CN117034173A

CN117034173A - Data processing method, device, computer equipment and storage medium

Info

Publication number: CN117034173A
Application number: CN202311059530.9A
Authority: CN
Inventors: 鞠美双
Original assignee: Ping An Health Insurance Company of China Ltd
Current assignee: Ping An Health Insurance Company of China Ltd
Priority date: 2023-08-21
Filing date: 2023-08-21
Publication date: 2023-11-10

Abstract

The embodiment of the application belongs to the field of big data and the field of financial science and technology, and relates to a data processing method, which comprises the following steps: acquiring event data corresponding to a circulation node of a target service, wherein the event data is sent by a business system; analyzing the event data to obtain result data; obtaining a target link type corresponding to a circulation node; obtaining a target index rule corresponding to the target link type from a rule base; verifying the result data based on the target index rule, and identifying abnormal data in the result data; and sending an alarm notification to the service system based on the abnormal data. The application also provides a data processing device, computer equipment and a storage medium. In addition, the application also relates to a blockchain technology, and abnormal data can be stored in the blockchain. The method and the device can be applied to an abnormal alarm scene in the financial field, can realize the rapid and accurate identification of the abnormal data from the result data contained in the data based on the use of the index rule, and improve the processing efficiency of the abnormal verification of the result data.

Description

Data processing method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of big data technology and the field of financial technology, and in particular, to a data processing method, a data processing device, a computer device, and a storage medium.

Background

With the rapid development of internet finance, many finance and technology companies develop business systems for performing business processes, such as medical management systems, insurance systems, banking systems, transaction systems, and the like. However, in the process of processing service data of various nodes, some abnormal data with problems usually occur in the service data. In the existing method for identifying abnormal data in service data of various nodes in a service system, quality inspection personnel generally inspect the service data of various nodes to identify whether the abnormal data exists in the service data, so that more manpower resources are required to be consumed based on a manual abnormal identification mode, the processing efficiency of abnormal identification is low, the discovery problem is late, and the occurrence probability of customer complaints is increased.

Disclosure of Invention

The embodiment of the application aims to provide a data processing method, a device, computer equipment and a storage medium, which are used for solving the technical problems that the existing manual abnormality identification mode needs to consume more manpower resources, the processing efficiency of abnormality identification is low, the discovery problem is late, and the occurrence probability of customer complaints is increased.

In order to solve the above technical problems, an embodiment of the present application provides a data processing method, which adopts the following technical schemes:

acquiring event data corresponding to a circulation node of a target service, wherein the event data is sent by a business system;

analyzing the event data to obtain corresponding result data;

acquiring a target link type corresponding to a circulation node of the target service;

acquiring a target index rule corresponding to the target link type from a preset rule base;

verifying the result data based on the target index rule, and identifying abnormal data in the result data;

and sending an alarm notification to the service system based on the abnormal data.

Further, the step of sending an alarm notification to the service system based on the abnormal data specifically includes:

acquiring a notification mode corresponding to the target link type;

generating corresponding alarm information based on the abnormal data;

determining operation staff corresponding to the service system;

and pushing the alarm information to the operation and maintenance personnel based on the notification mode.

Further, the step of generating the corresponding alarm information based on the abnormal data specifically includes:

Acquiring an exception handling mode corresponding to the exception data;

acquiring a preset alarm information template;

filling the abnormal data and the abnormal processing mode into the alarm information template to obtain a filled alarm information template;

and taking the filled alarm information template as the alarm information.

Further, the event data is call data corresponding to a circulation node of the agent and the customer phone communication, and the result data is reply voice of the agent contained in the call data; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

performing voice recognition on the reply voice to obtain corresponding text data;

word segmentation processing is carried out on the text data to obtain a plurality of corresponding words;

acquiring a violation word set contained in the target index rule;

performing illegal word matching on the words based on the illegal word set, and judging whether illegal keywords successfully matched with the illegal word set exist in the words;

if yes, the illegal keywords are screened out from the words, and the illegal keywords are used as abnormal data in the result data.

