CN110766591A - Intelligent service management method, device, terminal and storage medium - Google Patents
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Abstract
The embodiment of the invention relates to the technical field of information processing, and discloses an intelligent service management method, an intelligent service management device, an intelligent service management terminal and a storage medium. In the invention, a service set containing services to be classified is obtained; extracting all service attributes of all services to be classified and all possible values of the service attributes; calculating the product of the number of all possible values of all service attributes, and taking the product as the category number of the service to be classified; classifying the services to be classified by utilizing a clustering algorithm according to the number of the classes to obtain a classification result; and managing the service set according to the classification result. Therefore, in the service management process, the cost of service input information is reduced, the manual intervention degree is reduced, the service is classified by using the service characteristics, the secondary development of a system when a new service is added is avoided, and the purpose of intelligently managing the service is achieved.
Description
Technical Field
The embodiment of the invention relates to the technical field of information processing, in particular to an intelligent service management method, an intelligent service management device, an intelligent service management terminal and a storage medium.
Background
With the continuous development of internet technology, various industries are rapidly developed, and how to manage huge businesses more conveniently and intelligently becomes a problem to be solved urgently. The existing service management methods mainly include the following: 1) the service message is synchronized to a unified management control platform, and the service management of multiple sources, multiple outputs and multiple operation modes is provided. 2) The plug-in type service management system is characterized in that one or more plug-ins of the value added service management system are built on the basis of a unified portal management system and used for processing specific value added service functions. The portal management system manages the comprehensive public service and jumps to the value added service page through connection. 3) The IPTV distributed service management system comprises a central service management system, a regional service management system and a service display scheduling system, wherein the central service management system is provided with the regional service management system, and the regional service management system is provided with the service display scheduling system.
The inventor finds that at least the following problems exist in the prior art: in the existing service management method, various information of the service still needs to be manually input and classified, meanwhile, various established query conditions still need to be manually input for querying the service, and the found results are all displayed in a list. The whole service management process is relatively complex and time-consuming, and the operation cost is high. With the continuous development of services, the system is also continuously developed secondarily due to the customized services, the attribute information of the services is increased, and the development and maintenance cost is high.
Disclosure of Invention
The embodiment of the invention aims to provide an intelligent service management method, so that in service management, the cost of service input information is reduced, the degree of manual intervention is reduced, the manual classification of services by using service characteristics is reduced, and the secondary development of a system when a new service is added is avoided.
In order to solve the above technical problem, an embodiment of the present invention provides an intelligent service management method, including the following steps: acquiring a service set containing services to be classified; extracting all service attributes of all services to be classified and all possible values of the service attributes; calculating the product of the number of all possible values of all service attributes, and taking the product as the category number of the service to be classified; classifying the services to be classified by utilizing a clustering algorithm according to the number of the classes to obtain a classification result; and managing the service set according to the classification result.
The embodiment of the present invention further provides an intelligent service management device, including: the acquisition module is used for acquiring a service set containing services to be classified; the analysis module is used for analyzing the service attribute and the value of the service attribute and calculating the number of categories; the algorithm module is used for classifying the services to be classified by utilizing a clustering algorithm according to the category number calculated by the analysis module; and the output module outputs the classification result of the algorithm module in a visual mode.
An embodiment of the present invention further provides a terminal, including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform one of the service management methods described above.
A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements a service management method as described above.
Compared with the prior art, the embodiment of the invention classifies the services by a clustering algorithm according to the service attributes and the values of the service attributes of the existing services in the service set, and manages the services by using the classified results, so that the cost of service input information is reduced, the manual intervention degree is reduced, the manual classification of the services by using the service characteristics is reduced, and the secondary development of a system when a new service is added is avoided.
In addition, the managing the service set according to the classification result specifically includes: when the service to be classified is changed, judging whether the service attribute of the changed service to be classified or the value of the service attribute is changed; when the judgment result is yes, regenerating the number of the classes of the service to be classified; and classifying the services to be classified by utilizing the clustering algorithm according to the regenerated category number of the services to be classified. When the service is changed, the changed service is classified in real time without human intervention of a user, so that secondary development of value added service is not needed, new service data is dynamically analyzed, and service management efficiency is improved.
