model based on the updated alarm work order sample information.

In an embodiment, the determining module 520 is further specifically configured to:

and performing characteristic processing on the historical behavior information to obtain model input characteristics corresponding to the alarm work order after the characteristic processing is performed.

In some embodiments of the present application, when the determining module 520 performs feature processing on the historical behavior information, it is specifically configured to perform at least one of the following processes:

And determining whether the first client and the second client meet before alarming based on the position information of the first client and the second client, wherein the first client is a service requester terminal, the second client is a service provider terminal, or the first client is the service provider terminal, and the second client is the service requester terminal.

In the foregoing embodiment, the second obtaining module 550 is specifically configured to determine the processing priority of the alarm work order sample according to the following steps:

In the above embodiment, the training module 560 may further be specifically configured to:

and performing characteristic processing on the historical behavior information corresponding to the alarm work order sample to obtain the model input characteristics corresponding to the alarm work order sample after the characteristic processing is performed.

The work order processing device provided by the embodiment of the application acquires historical behavior information corresponding to an alarm work order after the alarm work order of a first client is generated, wherein the first client is a passenger client or a second client; determining the processing priority of the alarm work order according to the historical behavior information and a pre-trained work order priority recognition model; and processing the alarm work order according to the processing priority of the alarm work order.

Therefore, the processing priority of the alarm work order is identified by acquiring the historical behavior information of the alarm work order, the alarm work order is processed based on the processing priority of the alarm work order, so that the alarm event with the real alarm intention can be processed preferentially, the processing efficiency of the real alarm is improved, the utilization efficiency of customer service resources is improved, and the problems that the alarm event work order in the prior art is large in data volume, the alarm event with the real alarm intention is overstocked, cannot be processed in time and has potential safety hazards can be solved.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the work order processing method in the method embodiments shown in fig. 3 and fig. 4 may be executed.

The modules may be connected or in communication with each other via a wired or wireless connection. The wired connection may include a metal cable, an optical cable, a hybrid cable, etc., or any combination thereof. The wireless connection may comprise a connection over a LAN, WAN, bluetooth, ZigBee, NFC, or the like, or any combination thereof. Two or more modules may be combined into a single module, and any one module may be divided into two or more units.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to corresponding processes in the method embodiments, and are not described in detail in this application. In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical division, and there may be other divisions in actual implementation, and for example, a plurality of modules or components may be combined or integrated into another system, 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 of devices or modules through some communication interfaces, and may be in an electrical, mechanical or other form.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. 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 functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to 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 for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall 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 processing, the method comprising:

2. The method of claim 1, wherein after determining a processing priority for the alarm work order based on the historical behavior information and a pre-trained work order priority recognition model, the method comprises:

3. The method of claim 1, wherein determining a processing priority for the alarm work order based on the historical behavior information and a pre-trained work order priority recognition model comprises:

4. The method of claim 3, wherein characterizing the historical behavior information comprises performing at least one of:

5. The method of claim 1, wherein the method further comprises:

6. The method of claim 5, wherein the processing priority of the alarm work order sample is determined according to the following steps:

7. The method of claim 5, wherein training the work order priority recognition model based on the alarm work order sample information comprises:

performing feature processing on historical behavior information corresponding to the alarm work order sample to obtain a model input feature corresponding to the alarm work order sample after the feature processing is performed;

8. The method of claim 7, wherein after training the work order priority recognition model based on the processing priorities of the alarm work order samples as a result of model output and model input features corresponding to the alarm work order samples, the method further comprises:

9. A method as claimed in any one of claims 1 to 8, wherein the historical behaviour information includes at least one of the following characteristics:

10. A work order processing apparatus, comprising:

11. The work order processing apparatus of claim 10, wherein said work order processing apparatus further comprises:

12. The work order processing apparatus of claim 10, wherein the determination module is specifically configured to:

13. The work order processing apparatus as claimed in claim 12, wherein the determining module is specifically configured to perform at least one of the following processes when performing the feature processing on the historical behavior information:

14. The work order processing apparatus of claim 10, wherein said work order processing apparatus further comprises:

15. The work order processing apparatus of claim 14, wherein the second obtaining module is specifically configured to determine a processing priority of the alarm work order sample according to the following steps:

16. The work order processing apparatus of claim 14, wherein the training module is specifically configured to:

17. The work order processing apparatus of claim 10, wherein said work order processing apparatus further comprises:

18. The work order processing apparatus of any of claims 10 to 17, wherein the historical behavior information comprises at least one of:

19. An electronic device, comprising: a processor, a storage medium and a communication bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the communication bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the steps of the work order processing method as claimed in any one of claims 1 to 9.

20. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of work order processing according to any one of claims 1 to 9.