CN113157741A - Service state visualization method and device based on dimension conversion and electronic equipment - Google Patents
Service state visualization method and device based on dimension conversion and electronic equipment Download PDFInfo
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Abstract
The embodiment of the specification provides a service state visualization method based on dimension conversion, which includes constructing a display generation module, including a display material library and display rules, configuring the display rules and displaying material generation page content according to display parameters, acquiring original service data in a current control period, generating a first data table, processing the first data table as a material, converting the dimensions of the data in the first data table according to preset dimension conversion rules, calculating the data in the first data table by using the converted dimensions to obtain the data after the dimensions are converted, mining a new analysis angle, generating a second data table, determining the state of the data after the dimensions are converted, reducing dependence and randomness on manual evaluation, generating a visualization page with the data after the dimensions are converted and state marks by using the display generation module, abstracting the service, and marking the service, The potential state is displayed intuitively, and the dependence on human subjective analysis is small, so that the accuracy of service monitoring can be improved.
Description
Technical Field
The application relates to the field of internet, in particular to a service state visualization method and device based on dimension conversion and an electronic device.
Background
For service monitoring, data to be monitored is usually directly set at the front end, and the front end synchronously displays the data in real time after receiving the data, so that the real situation of the monitored service can be known.
However, this mode still mainly monitors the original data of the service directly at present, and with continuous innovation of the service mode in the service scene, the description mode and the analysis angle of the service state are gradually complex, and if the service is still monitored by using the operator data, the potential analysis angle is easily omitted, and it is difficult to accurately grasp the current state of the service.
Therefore, it is necessary to provide a new method to improve the accuracy of service monitoring.
Disclosure of Invention
The embodiment of the specification provides a service state visualization method and device based on dimension conversion and electronic equipment, and is used for improving the accuracy of service monitoring.
An embodiment of the present specification provides a service state visualization method based on dimension conversion, including:
constructing a display generation module, wherein the display generation module comprises a display material library and a display rule, and configuring the display rule and displaying the material according to display parameters to generate page content;
acquiring original service data in a current control period, and generating a first data table;
converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data with converted dimensionality, and generating a second data table;
and determining the state of the data after the dimensionality is converted, and generating a visual page with the data after the dimensionality is converted and a state mark by using a display generation module.
Optionally, the converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule includes:
and determining the current service type, and converting the dimensionality of the data in the first data table according to a dimensionality conversion rule corresponding to the current service type.
Optionally, the determining the state of the data after the dimensionality conversion includes:
and constructing and training a business state recognition model, and recognizing the state of the data after dimensionality conversion by using the constructed business state recognition model.
Optionally, the method further comprises:
and acquiring a service correction strategy in a historical period, and extracting service link information to generate a dimension conversion rule.
Optionally, the extracting fault link information and generating a dimension conversion rule includes:
and clustering the service link information, identifying the dimension of the service link information which is clustered into the same class, and taking the identified dimension as the dimension after conversion in the dimension conversion rule.
Optionally, the clustering the service link information includes: and performing semi-supervised clustering on the labels of the business link information in combination with the user.
Optionally, the generating, by using the presentation generating module, the visualized page with the data and the state tag after the dimension conversion further includes:
and updating the data and the state mark after dimensionality conversion in the visual page in real time.
Optionally, the method further comprises:
and configuring an early warning pushing rule with a risk level, and pushing early warning information to a user when the state of the data after dimension conversion meets the risk level.
Optionally, the configuring the early warning pushing rule includes:
and configuring the risk level according to the reaction time of the user.
An embodiment of the present specification provides a service state visualization device based on dimension conversion, including:
the data acquisition module is used for acquiring original service data in the current control period and generating a first data table;
the conversion module is used for converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data after dimensionality conversion, and generating a second data table;
and the visualization module is used for determining the state of the data after the dimensionality is converted and generating a visualization page with the data after the dimensionality is converted and a state mark.
Optionally, the converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule includes:
and determining the current service type, and converting the dimensionality of the data in the first data table according to a dimensionality conversion rule corresponding to the current service type.
Optionally, the determining the state of the data after the dimensionality conversion includes:
and constructing and training a business state recognition model, and recognizing the state of the data after dimensionality conversion by using the constructed business state recognition model.
Optionally, the method further comprises:
and acquiring a service correction strategy in a historical period, and extracting service link information to generate a dimension conversion rule.
Optionally, the extracting fault link information and generating a dimension conversion rule includes:
and clustering the service link information, identifying the dimension of the service link information which is clustered into the same class, and taking the identified dimension as the dimension after conversion in the dimension conversion rule.
