CN114611850A - Service analysis method and device and electronic equipment - Google Patents
Service analysis method and device and electronic equipment Download PDFInfo
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Abstract
The application discloses a business analysis method, a business analysis device and electronic equipment, which are used for at least solving the problems of low business analysis efficiency and inaccurate analysis result in the related technology. The method comprises the following steps: acquiring target analysis demand characteristics of a service analysis task to be processed; determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library; performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task; and generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for service analysis, and an electronic device.
Background
With the continuous development of mobile communication Technology, under the conditions of large concentration of an IT (Information Technology) system and continuous and complete capability of a large data platform, how to continuously and orderly analyze, supervise and guide the development of the whole network service, and meet the requirements of users on service diversity and high reliability is called a problem to be solved by operators.
In the related art, when performing business analysis, it is generally necessary for business analysts to manually extract required index data from a basic data system in which a large amount of index data is stored, in order to perform business analysis. However, the manual extraction method affects the efficiency of business analysis, and different business analysts have different understandings of business analysis requirements, so that the aperture of the extracted index data is different, and the accuracy of the business analysis result is affected.
Disclosure of Invention
The embodiment of the application provides a business analysis method, a business analysis device and electronic equipment, and aims to at least solve the problems of low business analysis efficiency and inaccurate analysis result in the related technology.
In order to solve the technical problem, the embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a service analysis method, including:
acquiring target analysis demand characteristics of a service analysis task to be processed;
determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
Optionally, determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis requirement characteristic and a business analysis requirement characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library, where the method includes:
determining similarity between the target analysis requirement characteristics and business analysis requirement characteristics corresponding to the historical analysis reports in the historical analysis report library;
based on the similarity, selecting a historical analysis report matched with the business analysis task from the historical analysis report library;
and determining a target analysis template matched with the business analysis task based on the analysis template corresponding to the matched historical analysis report.
Optionally, performing cluster analysis on the index set used by the matched historical analysis report based on a preset corresponding relationship between a set clustering algorithm, the target analysis demand characteristic, and the service characteristics of different services and the index set, so as to obtain a target index set matched with the service analysis task, including:
clustering the index sets used by the matched historical analysis reports based on a set clustering algorithm and a preset corresponding relation between the service characteristics of different services and the index sets to obtain a plurality of index set clusters and service characteristics corresponding to the index set clusters;
selecting a target index cluster matched with the service analysis task from the index clusters based on the service characteristic corresponding to each index cluster and the target analysis demand characteristic;
and determining a target index set matched with the business analysis task based on the target index set cluster.
Optionally, determining a target index set matched with the business analysis task based on the target index set cluster includes:
for each index set in the target index set cluster, selecting indexes matched with the service analysis tasks from the index sets based on the service value scores of the services corresponding to the index sets and the index value scores of the indexes in the index sets;
and generating a target index set matched with the business analysis task based on the indexes selected from all the index sets in the target index set cluster.
Optionally, after generating a business analysis report of the business analysis task based on the target index set and the target analysis template, the method further includes:
determining the number of indexes of the service related to the target index set and the service related to the service analysis report reference based on the target index set and the preset corresponding relation;
updating the service value score of the related service based on the number of indexes of the related service quoted by the target index set, the number of indexes in the index set corresponding to the related service and the number of indexes in the target index set, wherein the service value score of the related service is determined based on the number of indexes of the index set corresponding to the related service quoted by each historical analysis report in the historical analysis report library, the total number of used indexes and the number of indexes in the index set corresponding to the related service, and/or,
and updating the index value score of each index in the index set corresponding to the related service based on the updated service value score of the related service, the number of the indexes in the index set corresponding to the related service and the total number of the indexes used by each historical analysis report in the historical analysis report library.
Optionally, after generating a business analysis report of the business analysis task based on the target index set and the target analysis template, the method further includes:
and updating the historical analysis report base based on the business analysis report and the target analysis demand characteristics.