Further, the event data is processing description data of each operation link contained in the designated operation allocated to the service personnel, and the result data is processing aging data contained in the processing description data of each operation link; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

acquiring a specified processing time limit corresponding to each operation link contained in the target index rule;

screening specified treatment aging data exceeding corresponding specified treatment time limit from all the treatment aging data;

and taking the specified processing aging data as abnormal data in the result data.

Further, the event data records video for the work of business personnel; the result data is image data in the work recording video; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

screening the image data in the work record video to obtain a business interaction image included in the work record video;

Screening target images which do not accord with interaction specifications contained in the target index rules from the business interaction images based on the target index rules;

and taking the target image as abnormal data in the result data.

Further, before the step of obtaining the target index rule corresponding to the target link type from the preset rule base, the method further includes:

receiving a rule configuration request triggered by a user;

responding to the rule configuration request, and displaying a preset rule configuration page;

receiving rule configuration information input by the user in the rule configuration page;

performing rule configuration processing based on the rule configuration information to generate a corresponding rule;

acquiring a link type corresponding to the rule;

and storing the rule into the rule base based on the link type.

In order to solve the above technical problems, the embodiment of the present application further provides a data processing apparatus, which adopts the following technical scheme:

the first acquisition module is used for acquiring event data which is sent by the business system and corresponds to the circulation node of the target service;

the analysis module is used for analyzing the event data to obtain corresponding result data;

The second acquisition module is used for acquiring a target link type corresponding to the circulation node of the target service;

the third acquisition module is used for acquiring a target index rule corresponding to the target link type from a preset rule base;

the verification module is used for verifying the result data based on the target index rule and identifying abnormal data in the result data;

and the sending module is used for sending an alarm notification to the service system based on the abnormal data.

In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical schemes:

analyzing the event data to obtain corresponding result data;

In order to solve the above technical problems, an embodiment of the present application further provides a computer readable storage medium, which adopts the following technical schemes:

analyzing the event data to obtain corresponding result data;

Compared with the prior art, the embodiment of the application has the following main beneficial effects:

the embodiment of the application firstly acquires event data which is sent by a business system and corresponds to a circulation node of a target service; then analyzing the event data to obtain corresponding result data; then, obtaining a target link type corresponding to the circulation node of the target service; subsequently, a target index rule corresponding to the target link type is obtained from a preset rule base; further verifying the result data based on the target index rule, and identifying abnormal data in the result data; and finally, sending an alarm notification to the service system based on the abnormal data. After event data corresponding to a circulation node of a target service, which is sent by a service system, is received, the embodiment of the application automatically acquires a target index rule corresponding to the circulation node of the target service from a preset rule base, and further checks the result data based on the target index rule, so as to automatically and quickly identify abnormal data in the result data, and sends an alarm notification to the service system based on the abnormal data. The method can realize the rapid and accurate identification of the abnormal data from the result data contained in the event data based on the use of the index rule constructed in advance, and improves the processing efficiency of the abnormal verification of the result data. And the follow-up sending of alarm notice to the service system based on the abnormal data can promote the operation and maintenance personnel of the service system to perform abnormal intervention in time, and solve the service abnormality as early as possible, thereby effectively reducing the generation of customer complaints.

Drawings

In order to more clearly illustrate the solution of the present application, a brief description will be given below of the drawings required for the description of the embodiments of the present application, it being apparent that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without the exercise of inventive effort for a person of ordinary skill in the art.

FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;

FIG. 2 is a flow chart of one embodiment of a data processing method according to the present application;

FIG. 3 is a schematic diagram of one embodiment of a data processing apparatus according to the present application;

FIG. 4 is a schematic structural diagram of one embodiment of a computer device in accordance with the present application.

Detailed Description

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

In order to make the person skilled in the art better understand the solution of the present application, the technical solution of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings.

As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.

The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.

The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.