In addition, after extracting all the service attributes and all possible values of the service attributes of the services to be classified, the following steps are included: generating a service template according to the service attribute of the service to be classified and all possible values of the service attribute; the service template is used for recording all combinations of all possible values of the existing service attributes, and comparing the combinations with the service attributes and the values of the service attributes of the new service when the service is changed. The service template can visually display the changed service attribute characteristics and the changes of the service attribute characteristics before the change when the service is changed, reduce the input operation of a user during service management, improve the efficiency of service management, dynamically manage the service and avoid the secondary development of a system after new service is added.
In addition, the management of the service set according to the classification result specifically includes: defining a set of the same type of service as a service cluster; the service cluster is provided with an attribute label, and the content of the attribute label is all values of all service attributes of the services in the service cluster; and outputting the classification result by taking the service cluster as a unit. Therefore, the user can select any service type which the user desires to manage through the label content before management, and the service type is displayed according to the requirement of the user during output, so that the cost of service information input can be reduced, and the user experience is improved.
In addition, the outputting the classification result with the service cluster as a unit specifically includes: presetting the priority of service attributes; and outputting classification results in a layering mode according to the priority of the service attributes. Therefore, when the user demands are different, the system can output classification results in a hierarchical manner according to the user demands, and classifies the services in a more intelligent manner in the management process, so that the service management process can adapt to different user demands, and service data analysis results are output more dynamically and intelligently.
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One or more embodiments are illustrated by the corresponding figures in the drawings, which are not meant to be limiting.
FIG. 1 is a flow chart of a method of intelligent traffic management according to a first embodiment of the present invention;
FIG. 2 is a flow chart of a method of intelligent traffic management according to a second embodiment of the present invention;
fig. 3 is a block diagram of an intelligent traffic management apparatus according to a third embodiment of the present invention;
fig. 4 is a block diagram of a terminal according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments. The following embodiments are divided for convenience of description, and should not constitute any limitation to the specific implementation manner of the present invention, and the embodiments may be mutually incorporated and referred to without contradiction.
A first embodiment of the present invention relates to an intelligent service management method, and a specific flow is shown in fig. 1, including: acquiring a service set containing services to be classified; extracting all service attributes of all services to be classified and all possible values of the service attributes; calculating the product of the number of all possible values of all service attributes, and taking the product as the category number of the service to be classified; classifying the services to be classified by utilizing a clustering algorithm according to the number of the classes to obtain a classification result; and managing the service set according to the classification result.
The following describes implementation details of the intelligent service management method according to this embodiment in detail, and the following is only provided for easy understanding and is not necessary for implementing this embodiment.
The first embodiment of the invention relates to an intelligent service management method which is applied to a terminal. The specific process is shown in fig. 1, and specifically comprises the following steps:
Specifically, before performing specific management on the services, the terminal needs to classify all the services that need to be managed. After the business system is initialized, all businesses are read into a memory structure of the business system in a set mode. The set of all services contains information about all services. The service set is a set formed by all service elements to be classified, and comprises service attributes of the services to be classified and all values of all the service attributes.
And 102, classifying the service to be classified by using a clustering algorithm.
In particular, clustering algorithms are a class of algorithms that can classify data. In the present embodiment, a K-means clustering algorithm is used as an example of classifying the traffic. The scheme can be realized by adopting various clustering algorithms, and the embodiment does not form specific limitation on the scheme. The values that need to be determined before classification using the K-means clustering algorithm include: the number of classes K of the classification, the dimensionality of the classification and the value of each dimensionality.
After the service set is read into the memory, the attribute information of each service is traversed, the service attributes of all the services at present are read, and the attribute values corresponding to each service attribute are read. Firstly, initializing a set C formed by service attributes needing to be analyzedkX, y, z …, where x, y, z … are a number of different traffic attributes, corresponding to each dimension in the algorithm. And carrying out numerical assignment on the value of each service attribute, wherein the value corresponds to the value of each classification dimension in the algorithm. In addition, eachThe service attributes are independent and have different value ranges.