Optionally, the clustering the service link information includes: and performing semi-supervised clustering on the labels of the business link information in combination with the user.
Optionally, the generating, by using the presentation generating module, the visualized page with the data and the state tag after the dimension conversion further includes:
and updating the data and the state mark after dimensionality conversion in the visual page in real time.
Optionally, the method further comprises:
and configuring an early warning pushing rule with a risk level, and pushing early warning information to a user when the state of the data after dimension conversion meets the risk level.
Optionally, the configuring the early warning pushing rule includes:
and configuring the risk level according to the reaction time of the user.
An embodiment of the present specification further provides an electronic device, where the electronic device includes:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform any of the methods described above.
The present specification also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement any of the above methods.
The various technical schemes provided by the embodiment of the specification configure the display rule and display material generation page content by constructing a display generation module comprising a display material library and a display rule according to display parameters, acquire original business data in the current control period, generate a first data table, process the first data table as a material, convert the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculate the data in the first data table by using the converted dimensionality to obtain the data after dimensionality conversion, mine a new analysis angle, generate a second data table, determine the state of the data after dimensionality conversion, reduce the dependence and randomness on manual evaluation, generate a visual page with the data after dimensionality conversion and state marks by using the display generation module, and visually display the abstract and potential states of business, the dependence on the artificial subjective analysis is small, so that the accuracy of service monitoring can be improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic diagram illustrating a business state visualization method based on dimension transformation according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a service state visualization device based on dimension conversion according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic diagram of a business state visualization method based on dimension transformation according to an embodiment of the present disclosure, where the method may include:
s101, constructing a display generation module, wherein the display generation module comprises a display material library and a display rule, and configuring the display rule and displaying the material according to display parameters to generate page content.
In the embodiment of the present specification, in order to enable a page to automatically process and display service data according to a preset requirement, a display generation module may be constructed. The display generation module includes a display material library as one of data bases, and also includes a display rule, and the display rule may be configured with a page style and may also be configured with a display logic, for example, from which dimension the display is to be performed.
In this embodiment, the presentation generation module may have a configuration interface, and the user may configure the material and the page content to be presented by manually configuring the parameters.
Specifically, here, the user may select various types of services to select a service of data to be monitored.
Of course, this may mean that the user causes the presentation generation module to automatically generate the data processing logic by way of parameter configuration, and does not need to configure in a way of developing page codes.
By configuring the presentation parameters, a dimension conversion rule can be generated.
S102, acquiring original service data in the current control period and generating a first data table.
In this embodiment of the present specification, we may collect corresponding original service data through a service type corresponding to a display parameter configured by a user, and report the original service data to a database of a server to generate a data table, which is referred to as a first data table.
The acquired service raw data may be at least one of user information participating in the service, behavior information of the user, response state information of the page, and the like, and of course, the service raw data may also be data of various attributes.
The obtaining of the original service data in the current control period may be that the server obtains the original service data in the current control period, so that the server may directly store the obtained data in a database, and generate a first data table in the database.
Here, the current management and control period may be a preset period, such as daily, weekly, and monthly.
S103, converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data with converted dimensionality, and generating a second data table.
In an embodiment of this specification, the converting, according to a preset dimension conversion rule, a dimension of data in a first data table includes:
and determining the current service type, and converting the dimensionality of the data in the first data table according to a dimensionality conversion rule corresponding to the current service type.
The preset conversion rule may include dimension information before conversion, dimension information after conversion, and a conversion function.
The converted dimension information may be preset or obtained through temporary learning.
In the latter scenario, this may mean that the service metadata collected in the current management and control period has a new dimension, or the dimension combination mode of the service staff data is a new combination mode, and at this time, since it is difficult to find the newly added service raw data in time, the optimal converted dimension and conversion function may not be defined in time by the setting mode.
Therefore, by means of learning, when a new dimension combination or a new data attribute of a salesman appears in a set of business raw data in the background, the user can learn the dimension to describe the business state.
Therefore, in the embodiment of the present specification, the method may further include:
and processing a data attribute combination formed by multiple service original data acquired in the current control period by using a conversion relation recognition model which is constructed and trained in advance, and outputting the converted attribute information of the single dimension and the conversion function of the converted single dimension data and the dimensional data under the combination.
In the embodiment of the present specification, it is considered that in actual application, when an operator identifies a service abnormality, the operator often needs to locate and troubleshoot the abnormality reason to perform troubleshooting, and if the converted dimensionality corresponds to each failure reason, a user can directly judge which link the abnormality is, according to the state of the converted dimensionality data, without repeatedly reasoning the abnormal link according to a plurality of data, so that the efficiency is high.