Optionally, before generating a business analysis report of the business analysis task based on the target index set and the target analysis template, the method further includes:
judging whether the target index set is stored in a business analysis system for generating a business analysis report;
if the judgment result is negative, the indexes which are not stored in the business analysis system in the target index set are extracted from the corresponding business basic system and stored in the business analysis system.
In a second aspect, an embodiment of the present application provides a service analysis apparatus, including:
the requirement characteristic acquisition module is used for acquiring target analysis requirement characteristics of a service analysis task to be processed;
the first determining module is used for determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
the second determining module is used for performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and the report generation module is used for generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method according to the first aspect.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: determining historical analysis reports and target analysis templates matched with the business analysis tasks based on the target analysis demand characteristics of the business analysis tasks to be processed and the business analysis demand characteristics and analysis templates corresponding to the existing historical analysis reports, and providing analysis directions and ideas for business analysts; performing clustering analysis on an index set used by the matched historical analysis report by adopting a clustering algorithm according to the preset corresponding relation between the target analysis demand characteristics and the service characteristics of different services to obtain a target index set matched with a service analysis task; and finally, generating a business analysis report corresponding to the business analysis task based on the target index set and the target analysis template, so that the automatic processing of the business analysis task is realized, compared with a mode of manually adding index data in the related technology, the processing efficiency and accuracy of the business analysis task are improved, the daily work of data query, marketing tracking, customer insight and the like of business analysis personnel can be efficiently supported, the access pressure of a system support department is effectively relieved, and the business analysis cost and the labor cost are reduced.
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 of an application scenario related to a service analysis method provided in an embodiment of the present application;
fig. 2 is a flowchart of a service analysis method according to an embodiment of the present application;
fig. 3 is a flowchart of another service analysis method provided in the embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a service analysis apparatus according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
The service analysis method provided by one or more embodiments of the present application can be applied to the scenario shown in fig. 1. In fig. 1, the scenario includes a service analysis system 1, a plurality of service basic data systems 2, and a scheduling system 3. The different business basic data systems 2 store index data of different fields, for example, the different fields may include, but are not limited to, a marketing field, a product field, a service field, a customer field, a resource field, an accounting field, a network field, and the like, and in order to effectively distinguish and arrange the index data of the different fields, the different fields correspond to one business basic data system 2 for storing the index data of the field.
In the service processing process, the interaction process among the service analysis system 1, the service basic data system 2 and the scheduling system 3 is as follows: the dispatching system 3 extracts index data matched with the analysis requirements from one or more service basic data systems 2 to the service analysis system 1 according to the analysis requirements of the service analysis tasks, and the service analysis system 1 executes the service analysis tasks and outputs service analysis results based on the extracted index data.
Based on the above scenario, an embodiment of the present application provides a service analysis method, which may be applied to a service analysis system, for example, in a service analysis system 1 shown in fig. 1, please refer to fig. 2, and the method includes the following steps:
and S22, acquiring the target analysis requirement characteristics of the service analysis task to be processed.
The target analysis requirement characteristics refer to characteristics for describing analysis requirements of the business analysis tasks to be processed. The target analysis requirement characteristics may specifically include text information for describing a business analysis task to be processed. For example, if the service analysis task to be processed is to analyze magic hundred and value added services from both aspects of service development and service quality, then the target analysis requirement characteristics include: magic sum, value added service, service development and service quality.
In practical application, the target analysis demand characteristics can be obtained by identifying business analysis task information input by business analysts in a business analysis guide page.
And S24, determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis requirement characteristics and the business analysis requirement characteristics and the analysis template corresponding to the historical analysis report in the preset historical analysis report library.
The historical analysis report base stores a large number of generated historical analysis reports, each historical analysis report is generated by using a corresponding analysis template based on the corresponding business analysis requirement characteristics to carry out business analysis. In practical applications, the analysis templates in the embodiment of the present application may generally include, but are not limited to, the following types of templates according to different targeted business analysis tasks: a swivel analysis template, a comprehensive analysis template, a daily data analysis template, and the like.