It should be noted that, the data processing method provided by the embodiment of the present application is generally executed by a server/terminal device, and accordingly, the data processing apparatus is generally disposed in the server/terminal device.

It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.

With continued reference to FIG. 2, a flow chart of one embodiment of a data processing method according to the present application is shown. The order of the steps in the flowchart may be changed and some steps may be omitted according to various needs. The data processing method provided by the embodiment of the application can be applied to any scene needing abnormal data alarming, and the product recommending method can be applied to products of the scenes, for example, abnormal data alarming in the field of financial insurance or digital medical treatment. The data processing method comprises the following steps:

step S201, obtaining event data corresponding to a circulation node of a target service, wherein the event data is sent by a business system.

In this embodiment, the electronic device (e.g., the server/terminal device shown in fig. 1) on which the data processing method operates may acquire the event data through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection. The specific execution subject of the embodiment is a service quality control platform. The business system can be a medical management system, an insurance system, a banking system, a transaction system, an order system and the like. The business system sends the circulation node or state of the service to the service quality control platform in the form of event data.

Step S202, analyzing the event data to obtain corresponding result data.

In this embodiment, different types of event data correspond to different result data. For example, if the event data is call data corresponding to a circulation node where an agent communicates with a customer phone, the corresponding result data is a reply voice of the agent contained in the call data; if the event data are the processing description data of each operation link contained in the appointed operation allocated to the service personnel, the corresponding result data are the processing aging data contained in the processing description data of each operation link; and if the event data is the work record video of the business personnel, the corresponding result data is the image data in the work record video.

Step S203, obtaining a target link type corresponding to the flow node of the target service.

In this embodiment, a link type corresponding to a streaming node of a service is constructed in advance.

Step S204, obtaining a target index rule corresponding to the target link type from a preset rule base.

In this embodiment, the rule base is a database that is built in advance and stores index rules that are respectively matched with various link types. The above detailed construction process of the rule base will be described in further detail in the following embodiments, which will not be described herein.

Step S205, verifying the result data based on the target index rule, and identifying abnormal data in the result data.

In this embodiment, the verification is performed on the result data based on the target index rule, and a specific implementation process of the abnormal data in the result data is identified.

And step S206, sending an alarm notification to the service system based on the abnormal data.

In this embodiment, the foregoing specific implementation process of sending the alarm notification to the service system based on the abnormal data will be described in further detail in the following specific embodiments, which will not be described herein.

Firstly, acquiring event data which is sent by a business system and corresponds to a circulation node of a target service; then analyzing the event data to obtain corresponding result data; then, obtaining a target link type corresponding to the circulation node of the target service; subsequently, a target index rule corresponding to the target link type is obtained from a preset rule base; further verifying the result data based on the target index rule, and identifying abnormal data in the result data; and finally, sending an alarm notification to the service system based on the abnormal data. After event data corresponding to a circulation node of a target service, which is sent by a service system, is received, the target index rule corresponding to the circulation node of the target service is automatically obtained from the preset rule base, and then the result data is checked based on the target index rule, so that abnormal data in the result data can be automatically and rapidly identified, and an alarm notification is sent to the service system based on the abnormal data. The method can realize the rapid and accurate identification of the abnormal data from the result data contained in the event data based on the use of the index rule constructed in advance, and improves the processing efficiency of the abnormal verification of the result data. And the follow-up sending of alarm notice to the service system based on the abnormal data can promote the operation and maintenance personnel of the service system to perform abnormal intervention in time, and solve the service abnormality as early as possible, thereby effectively reducing the generation of customer complaints.

In some alternative implementations, step S206 includes the steps of:

and acquiring a notification mode corresponding to the target link type.

In this embodiment, for different link types, matched notification modes are set for the various link types in advance, where the notification modes may include modes such as in-station information, mail, short message, and the like.

And generating corresponding alarm information based on the abnormal data.