The method directly obtains the dimension data of a certain link state reflected by the back of various operator data in a self-conversion mode, and the abnormality of which state can be directly identified according to the dimension data.
Therefore, when the conversion relation recognition model is constructed, the converted dimensionality can be corresponding to the abnormal links collected in the historical time.
For which abnormal links exist in historical time, the abnormal links can be obtained from a business correction strategy, and even dimension conversion rules can be extracted from the abnormal links.
Therefore, in the embodiment of the present specification, the method may further include:
and acquiring a service correction strategy in a historical period, and extracting service link information to generate a dimension conversion rule.
Considering that the same abnormal reason may cause fluctuation of multiple service raw data, if the combination of the multiple service member data can be analyzed, the abnormal reason corresponding to the service raw data with multiple attributes can be known.
Therefore, in an embodiment of this specification, the extracting fault link information to generate a dimension conversion rule includes:
and clustering the service link information, identifying the dimension of the service link information which is clustered into the same class, and taking the identified dimension as the dimension after conversion in the dimension conversion rule.
In an embodiment of this specification, the clustering service link information includes: and performing semi-supervised clustering on the labels of the business link information in combination with the user.
Through clustering, potential analysis dimensionality can be fully mined, and dimensionality describing business states is abstracted.
Of course, in the embodiment of this specification, it is considered that one anomaly may cause an anomaly of multiple original data with continuous service logics, and therefore, we may also extract the converted data dimension according to the logical links of multiple service original data, define different anomaly logical links as different anomalies and corresponding converted dimensions, that is, not only identify the combination manner of the service original data with multiple attributes, but also identify the arrangement manner of the service original data with multiple attributes in the combination, and extract the converted dimensions according to the arrangement manner, which is not described in detail herein.
And S104, determining the state of the data after dimension conversion, and generating a visual page with the data after dimension conversion and a state mark by using a display generation module.
The method comprises the steps of constructing a display generation module which comprises a display material library and a display rule, configuring the display rule and displaying material generation page content according to display parameters, obtaining original business data in a current control period, generating a first data table to be used as a material for processing, converting dimensionality of data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data after dimensionality conversion, mining a new analysis angle, generating a second data table, determining the state of the data after dimensionality conversion, reducing dependence and randomness on manual evaluation, generating a visual page with the data after dimensionality conversion and state marks by using the display generation module, visually displaying abstract and potential states of the business, and having small dependence on subjective analysis of people, therefore, the accuracy of service monitoring can be improved.
In an embodiment of the present specification, the determining the state of the data after converting the dimension includes:
and constructing and training a business state recognition model, and recognizing the state of the data after dimensionality conversion by using the constructed business state recognition model.
In an embodiment of this specification, the generating, by using the presentation generating module, the visualized page having the data and the state tag after the dimension conversion further includes:
and updating the data and the state mark after dimensionality conversion in the visual page in real time.
In the embodiment of this specification, still include:
and configuring an early warning pushing rule with a risk level, and pushing early warning information to a user when the state of the data after dimension conversion meets the risk level.
Therefore, risk identification and early warning can be carried out from the abstracted dimensionality without the process of artificial analysis, so that early warning can be accelerated, and the real-time performance and the reaction speed of monitoring are improved.
In an embodiment of this specification, the configuring an early warning pushing rule with a risk level includes:
and configuring the risk level according to the reaction time of the user.
This can mean in practical application that, for a user with a fast response, because the capability of handling and solving problems is stronger, the same abnormal state has a weaker risk for the user with a fast response, and has a higher risk for the user with a slow response, so that the risk level can be configured according to the response time of the user, and the self-attributes of different users can be considered, and are adapted to the self-attributes of the user.
Fig. 2 is a schematic structural diagram of a service state visualization apparatus based on dimension conversion according to an embodiment of the present disclosure, where the apparatus may include:
the data acquisition module 201 is configured to acquire service raw data in a current control period and generate a first data table;
the conversion module 202 is configured to convert the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculate the data in the first data table by using the converted dimensionality to obtain data with converted dimensionality, and generate a second data table;
and the visualization module 203 determines the state of the data after the dimensionality is converted and generates a visualization page with the data after the dimensionality is converted and a state mark.
In an embodiment of this specification, the converting, according to a preset dimension conversion rule, a dimension of data in a first data table includes:
and determining the current service type, and converting the dimensionality of the data in the first data table according to a dimensionality conversion rule corresponding to the current service type.
In an embodiment of the present specification, the determining the state of the data after converting the dimension includes:
and constructing and training a business state recognition model, and recognizing the state of the data after dimensionality conversion by using the constructed business state recognition model.