In view of the business analysis tasks with similar analysis requirements, generally adopted indexes and analysis templates are similar, and further, obtained analysis reports are also similar, so that in an optional scheme, the historical analysis report and the target analysis template matched with the business analysis task to be processed can be determined based on the target analysis requirement characteristics of the business analysis task to be processed and the business requirement characteristics of each historical analysis report, so that the business analysis task to be processed can be processed by referring to the matched analysis report and analysis template, the idea and the direction for executing the business analysis task can be quickly obtained, and the corresponding business analysis report can be obtained.
Specifically, as shown in fig. 3, the step S24 may include:
and S241, determining the similarity between the target analysis demand characteristics and the business analysis demand characteristics corresponding to the historical analysis reports in the historical analysis report library.
Alternatively, the above-described similarity may be expressed in terms of cosine similarity, as shown in the following equation (1).
Wherein, sim (C, R)i) Representing the similarity between the target analysis demand characteristics and the business analysis demand characteristics corresponding to the ith historical analysis report; c represents target analysis demand characteristics; riAnd representing the service analysis demand characteristics corresponding to the ith historical analysis report.
Of course, it may be understood that the similarity between the target analysis requirement characteristic and the service analysis requirement characteristic corresponding to the historical analysis report may also be represented by a similarity in any other suitable form in the field, and this is not specifically limited in this embodiment of the present application.
And S242, selecting the historical analysis report matched with the business analysis task from the historical analysis report library based on the similarity between the target analysis requirement characteristic and the business analysis requirement characteristic corresponding to each historical analysis report.
Optionally, the historical analysis reports in the historical analysis report library may be sorted according to the corresponding similarity, and the historical analysis report matched with the service analysis task is selected according to the sorting result. For example, the first preset number of historical analysis reports with the highest similarity may be determined as the historical analysis reports matching the business analysis tasks. The first preset number may be set in a user-defined manner according to actual analysis requirements, for example, the first preset number may be set to 10 or may also be set to 1, and the numerical value of the first preset number is not specifically limited in the embodiment of the present application.
Optionally, the historical analysis report with the similarity exceeding the first preset similarity threshold may also be determined as the historical analysis report matched with the business analysis task. The first preset similarity threshold may be set in a user-defined manner according to actual analysis requirements, for example, the first preset similarity threshold may be 80%, and the numerical value of the first preset similarity threshold is not specifically limited in the embodiment of the present application.
And S243, determining a target analysis template matched with the business analysis task based on the analysis template corresponding to the historical analysis report matched with the business analysis task.
Optionally, in a case that the number of the historical analysis reports matched with the business analysis task is 1, determining an analysis template corresponding to the historical analysis report as a target analysis template; when the number of the historical analysis reports matched with the business analysis tasks is multiple, the multiple matched historical analysis reports can be displayed to business analysts, the business analysts select the historical analysis reports, and further the analysis templates corresponding to the historical analysis reports selected by the business analysts are determined as target analysis templates.
And S26, performing cluster analysis on the index set used by the matched historical analysis report based on the preset corresponding relation among the set clustering algorithm, the target analysis demand characteristics and the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task to be processed.
In the embodiment of the present application, the service characteristics of the service are used to reflect the characteristics of the service, and specifically, the service characteristics may include, but are not limited to, text information (such as keywords) used to describe the characteristics of the service. The index set corresponding to the service characteristics of the service is obtained by analyzing the service characteristics of the service and can be used for reflecting at least one index of the service characteristics of the service. For each service, the service can be analyzed through the index set corresponding to the service characteristic of the service. For example, for a personal business, the set of metrics corresponding to the business characteristics of the business may include, for example, but not limited to, one or more of the following: user age, user age distribution information, user net age distribution information, user package usage, and user package usage distribution information.
Further, considering that services of the same type have a certain common point, for example, all belong to individual services, when services of the same type are analyzed, the adopted index sets are relatively similar, and therefore, the correspondence between the service features of different services and the index sets may be the correspondence between services of different types and the index sets. The preset corresponding relation between the service characteristics of different types of services and the index set can be obtained by classifying and sorting the services of various types in the whole network based on the service characteristics.