According to the service attribute CkWherein the value c of the attribute xx＝(x1、x2、x3…xn) There are n kinds of values c of attribute yy＝(y1、y2、y3…ym) There are m kinds. Obtaining K according to all combinations of values of various attributes:
where k is the set CkNumber of elements { x, y, z … }, ckThe number of categories of values of the attribute with sequence number k. And K is the number of categories in the clustering algorithm. And generating a data set by using all the data for an algorithm.
For example, assume a service set having 60 mobile communication services, wherein the service attribute types include call time, call unit price, and traffic volume. Wherein, the value of the call time includes: 100 minutes, 200 minutes, 500 minutes; the values of the call unit price include: 0.1 yuan/min, 0.15 yuan/min, 0.2 yuan/min; the values of the data traffic include: 1GB, 5GB and 10 GB. In addition to the service attributes described above, the service attributes may also include attribute features of any service, including, for example: service area, service level, etc. The service attributes and values used in this example do not constitute any limitation on the attributes of the services described in the scheme.
Based on the service attributes and the values of the service attributes, the number of categories in the service set is as follows:
after the class number is determined, each service is assigned, according to the service of the service set in the above example, each service element is assigned to be an N-dimensional vector, and the service attributes in the example are divided into three classes, so that N is 3 here. Assuming a value of 1 for a 100 minute talk time,the call unit price of 0.1 yuan/min is 1, the traffic assignment of 5GB is 2, and a service element c containing 100 minutes of call time, 0.1 yuan/min of call unit price and 5GB data traffic1After assignment c1＝(1,1,2)。
The following describes a specific process of the algorithm:
1. randomly selecting K services from a service set as an initial centroid using a random algorithm
2. Traversing the distance between each data in the existing data set and the nearest centroid, and classifying, wherein the algorithm formula is as follows:
wherein the initial center of mass
Business element c in a business setj＝(c1、c2、c3…cn)。
cjIs a k-dimensional vector, the value of k is equal to the number of the service attributes.
3. And recalculating the centroid, and taking the arithmetic mean value of each dimensionality of the data in the service cluster as a new centroid:
4. and (4) clustering the service data set according to the latest centroid by using the algorithm again, and repeating the steps 2 and 3 until the centroid is not changed any more.
And 103, managing the service according to the classification result.
And after the final centroid is obtained by the algorithm, outputting the classification result. And the data information of each type of service is visually displayed, so that a user can conveniently manage the service according to the classification result. Such as pricing the services in the same category, querying specific attribute data of the services, adding new services or deleting existing services, and the like.
Compared with the prior art, the method and the system have the advantages that the existing service attribute characteristics are manually analyzed, then all services needing to be managed are intelligently classified by using the clustering algorithm, so that the cost of service input information is reduced, the manual intervention degree is reduced, the manual classification of the services by using the service characteristics is reduced, the efficiency of service management is improved, and the management cost is greatly reduced.
A second embodiment of the present invention relates to an intelligent service management method, and a specific flow is shown in fig. 2, including:
Specifically, after traversing all the services to be classified in the service set, all the service attributes of the existing services are extracted, and the values of the service attributes under one class of service attributes are displayed to the user in a selectable list form. When a new service needs to be added into the service set, the user firstly compares the characteristics of the new service with the service attributes listed in the service template and the values of the service attributes, and when the service template can meet the new service, the user selects the proper service attribute values in the service template to form the new service and adds the new service into the service set. If the current service template can not satisfy the new service, that is, the new service has the service attribute or the value of the service attribute which does not exist in the service template, at this time, the extra service attribute or the value of the service attribute which the new service has is added into the service template, and the service template is modified to adapt to the new service.
And step 203, classifying the service to be classified by using a clustering algorithm. This step is similar to step 102 in the first embodiment, and is not described herein again.
Specifically, when the services in the service set change, for example, the services are added or deleted, or the service attribute characteristics change, the services in the service set need to be classified by a primary clustering algorithm according to the new K value and the new service attribute characteristics.
In a specific application, it is first determined whether a change in a service set is an addition of a new service or a removal of an existing service. And then judging whether the change affects the service attribute characteristics existing in the existing service template, if so, recalculating the current category number, and finally classifying the services in the changed service set by using the clustering algorithm again. Meanwhile, the service template needs to be modified correspondingly.
And step 205, performing hierarchical management on the services according to the classification result.