In this embodiment, the foregoing specific implementation process of generating the corresponding alarm information based on the abnormal data will be described in further detail in the following specific embodiments, which are not described herein.

And determining operation and maintenance personnel corresponding to the service system.

In this embodiment, the operation and maintenance personnel are personnel performing operation and maintenance management on the service system.

In this embodiment, the communication information corresponding to the notification manner may be obtained by the operation and maintenance personnel based on the notification manner, and the alarm information may be pushed to the operation and maintenance personnel based on the communication information.

The method comprises the steps of obtaining a notification mode corresponding to the type of the target link; then generating corresponding alarm information based on the abnormal data; then determining operation staff corresponding to the service system; and pushing the alarm information to the operation and maintenance personnel based on the notification mode. After the abnormal data in the result data are identified based on the use of the target index rule, the method and the system also intelligently and timely generate the corresponding alarm information based on the abnormal data, and push the alarm information to operation and maintenance personnel of a service system according to the notification mode corresponding to the target link type, so that the operation and maintenance personnel can be prompted to perform abnormal intervention in time, service abnormality is solved as early as possible, and accordingly customer complaints can be effectively reduced.

In some optional implementations of this embodiment, the generating the corresponding alert information based on the abnormal data includes the following steps:

and acquiring an exception handling mode corresponding to the exception data.

In this embodiment, for different types of exception data, the matched exception handling modes are set for the various types of exceptions according to actual handling experience in advance.

And acquiring a preset alarm information template.

In this embodiment, the alert information template is an information template created in advance according to an actual alert service requirement.

Filling the abnormal data and the abnormal processing mode into the alarm information template to obtain a filled alarm information template.

In this embodiment, the alert information template includes a data field and a processing mode field, and the filled alert information template may be obtained by filling the abnormal data into a filling position of the data field in the alert information template and filling the abnormal processing mode into a filling position of the processing mode field in the alert information template.

And taking the filled alarm information template as the alarm information.

The application obtains the abnormal processing mode corresponding to the abnormal data; then acquiring a preset alarm information template; filling the abnormal data and the abnormal processing mode into the alarm information template to obtain a filled alarm information template; and taking the filled alarm information template as the alarm information. According to the method and the device for generating the alarm information, after the abnormal data in the result data are identified based on the use of the target index rule, the abnormal processing mode corresponding to the abnormal data is further acquired, and then the alarm information template is filled by the abnormal data and the abnormal processing mode, so that corresponding alarm information can be generated quickly and conveniently, and the intelligent of generating the alarm information is improved. The alarming information is pushed to operation and maintenance personnel of the service system in the follow-up process, so that the operation and maintenance personnel can conduct abnormal intervention in time, service abnormality is solved as soon as possible, and therefore the generation of customer complaints can be effectively reduced.

In some optional implementation manners, the event data is call data corresponding to a circulation node of the agent and the customer phone communication, and the result data is reply voice of the agent contained in the call data; step S205 includes the steps of:

And carrying out voice recognition on the reply voice to obtain corresponding text data.

In this embodiment, the reply voice may be subjected to voice recognition based on the existing voice recognition technology, so as to obtain corresponding text data.

And performing word segmentation processing on the text data to obtain a plurality of corresponding words.

In this embodiment, a jieba tool may be used to perform word segmentation on the text data to obtain an initial word, and then perform deactivated word filtering on the first word to obtain the word, so as to ensure accuracy of the generated word. For example, in the context of communication between a financial insurance agent and a customer, the reply voice may include: the related insurance information of health insurance is sent to the mobile phone of you later through a short message mode.

And obtaining a violation word set contained in the target index rule.

In this embodiment, the target index rule is a pre-configured generated index rule applied to a circulation node where an agent communicates with a client phone, where the target index rule is used to check whether a violation word exists in a reply voice of the agent contained in call data corresponding to the circulation node where the agent communicates with the client phone. The violation word set can be constructed according to the collection of the violations existing in the business.

And carrying out illegal word matching on the words based on the illegal word set, and judging whether illegal keywords successfully matched with the illegal word set exist in the words.