Specifically, the network-wide services may be classified and sorted based on their service features to obtain various types of services, i.e., B ═ B1,B2,...,BmIn which BiThe method comprises the steps of representing the ith type of service, representing the number of service types by m, wherein each type of service comprises attribute information such as service codes, service names, service characteristics, service analysis value scores, subclass service codes and the like, wherein the attribute information of the ith type of service is marked as Bi＝{b1,b2,...,bnAnd n represents the number of attributes contained in the attribute information. Then, for each type of service, the development of the whole network service can be analyzed by the type of service according to the service characteristics of each service contained in the type of service, and an index set corresponding to the type of service is extracted. Wherein, the firstThe index set corresponding to the i-type service is recorded as Bi＝{Ii1,Ii2,...,IioAnd f, o represents the number of index sets corresponding to the ith service. In practical applications, the index set of each service may be derived from different fields, specifically including but not limited to a marketing domain, a product domain, a service domain, a customer domain, a resource domain, an accounting domain, a network domain, and the like. Further, attribute information of each type of service and a corresponding index set are merged and recorded as:
then B isiIj＝(bi,...,bn,Iij1,Iij2,...,Iijp) Thus, the preset corresponding relation between the service characteristics of different types of services and the index set is obtained.
It should be noted that, in practical applications, the preset corresponding relationship between the different services and the index set may be stored in the service analysis system in advance, so that the service analysis system may directly read the preset corresponding relationship from the local to process the service analysis task to be processed.
In addition, the scheduling system can periodically inquire whether a new service and an index set corresponding to the new service or a new index set corresponding to an existing service exist in each service basic data system, if so, the scheduling system extracts the new service and the index set corresponding to the new service or the new index set corresponding to the existing service from each service basic data system to the service analysis system so as to update the preset corresponding relation, and accurate data support is provided for the execution of subsequent service analysis tasks.
The service analysis requirement characteristics corresponding to the historical analysis reports matched with the service analysis tasks are similar to the target analysis requirement characteristics, so that the index sets used by the matched historical analysis reports have a certain reference value for the service analysis tasks to be processed, the index sets used by the historical analysis reports with similar service characteristics can be clustered according to the service characteristics, the index sets used by the corresponding historical analysis reports with similar service characteristics are gathered together, and then the index sets meeting the analysis requirements of the service analysis tasks to be processed, namely the target index sets matched with the service analysis tasks, are determined according to the clustering results and the target analysis requirement characteristics.
It should be noted that the clustering algorithm in the embodiment of the present application may be any suitable clustering algorithm, and specifically, may include, but is not limited to, one or a combination of the following algorithms: hierarchical Clustering algorithm (Hierarchical Clustering), K-means Clustering (K-means Clustering), SOM Clustering algorithm, and FCM Clustering algorithm. Preferably, the clustering algorithm may adopt a hierarchical clustering algorithm.
And S28, generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
Specifically, the corresponding business analysis task can be executed based on the target index set to obtain a business analysis result, and a business analysis report of the business analysis task is further generated based on the business analysis result and the target analysis template for reference and analysis of business analysts.
The business analysis report may include a business analysis result of the business analysis task, or may further include risk early warning, optimization suggestions and the like for related businesses, so as to provide data basis and guidance suggestions for quality and fusion development of related businesses.
By the business analysis method provided by the embodiment of the application, the historical analysis report and the target analysis template matched with the business analysis task are determined based on the target analysis requirement characteristics of the business analysis task to be processed and the business analysis requirement characteristics and the analysis templates corresponding to the existing historical analysis reports, so that the analysis direction and the thinking can be provided for business analysts; performing clustering analysis on an index set used by the matched historical analysis report by adopting a clustering algorithm according to the preset corresponding relation between the target analysis demand characteristics and the service characteristics of different services to obtain a target index set matched with a service analysis task; and finally, generating a business analysis report corresponding to the business analysis task based on the target index set and the target analysis template, so that the automatic processing of the business analysis task is realized, compared with a mode of manually adding index data in the related technology, the processing efficiency and accuracy of the business analysis task are improved, the daily work of data query, marketing tracking, customer insight and the like of business analysis personnel can be efficiently supported, the access pressure of a system support department is effectively relieved, and the business analysis cost and the labor cost are reduced.