Specifically, after the services are classified by a clustering algorithm, a set formed by the classified services is defined as a service cluster, and a label is added to the service cluster according to the attribute characteristics of the services in the service cluster. For example, the label content of the service cluster A is 0.15 yuan/min-5 GB-500 min. Those skilled in the art will appreciate that the content in the tag corresponds to the value of the service attribute in the service template. Therefore, when the user needs to manage the classified services, when a service class which is expected to be managed is selected through the service template, the values of the service attributes of the service class are selected from the service template, after the system obtains the values selected by the user, the service clusters of all the labels containing the values of the service attributes input by the user are read, and the analysis results are displayed to the user for the user to manage the services.
Meanwhile, in specific application, a user can set the priority level of each service attribute before classification, after the service is classified by using a clustering algorithm, the system sets the priority level according to the user, displays the classification result in a tree diagram or other hierarchical diagram mode layer by layer according to the priority level set by the user and all service clusters according to label contents of the service clusters, and is convenient for the user to manage the service.
In a specific example, assuming that the priority is the call unit price > data traffic > call time, the classification result can be shown as follows:
when the priority of the service attribute changes, the order of the service attributes 1, 2 and 3 in the table is rearranged according to the priority.
Compared with the prior art, the method and the system have the advantages that when the service to be managed changes, the changed service set is reclassified in real time, the purpose of dynamically analyzing new service data is achieved, secondary development on the system is not needed when the service is updated, and the development and maintenance cost of the system in the later period is reduced. Meanwhile, when the classification result is output, the classification result can be displayed to the user in a hierarchical manner according to the priority of the service attribute preset by the user, so that the efficiency of the user in the process of service management and analysis is improved.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
A third embodiment of the present invention relates to an intelligent service management apparatus, as shown in fig. 3, including:
an obtaining module 301, configured to obtain a service set including services to be classified.
Specifically, after the service management system is initialized, the obtaining module 301 reads a service set to be managed from a database storing services into a memory structure for other modules to use at any time. Meanwhile, when the service in the service set is changed, the existing service in the memory structure is modified by corresponding addition, deletion and the like.
In an embodiment, the obtaining module 301 may further be configured to obtain a service tag added by the user for the classified service cluster, and establish a link with the classified service cluster.
In one embodiment, the obtaining module 301 may further be configured to obtain priorities set by the user for various service attributes, and provide the priorities to the outputting module 304.
An analysis module 302, configured to analyze the service attribute and the value of the service attribute, and calculate the number of categories at the same time;
specifically, the module analyzes the existing services in the service set, the service attributes of the existing services, and the values of the service attributes, and calculates the number of classes of the existing services.
In an embodiment, after the analysis module 302 completes the analysis, a service template is generated, and the service template is used for displaying the values of the service attributes under a class of service attributes to the user in a selectable list form.
In one embodiment, the analysis module 302 may be further configured to re-analyze the service attribute characteristics and re-calculate the number of classes of the changed service when the existing service is changed.
And the algorithm module 303 is used for classifying the service to be classified by using a clustering algorithm according to the category number calculated by the analysis module 302.
Specifically, algorithm module 303 runs a clustering algorithm capable of classifying traffic, including but not limited to a K-means clustering algorithm. After the analysis module 302 completes analysis of the service and calculates the number of classes of the existing service in the memory structure, the service is classified. And provides the classification results to the output module 304.
And the output module 304 is used for visually outputting the classification result of the algorithm module 303.
Specifically, the output module 304 is configured to display the classification result to the user in an intuitive manner such as a table, so that the user can perform specific management operation on the service.
In one embodiment, the output module 304 may further display the service clusters containing the service attribute features input by the user in the tag to the user in a list form in a visual manner according to the service attribute features input by the user.
In an embodiment, the output module 304 may further output each service cluster hierarchically according to the priority of the service attribute preset by the user and display the service cluster to the user.
It should be understood that this embodiment is a system example corresponding to the first and second embodiments, and may be implemented in cooperation with the first and second embodiments. The related technical details mentioned in the first embodiment are still valid in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related-art details mentioned in the present embodiment can also be applied to the first embodiment as well as the second embodiment.