In this embodiment, by using a parallel comparison instruction, each word obtained by word segmentation in the text data is respectively matched with each keyword in the offensive word set, so as to improve the processing efficiency of word matching.

In this embodiment, if the text data includes the offending word, it indicates that the text data is abnormal, that is, the event data corresponding to the circulation node of the target service has abnormal data.

The application obtains corresponding text data by carrying out voice recognition on the reply voice; then word segmentation processing is carried out on the text data to obtain a plurality of corresponding words; then obtaining a violation word set contained in the target index rule; subsequently, carrying out illegal word matching on the words based on the illegal word set, and judging whether illegal keywords successfully matched with the illegal word set exist in the words or not; if yes, the illegal keywords are screened out from the words, and the illegal keywords are used as abnormal data in the result data. The application can realize the rapid and convenient abnormal verification of the reply voice of the agent contained in the call data corresponding to the circulation node communicated with the customer telephone by using the target index rule, so as to realize the rapid and accurate recognition of the abnormal illegal keyword data from the reply voice, improve the processing efficiency of the abnormal verification of the result data, be beneficial to the subsequent sending of alarm notification to the service system based on the abnormal data, promote the operation and maintenance personnel of the service system to perform abnormal intervention in time, solve the service abnormality as early as possible, and effectively reduce the generation of customer complaints.

In some optional implementations, the event data is processing description data of each job link included in a designated job allocated to a service person, and the result data is processing aging data included in the processing description data of each job link; step S205 includes the steps of:

and acquiring a specified processing time limit corresponding to each operation link contained in the target index rule.

In this embodiment, the target index rule is a pre-configured generated index rule applied to a circulation node for distributing a job to a business person, where the target index rule is used to check whether processing aging data included in processing description data of each job link included in a specified job distributed to the business person meets a preset specified processing time limit. The specified processing time limit can be set according to actual business processing requirements.

And screening out the specified treatment aging data exceeding the corresponding specified treatment time limit from all the treatment aging data.

In this embodiment, for different operation links, a predetermined processing time limit corresponding to each operation link is previously constructed.

In this embodiment, if specified processing time limit data exceeding a corresponding specified processing time limit exists in all the processing time limit data, it indicates that abnormality exists in the processing time limit data, that is, abnormality data exists in event data applied to a circulation node that distributes a job to a business person.

The method comprises the steps of obtaining a specified processing time limit corresponding to each operation link contained in the target index rule; and subsequently screening out specified treatment aging data exceeding a corresponding specified treatment time limit from all the treatment aging data, and taking the specified treatment aging data as abnormal data in the result data. The application can realize the rapid and convenient abnormal verification of the processing aging data contained in the processing description data of each operation link contained in the appointed operation of the service personnel through the use of the target index rule, so as to realize the rapid and accurate identification of the abnormal appointed processing aging data from the processing aging data, improve the processing efficiency of the abnormal verification of the result data, be beneficial to the subsequent sending of alarm notification to the service system based on the abnormal data, promote the operation and maintenance personnel of the service system to perform abnormal intervention in time, solve the service abnormality as early as possible, and effectively reduce the generation of customer complaints.

In some optional implementations of this embodiment, the event data is a video of a business person's work record; the result data is image data in the work recording video; step S205 includes the steps of:

and screening the image data in the work record video to obtain the business interaction image included in the work record video.

In this embodiment, the service interaction image refers to an image including interactions between service personnel and users. The images of simultaneous business personnel and users can be screened from the image data in the work record video to be used as the business interaction images.

And screening target images which do not accord with the interaction specification contained in the target index rule from the business interaction images based on the target index rule.

In this embodiment, the target index rule is a pre-configured generated index rule applied to a transfer node of a working record video of a shooting service person, where the target index rule is used to check whether image data included in the working record video of the service person meets a preset interaction specification. The interaction specification can be set according to actual business processing requirements, and includes rules that business personnel need to form a group picture with a customer on a sickbed, and the like.