In order to make those skilled in the art understand the service analysis method provided in the embodiment of the present application, the following describes each step of the service analysis method provided in the embodiment of the present application in detail.
With respect to the step S26, in an alternative scheme, as shown in fig. 3, the step S26 may include:
and S261, clustering the index sets used by the matched historical analysis reports based on a set clustering algorithm and a preset corresponding relation between the service characteristics of different services and the index sets to obtain a plurality of index set clusters and service characteristics corresponding to the index set clusters.
Each index set cluster can contain one or more index sets, and the service characteristics corresponding to the index sets in the same index set cluster are similar.
And S262, selecting a target index cluster matched with the service analysis task from the index clusters based on the service characteristic and the target analysis demand characteristic corresponding to each index cluster.
More specifically, the similarity between the service feature corresponding to each index cluster and the target analysis requirement feature may be calculated for each index cluster, and then, the target index cluster matched with the service analysis task may be selected from all the index clusters according to the similarity corresponding to each index cluster. It should be noted that, the similarity between the service features corresponding to the index cluster and the target analysis requirement features may be calculated in step S241, and the similarity between the target analysis requirement features and the service analysis requirement features corresponding to the historical analysis report is similar, and is not described herein again.
When the target index cluster is selected from all the index cluster clusters, optionally, all the index cluster clusters may be sorted according to the corresponding similarity, and the target index cluster matched with the service analysis task is selected from the sorted result. For example, the index set cluster with the highest similarity and the second preset number may be determined as the target index set cluster matched with the business analysis task. The preset number can be set in a user-defined manner according to actual analysis requirements, for example, the second preset number can be set to be 1, and the numerical value of the second preset number is not specifically limited in the embodiment of the application.
Optionally, the historical analysis report with the similarity exceeding the second preset similarity threshold may also be determined as the historical analysis report matched with the business analysis task. The second preset similarity threshold may be set in a user-defined manner according to actual analysis requirements, for example, the second preset similarity threshold may be 80%, and the numerical value of the second preset similarity threshold is not specifically limited in the embodiment of the present application.
And S263, determining a target index set matched with the business analysis task based on the target index set cluster.
Alternatively, the index set included in the target index set cluster may be determined as a target index set matching the business analysis task.
Optionally, the index set in the target index set cluster may also be output and displayed to a business analyst, the business analyst selects the index set, and the index set selected by the business analyst is determined as the target index set matched with the business analysis task.
In a more preferable scheme, a target index set matched with the service analysis task can be determined by combining the service value scores of the services corresponding to the index sets in the target index set cluster and the index value scores of each index in the index sets. Specifically, for each index set in the target index set cluster, an index matched with the business analysis task is selected from the index set based on the business value score of the business corresponding to the index set and the index value score of each index in the index set, and then a target index set matched with the business analysis task is generated based on the index selected from each index set in the target index set cluster.
More specifically, for each index in the index set, a weighted sum may be performed according to the service value score corresponding to the index set and the index value score of the index, so as to obtain a composite score of the index, and then a third preset number of indexes before the composite score or indexes with composite scores exceeding a preset score are selected from the index set. Further, the indexes selected from each index set in the target index set cluster may be combined to obtain the target index set.
The third preset number and the preset score can be set according to actual needs in a user-defined manner, for example, the third preset number can be set to be 50.
The service value score of the service is used for reflecting the condition that the index set corresponding to the service is quoted by the existing historical analysis report, and if the service value score of the service is higher, the index set corresponding to the service is frequently quoted by the existing historical analysis report, so that the service value of the index set corresponding to the service is higher. Specifically, the service value score of the service may be determined based on the number of indexes in the historical analysis report library, which are used by each historical analysis report to refer to the service, the total number of indexes used by each historical analysis report, and the number of indexes in the index set corresponding to the service. More specifically, the service value score of a service can be determined by the following formula (2).