It should be noted that each module referred to in this embodiment is a logical module, and in practical applications, one logical unit may be one physical unit, may be a part of one physical unit, and may be implemented by a combination of multiple physical units. In addition, in order to highlight the innovative part of the present invention, elements that are not so closely related to solving the technical problems proposed by the present invention are not introduced in the present embodiment, but this does not indicate that other elements are not present in the present embodiment.
A fourth embodiment of the invention is directed to a terminal, as shown in fig. 4, comprising at least one processor 401; and a memory 402 communicatively coupled to the at least one processor; the memory 402 stores instructions executable by the at least one processor 401, and the instructions are executed by the at least one processor 401 to enable the at least one processor 401 to perform an intelligent traffic management method as described above.
Where the memory and processor are connected by a bus, the bus may comprise any number of interconnected buses and bridges, the buses connecting together one or more of the various circuits of the processor and the memory. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor is transmitted over a wireless medium via an antenna, which further receives the data and transmits the data to the processor. The processor is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And the memory may be used to store data used by the processor in performing operations.
A fifth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (10)
1. An intelligent service management method, comprising:
acquiring a service set containing services to be classified;
extracting all service attributes of the service to be classified and all possible values of the service attributes;
calculating the product of the number of all possible values of all the service attributes, and taking the product as the category number of the service to be classified;
classifying the services to be classified by utilizing a clustering algorithm according to the category number to obtain a classification result;
and managing the service set according to the classification result.
2. The method for service management according to claim 1, wherein the managing the service set according to the classification result specifically includes:
when the service to be classified is changed, judging whether the service attribute of the changed service to be classified or the value of the service attribute is changed;
when the judgment result is yes, regenerating the number of the classes of the service to be classified;
and classifying the services to be classified by utilizing the clustering algorithm according to the regenerated category number of the services to be classified.
3. The intelligent service management method according to claim 1 or 2, wherein after extracting all the service attributes of the service to be classified and all possible values of the service attributes, the method comprises:
generating a service template according to the service attribute of the service to be classified and all possible values of the service attribute; the service template is used for recording all combinations of all possible values of the existing service attributes, and comparing the combinations with the service attributes and the values of the service attributes of the new service when the service is changed.
4. The traffic management method according to claim 3,
when the service to be classified is changed into the new service, judging whether the service attribute of the new service and the value of the service attribute are matched with the service template;
if the service attribute of the new service or the value of the service attribute is not matched with the service template, adding the new service attribute or the value of the service attribute in the service template;
and generating a new service template.
5. The intelligent traffic management method according to claim 1, wherein the managing the traffic set according to the classification result specifically includes:
defining a set of the same type of service as a service cluster; the service cluster is provided with an attribute label, and the content of the attribute label is all values of all service attributes of the services in the service cluster;
and outputting the classification result by taking the service cluster as a unit.
6. The intelligent traffic management method according to claim 4, wherein after the classifying result is output in units of the traffic clusters, the method comprises:
obtaining the value of the service attribute to be managed; and acquiring the service cluster containing the value of the service attribute to be managed in the attribute label according to the classification result, and managing the acquired service cluster.
7. The intelligent service management method according to claim 4, wherein the outputting the classification result with the service cluster as a unit specifically comprises:
presetting the priority of the service attribute;
and outputting the classification result in a layering way according to the priority of the service attribute.
8. An intelligent traffic management device, comprising:
the acquisition module is used for acquiring the service set containing the service to be classified;
the analysis module is used for analyzing the service attribute and the value of the service attribute and calculating the category number;
the algorithm module is used for classifying the service to be classified by utilizing a clustering algorithm according to the category number calculated by the analysis module;
and the output module is used for outputting the classification result of the algorithm module in a visual mode.
9. A terminal, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a traffic management method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, storing a computer program, wherein the computer program, when executed by a processor, implements a traffic management method according to any of claims 1 to 7.
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| CN201910843503.8A CN110766591A (en) | 2019-09-06 | 2019-09-06 | Intelligent service management method, device, terminal and storage medium |
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| CN201910843503.8A CN110766591A (en) | 2019-09-06 | 2019-09-06 | Intelligent service management method, device, terminal and storage medium |
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| CN113159487A (en) * | 2021-01-21 | 2021-07-23 | 全球能源互联网研究院有限公司 | Power data management method and device, electronic equipment and storage medium |
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