And taking the target image as abnormal data in the result data.

In this embodiment, if a target image that does not meet the interaction specification included in the target index rule is selected from the service interaction images, it indicates that there is an abnormality in image data included in the work recording video of the service person, that is, there is abnormal data in event data applied to a circulation node that photographs the work recording video of the service person.

The application obtains the business interaction image included in the work recording video by screening the image data in the work recording video; and subsequently, based on the target index rule, screening target images which do not accord with the interaction specification contained in the target index rule from the business interaction images, and taking the target images as abnormal data in the result data. The application can realize the rapid and convenient abnormal verification of the image data contained in the work record video of the business personnel through the use of the target index rule, so as to realize the rapid and accurate identification of the abnormal target image which does not accord with the interaction specification contained in the target index rule from the image data, improve the processing efficiency of the abnormal verification of the result data, be beneficial to the subsequent sending of alarm notification to the business system based on the abnormal data, promote the operation and maintenance personnel of the business system to perform abnormal intervention in time, solve the service abnormality as early as possible, and effectively reduce the generation of customer complaints.

In some optional implementations of this embodiment, before step S204, the electronic device may further perform the following steps:

and receiving a rule configuration request triggered by a user.

In this embodiment, a configuration function of an index rule is preset to support configuration of the index rule for different link types in the service.

And responding to the rule configuration request, and displaying a preset rule configuration page.

In this embodiment, the rule configuration page is a page for configuring an index rule created according to an actual index rule construction service requirement.

And receiving rule configuration information input by the user in the rule configuration page.

In this embodiment, the rule configuration information includes basic information, quality control link information, and quality control index information. The basic information may include a quality control name, a quality control description, an applicable SOP, an applicable service item, etc.; the quality control link information can comprise a job name, a link serial number, a link name and the like; the quality control index information can comprise index names, time-effect calculation ranges, reminding types, reminding triggers, reminding objects, reminding modes, reminding speaking technologies and the like.

And carrying out rule configuration processing based on the rule configuration information to generate a corresponding rule.

In this embodiment, the required index rule may be configured by integrating rule configuration information input by the user and performing rule configuration processing.

And acquiring the link type corresponding to the rule.

In this embodiment, link type information may be obtained from the rule configuration information, so as to be used as a link type for configuring the rule generating credit.

And storing the rule into the rule base based on the link type.

In this embodiment, a data association relationship between the link type and the rule may be generated, and the rule may be stored in the rule base based on the data association relationship, so that a corresponding rule may be quickly queried from the rule base based on the link type.

After receiving a rule configuration request triggered by a user, responding to the rule configuration request, and displaying a preset rule configuration page; then receiving rule configuration information input by the user in the rule configuration page; then, rule configuration processing is carried out based on the rule configuration information, and corresponding rules are generated; subsequently obtaining a link type corresponding to the rule; and finally, storing the rule into the rule base based on the link type. After receiving the rule configuration request triggered by the user, the method and the device can intelligently and rapidly construct the corresponding rule according to the rule configuration information input by the user in the rule configuration page, so that the flexible configuration of the rule according to the personal requirements of the user is realized, the rule configuration efficiency is effectively improved, and the use experience of the user is improved. In addition, the rules are stored into the rule base based on link types corresponding to the rules, so that the intelligent storage of the rules is realized, the corresponding rules can be quickly queried from the rule base based on the link types, and the rule extraction efficiency is improved.

It should be emphasized that, to further ensure the privacy and security of the exception data, the exception data may also be stored in a blockchain node.

The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.

The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.

With further reference to fig. 3, as an implementation of the method shown in fig. 2 described above, the present application provides an embodiment of a data processing apparatus, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.