Wherein, bivA service value score representing the ith service; n represents the number of historical analysis reports stored in the historical analysis report library; p is a radical ofjIndicating the number of indexes in an index set corresponding to the ith service quoted by the jth historical analysis report; q. q.sjThe total number of indexes used by the jth historical analysis report is represented; piAnd indicating the number of indexes in the index set corresponding to the ith service.
The index value score of each index in the index set is used for reflecting the condition that each index is quoted by the existing historical analysis report, if the index value score of each index is higher, the index is frequently quoted by the existing historical analysis report, and therefore the use value of the index is higher. Specifically, the index value score of each index in the index set may be determined based on the service value score of the service corresponding to the index set, the number of indexes in the historical analysis report library, which refer to the service, of each historical analysis report, and the number of indexes in the index set. More specifically, the index value score of each index in the index set can be determined by the following formula (3).
Wherein, IimvIndex value scores of the mth index in the index set corresponding to the ith service are represented; i isimE j denotes that the jth historical analysis report references the mth index.
It can be appreciated that, with the above-described scheme, since the historical analysis report matched with the business analysis task has similar analysis requirements with the business analysis task, therefore, the index set used by the matched historical analysis report has a certain reference value for the business analysis task, clustering the index set used by the matched historical analysis report according to the service characteristics corresponding to the index set, so that corresponding index sets with similar service characteristics are clustered together to obtain a plurality of index set cluster, then determining a target index set matched with the business analysis task according to the business characteristics corresponding to each index set cluster and the target analysis demand characteristics corresponding to the business analysis task, the selected target index set better meets the analysis requirements of the business analysis task, and the analysis result obtained by executing the business analysis task based on the index sets is more accurate.
In addition, in the above-mentioned more preferable scheme, the service value scores of the services corresponding to the index sets and the index value scores of the included indexes are integrated to determine the target index set matched with the service analysis task, because the service value scores of the services can reflect the condition that the index set corresponding to the services is referred by the existing historical analysis report, and the index value scores of the single indexes can reflect the condition that the single indexes is referred by the existing historical analysis report, the target index set obtained by integrating the service value scores and the index value scores can better meet the analysis requirements of the service analysis task, and the accuracy of the analysis results of the service analysis task is further improved.
Further, in order to provide more accurate data support for other subsequent business analysis tasks, in another embodiment of the present application, after step S28, the business analysis method may further include updating the business value score of the business related to the business analysis task and the index value score of each index in the index set corresponding to the business. Specifically, the number of the indexes of the service related to the target index set and the number of the indexes of the service quoted by the generated service analysis report can be determined based on the preset corresponding relation between the target index set and the service characteristics and the index set of the different services; further, updating the service value score of the service based on the number of indexes of the service quoted by the target index set, the number of indexes in the index set corresponding to the service and the number of indexes in the target index set; and updating the index value score of each index in the index set corresponding to the service based on the updated service value score of the service, the number of the indexes in the index set corresponding to the service and the total number of the indexes used by each historical analysis report in the historical analysis report library.
More specifically, the service value score of the service can be updated by the following formula (4).
Wherein, biv-newThe service value score after the ith service is updated is represented; p represents the number of indexes in an index set corresponding to the ith service, which are quoted by the generated service analysis report; and q represents the total number of indexes used by the generated service analysis report.
The index value score of each index in the index set corresponding to the service can be updated by the following formula (5).
Wherein, Iimv-newAnd the index value score after the mth index is updated in the index set corresponding to the ith service is represented.
It can be understood that after the service analysis report of the service analysis task is generated, the service value score of the service related to the service analysis report and the index value score of each index in the corresponding index set are updated, so that an analysis closed loop is formed, and more accurate data support is provided for other subsequent service analysis tasks.
Further, in order to provide more accurate data support for other subsequent business analysis tasks, in another embodiment of the present application, after step S28, the business analysis method may further include: and updating a historical analysis report base based on the generated business analysis report and the target analysis demand characteristics. Thereby, the business analysis report can be used for providing reference for other business analysis tasks with the same analysis requirement.