In the embodiment of this specification, still include:
and acquiring a service correction strategy in a historical period, and extracting service link information to generate a dimension conversion rule.
In an embodiment of this specification, the extracting fault link information and generating a dimension conversion rule includes:
and clustering the service link information, identifying the dimension of the service link information which is clustered into the same class, and taking the identified dimension as the dimension after conversion in the dimension conversion rule.
In an embodiment of this specification, the clustering service link information includes: and performing semi-supervised clustering on the labels of the business link information in combination with the user.
In an embodiment of this specification, the generating, by using the presentation generating module, the visualized page having the data and the state tag after the dimension conversion further includes:
and updating the data and the state mark after dimensionality conversion in the visual page in real time.
In the embodiment of this specification, still include:
and configuring an early warning pushing rule with a risk level, and pushing early warning information to a user when the state of the data after dimension conversion meets the risk level.
In an embodiment of this specification, the configuring the early warning pushing rule includes:
and configuring the risk level according to the reaction time of the user.
The device comprises a display generation module, a display material library and a display rule, wherein the display rule and the display material generation page content are configured according to display parameters, original business data in the current control period are obtained, a first data table is generated and processed as a material, the dimensionality of the data in the first data table is converted according to a preset dimensionality conversion rule, the data in the first data table is calculated by using the converted dimensionality to obtain data after dimensionality conversion, a new analysis angle is mined to generate a second data table, the state of the data after dimensionality conversion is determined, the dependence and randomness on manual evaluation are reduced, a display generation module is used for generating a visual page with the data after dimensionality conversion and state marks, the abstract and potential states of the business are visually displayed, and the dependence on subjective analysis is small, therefore, the accuracy of service monitoring can be improved.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. An electronic device 300 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, electronic device 300 is embodied in the form of a general purpose computing device. The components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting the various system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code executable by the processing unit 310 to cause the processing unit 310 to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 300, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 350. Also, the electronic device 300 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 360. Network adapter 360 may communicate with other modules of electronic device 300 via bus 330. It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 1.
Fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
A computer program implementing the method shown in fig. 1 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (12)
1. A service state visualization method based on dimension conversion is characterized by comprising the following steps:
constructing a display generation module, wherein the display generation module comprises a display material library and a display rule, and configuring the display rule and displaying the material according to display parameters to generate page content;
acquiring original service data in a current control period, and generating a first data table;
converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data with converted dimensionality, and generating a second data table;
and determining the state of the data after the dimensionality is converted, and generating a visual page with the data after the dimensionality is converted and a state mark by using a display generation module.
2. The method according to claim 1, wherein converting the dimension of the data in the first data table according to a preset dimension conversion rule comprises:
and determining the current service type, and converting the dimensionality of the data in the first data table according to a dimensionality conversion rule corresponding to the current service type.
3. The method of any of claims 1-2, wherein determining the state of the post-conversion-dimensionality data comprises:
and constructing and training a business state recognition model, and recognizing the state of the data after dimensionality conversion by using the constructed business state recognition model.
4. The method according to any one of claims 1-3, further comprising:
and acquiring a service correction strategy in a historical period, and extracting service link information to generate a dimension conversion rule.
5. The method according to any one of claims 1-4, wherein the extracting fault link information generates a dimension conversion rule, comprising:
and clustering the service link information, identifying the dimension of the service link information which is clustered into the same class, and taking the identified dimension as the dimension after conversion in the dimension conversion rule.
6. The method of any one of claims 1-5, wherein clustering business segment information comprises: and performing semi-supervised clustering on the labels of the business link information in combination with the user.
7. The method according to any one of claims 1-6, wherein the generating a visualization page with the data after the dimension conversion and the status label by using the presentation generation module further comprises:
and updating the data and the state mark after dimensionality conversion in the visual page in real time.
8. The method according to any one of claims 1-7, further comprising:
and configuring an early warning pushing rule with a risk level, and pushing early warning information to a user when the state of the data after dimension conversion meets the risk level.
9. The method of any of claims 1-8, wherein configuring the early warning push rule comprises:
and configuring the risk level according to the reaction time of the user.
10. A service state visualization device based on dimension conversion is characterized by comprising:
the data acquisition module is used for acquiring original service data in the current control period and generating a first data table;
the conversion module is used for converting the dimensionality of the data in the first data table according to a preset dimensionality conversion rule, calculating the data in the first data table by using the converted dimensionality to obtain data after dimensionality conversion, and generating a second data table;
and the visualization module is used for determining the state of the data after the dimensionality is converted and generating a visualization page with the data after the dimensionality is converted and a state mark.
11. An electronic device, wherein the electronic device comprises:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-9.
12. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-9.
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