As shown in fig. 3, the data processing apparatus 300 according to the present embodiment includes: a first acquisition module 301, an analysis module 302, a second acquisition module 303, a third acquisition module 304, a verification module 305, and a transmission module 306. Wherein:

a first obtaining module 301, configured to obtain event data corresponding to a circulation node of a target service, where the event data is sent by a service system;

the analysis module 302 is configured to analyze the event data to obtain corresponding result data;

a second obtaining module 303, configured to obtain a target link type corresponding to a circulation node of the target service;

the third obtaining module 304 is configured to obtain a target index rule corresponding to the target link type from a preset rule base;

a verification module 305, configured to verify the result data based on the target indicator rule, and identify abnormal data in the result data;

and a sending module 306, configured to send an alarm notification to the service system based on the abnormal data.

In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the data processing method in the foregoing embodiment one by one, and are not described herein again.

In some alternative implementations of the present embodiment, the sending module 306 includes:

the first acquisition sub-module is used for acquiring a notification mode corresponding to the target link type;

the generation sub-module is used for generating corresponding alarm information based on the abnormal data;

the first determining submodule is used for determining operation and maintenance personnel corresponding to the service system;

and the pushing sub-module is used for pushing the alarm information to the operation and maintenance personnel based on the notification mode.

In some optional implementations of the present embodiment, generating the sub-module includes:

the first acquisition unit is used for acquiring an abnormal processing mode corresponding to the abnormal data;

the second acquisition unit is used for acquiring a preset alarm information template;

the filling unit is used for filling the abnormal data and the abnormal processing mode into the alarm information template to obtain a filled alarm information template;

And the determining unit is used for taking the filled alarm information template as the alarm information.

In some optional implementations of this embodiment, the event data is call data corresponding to a circulation node where an agent communicates with a customer phone, and the result data is a reply voice of the agent included in the call data; the verification module 305 includes:

the recognition module is used for carrying out voice recognition on the reply voice to obtain corresponding text data;

the processing module is used for carrying out word segmentation processing on the text data to obtain a plurality of corresponding words;

the second acquisition submodule is used for acquiring the violation word set contained in the target index rule;

the judging sub-module is used for carrying out illegal word matching on the words based on the illegal word set and judging whether illegal keywords successfully matched with the illegal word set exist in the words or not;

and the second determining submodule is used for screening out the violation keywords from the words if yes, and taking the violation keywords as abnormal data in the result data.

In some optional implementations of this embodiment, the event data is process description data of each job link included in a specified job allocated to a service person, and the result data is process aging data included in the process description data of each job link; the verification module 305 includes:

a third obtaining sub-module, configured to obtain a specified processing time limit corresponding to each of the operation links included in the target index rule;

the first screening submodule is used for screening specified treatment aging data exceeding corresponding specified treatment time limit from all the treatment aging data;

and a third determining submodule, configured to take the specified processing aging data as abnormal data in the result data.

In some optional implementations of this embodiment, the event data is a video of a business person's work record; the result data is image data in the work recording video; the verification module 305 includes:

The second screening sub-module is used for screening the image data in the work record video and acquiring a business interaction image included in the work record video;

a third screening sub-module, configured to screen, based on the target index rule, a target image that does not conform to an interaction specification included in the target index rule from the service interaction images;

and a fourth determining sub-module, configured to use the target image as abnormal data in the result data.

In some optional implementations of this embodiment, the data processing apparatus further includes:

the first receiving module is used for receiving a rule configuration request triggered by a user;

the display module is used for responding to the rule configuration request and displaying a preset rule configuration page;

the second receiving module is used for receiving rule configuration information input by the user in the rule configuration page;

the generation module is used for carrying out rule configuration processing based on the rule configuration information and generating corresponding rules;

A fourth obtaining module, configured to obtain a link type corresponding to the rule;

and the storage module is used for storing the rule into the rule base based on the link type.

In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 4, fig. 4 is a basic structural block diagram of a computer device according to the present embodiment.

The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It should be noted that only computer device 4 having components 41-43 is shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.

The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.