Further, in the process of performing business analysis, index data required by the business analysis is usually stored in different business basic data systems in a scattered manner, and each time a business analysis task, especially a new business analysis task, is performed, corresponding index data needs to be searched and extracted from the corresponding business basic data system, which takes a certain time, thereby affecting the execution efficiency of the whole business analysis task. In view of this, in another embodiment of the present application, before the step S28, the traffic analysis method may further include: judging whether a target index set is stored in the business analysis system; if the judgment result is negative, the indexes which are not stored in the business analysis system in the target index set are extracted from the corresponding business index system and stored in the business analysis system, so that the business analysis system can directly read the target index set from the local to execute the business analysis task without waiting for searching and calling from each business basic data system, the processing time of the business analysis task is shortened, and the processing efficiency of the business analysis task is improved.
It should be noted that, in implementation, the above process may be performed by triggering a scheduling system (e.g., the scheduling system 3 shown in fig. 1).
Secondly, in order to ensure the processing efficiency of the service analysis task, the scheduling system can check whether the index set corresponding to each service is stored in the service system at regular time, and if the judgment result is negative, the indexes which are not stored in the service system in the index set corresponding to each service are extracted from the corresponding service basic data system and stored in the service analysis system. In addition, the scheduling system can be configured to provide asynchronous execution capacity with each service basic data system so as to meet the scheduling and running capacity of data with large quantity and ultra-long execution time.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 4, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the service analysis device on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring target analysis demand characteristics of a service analysis task to be processed;
determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
The method executed by the service analysis device according to the embodiment shown in fig. 2 of the present application may be applied to a processor, or may be implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may also execute the method in fig. 2 and implement the functions of the service analysis apparatus in the embodiments shown in fig. 2 and fig. 3, which are not described herein again in this embodiment of the present application.
Of course, besides the software implementation, the electronic device of the present application does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or a logic device.
Embodiments of the present application also provide a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by a portable electronic device including a plurality of application programs, enable the portable electronic device to perform the method of the embodiment shown in fig. 2, and are specifically configured to:
acquiring target analysis demand characteristics of a service analysis task to be processed;
determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
Fig. 5 is a schematic structural diagram of a service analysis device according to an embodiment of the present application. Referring to fig. 5, in a software implementation, the service analysis apparatus 500 may include:
a requirement characteristic obtaining module 510, configured to obtain a target analysis requirement characteristic of a service analysis task to be processed;
a first determining module 520, configured to determine a historical analysis report and a target analysis template that are matched with the business analysis task based on the target analysis requirement feature and a business analysis requirement feature and an analysis template that correspond to a historical analysis report in a preset historical analysis report library;
a second determining module 530, configured to perform cluster analysis on the index set used by the matched historical analysis report based on a preset corresponding relationship between a set clustering algorithm, the target analysis demand characteristics, and the service characteristics of different services and the index set, so as to obtain a target index set matched with the service analysis task;
a report generating module 540, configured to generate a business analysis report of the business analysis task based on the target index set and the target analysis template.
Optionally, the first determining module is specifically configured to:
determining similarity between the target analysis demand characteristics and business analysis demand characteristics corresponding to each historical analysis report in the historical analysis report library;
based on the similarity, selecting a historical analysis report matched with the business analysis task from the historical analysis report library;
and determining a target analysis template matched with the business analysis task based on the analysis template corresponding to the matched historical analysis report.
Optionally, the first determining module is specifically configured to:
clustering the index sets used by the matched historical analysis reports based on a set clustering algorithm and a preset corresponding relation between the service characteristics of different services and the index sets to obtain a plurality of index set clusters and service characteristics corresponding to the index set clusters;
selecting a target index cluster matched with the service analysis task from the index clusters based on the service characteristic corresponding to each index cluster and the target analysis demand characteristic;
and determining a target index set matched with the business analysis task based on the target index set cluster.
Optionally, the first determining module is specifically configured to:
for each index set in the target index set cluster, selecting indexes matched with the service analysis tasks from the index sets based on the service value scores of the services corresponding to the index sets and the index value scores of the indexes in the index sets;
and generating a target index set matched with the business analysis task based on the indexes selected from all the index sets in the target index set cluster.