The memory 41 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 4. Of course, the memory 41 may also comprise both an internal memory unit of the computer device 4 and an external memory device. In this embodiment, the memory 41 is typically used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of a data processing method. Further, the memory 41 may be used to temporarily store various types of data that have been output or are to be output.

The processor 42 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the data processing method.

The network interface 43 may comprise a wireless network interface or a wired network interface, which network interface 43 is typically used for establishing a communication connection between the computer device 4 and other electronic devices.

in the embodiment of the application, firstly, event data which is sent by a business system and corresponds to a circulation node of a target service is obtained; then analyzing the event data to obtain corresponding result data; then, obtaining a target link type corresponding to the circulation node of the target service; subsequently, a target index rule corresponding to the target link type is obtained from a preset rule base; further verifying the result data based on the target index rule, and identifying abnormal data in the result data; and finally, sending an alarm notification to the service system based on the abnormal data. After event data corresponding to a circulation node of a target service, which is sent by a service system, is received, the embodiment of the application automatically acquires a target index rule corresponding to the circulation node of the target service from a preset rule base, and further checks the result data based on the target index rule, so as to automatically and quickly identify abnormal data in the result data, and sends an alarm notification to the service system based on the abnormal data. The method can realize the rapid and accurate identification of the abnormal data from the result data contained in the event data based on the use of the index rule constructed in advance, and improves the processing efficiency of the abnormal verification of the result data. And the follow-up sending of alarm notice to the service system based on the abnormal data can promote the operation and maintenance personnel of the service system to perform abnormal intervention in time, and solve the service abnormality as early as possible, thereby effectively reducing the generation of customer complaints.

The present application also provides another embodiment, namely, a computer-readable storage medium storing computer-readable instructions executable by at least one processor to cause the at least one processor to perform the steps of the data processing method as described above.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.

It is apparent that the above-described embodiments are only some embodiments of the present application, but not all embodiments, and the preferred embodiments of the present application are shown in the drawings, which do not limit the scope of the patent claims. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a thorough and complete understanding of the present disclosure. Although the application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing description, or equivalents may be substituted for elements thereof. All equivalent structures made by the content of the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the scope of the application.

Claims

1. A method of data processing comprising the steps of:

analyzing the event data to obtain corresponding result data;

2. The data processing method according to claim 1, wherein the step of sending an alarm notification to the service system based on the abnormal data specifically comprises:

acquiring a notification mode corresponding to the target link type;

generating corresponding alarm information based on the abnormal data;

determining operation staff corresponding to the service system;

3. The data processing method according to claim 2, wherein the step of generating the corresponding alarm information based on the abnormal data specifically includes:

Acquiring an exception handling mode corresponding to the exception data;

acquiring a preset alarm information template;

and taking the filled alarm information template as the alarm information.

4. The data processing method according to claim 1, wherein the event data is call data corresponding to a circulation node where an agent communicates with a customer phone, and the result data is a reply voice of the agent contained in the call data; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

acquiring a violation word set contained in the target index rule;

5. The data processing method according to claim 1, wherein the event data is process description data of each of the job links included in the designated job assigned to the business person, and the result data is process aging data included in the process description data of each of the job links; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

6. The data processing method according to claim 1, wherein the event data is a work record video of business personnel; the result data is image data in the work recording video; the step of verifying the result data based on the target index rule and identifying the abnormal data in the result data specifically includes:

and taking the target image as abnormal data in the result data.

7. The data processing method according to claim 1, further comprising, before the step of acquiring a target index rule corresponding to the target link type from a preset rule base:

receiving a rule configuration request triggered by a user;

acquiring a link type corresponding to the rule;

and storing the rule into the rule base based on the link type.

8. A data processing apparatus, comprising:

9. A computer device comprising a memory having stored therein computer readable instructions which when executed by a processor implement the steps of the data processing method of any of claims 1 to 7.

10. A computer-readable storage medium, having stored thereon computer-readable instructions which, when executed by a processor, implement the steps of the data processing method according to any of claims 1 to 7.