Optionally, the apparatus further comprises a third determining module and a first updating module;
the report generating module is further configured to trigger the third determining module after generating a business analysis report of the business analysis task based on the target index set and the target analysis template;
the third determining module is configured to determine, based on the target index set and the preset corresponding relationship, a number of indexes of the service related to the target index set and a number of indexes of the service related to the service analysis report citation;
the first updating module is configured to update the service value score of the related service based on the number of indexes of the service referred to by the target index set, the number of indexes in the index set corresponding to the related service, and the number of indexes in the target index set, wherein the service value score of the related service is determined based on the number of indexes of the index set corresponding to the service referred to by each historical analysis report in the historical analysis report library, the total number of used indexes, and the number of indexes in the index set corresponding to the related service, and/or based on the updated service value score of the related service, the number of indexes in the index set corresponding to the related service, and the total number of indexes used by each historical analysis report in the historical analysis report library, for each index in the index set corresponding to the related service, and updating the index value score of the index.
Optionally, the apparatus further comprises a second update module;
the report generation module is further configured to trigger the second update module after generating a business analysis report of the business analysis task based on the target index set and the target analysis template;
and the second updating module is used for updating the historical analysis report base based on the business analysis report and the target analysis demand characteristics.
Optionally, the apparatus further comprises:
the judging module is used for judging whether the target index set is stored in a business analysis system for generating a business analysis report or not before the report generating module generates the business analysis report of the business analysis task;
and the extraction module is used for extracting the indexes which are not stored in the business analysis system in the target index set from the corresponding business basic system and storing the indexes into the business analysis system if the judgment result is negative.
In short, the above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
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. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Claims (10)
1. A method for analyzing traffic, comprising:
acquiring target analysis demand characteristics of a service analysis task to be processed;
determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
performing clustering analysis on the index set used by the matched historical analysis report based on a set clustering algorithm, the target analysis demand characteristics and a preset corresponding relationship between the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
2. The method of claim 1, wherein determining a historical analysis report and a target analysis template matching the business analysis task based on the target analysis requirement characteristics and a business analysis requirement characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library comprises:
determining similarity between the target analysis demand characteristics and business analysis demand characteristics corresponding to each historical analysis report in the historical analysis report library;
based on the similarity, selecting a historical analysis report matched with the business analysis task from the historical analysis report library;
and determining a target analysis template matched with the business analysis task based on the analysis template corresponding to the matched historical analysis report.
3. The method according to claim 1, wherein performing cluster analysis on the index set used by the matched historical analysis report based on a preset corresponding relationship between a set clustering algorithm, the target analysis requirement characteristics, and service characteristics of different services and index sets to obtain a target index set matched with the service analysis task comprises:
clustering the index sets used by the matched historical analysis reports based on a set clustering algorithm and a preset corresponding relation between the service characteristics of different services and the index sets to obtain a plurality of index set clusters and service characteristics corresponding to the index set clusters;
selecting a target index cluster matched with the service analysis task from the index clusters based on the service characteristic corresponding to each index cluster and the target analysis demand characteristic;
and determining a target index set matched with the business analysis task based on the target index set cluster.
4. The method of claim 3, wherein determining a set of target metrics that match the business analysis task based on the cluster of target metrics comprises:
for each index set in the target index set cluster, selecting indexes matched with the service analysis tasks from the index sets based on the service value scores of the services corresponding to the index sets and the index value scores of the indexes in the index sets;
and generating a target index set matched with the business analysis task based on the indexes selected from all the index sets in the target index set cluster.
5. The method of claim 4, wherein after generating a business analysis report for the business analysis task based on the set of target metrics and the target analysis template, the method further comprises:
determining the number of indexes of the service related to the target index set and the service related to the service analysis report reference based on the target index set and the preset corresponding relation;
updating the service value score of the related service based on the number of indexes of the related service quoted by the target index set, the number of indexes in the index set corresponding to the related service and the number of indexes in the target index set, wherein the service value score of the related service is determined based on the number of indexes of the index set corresponding to the related service quoted by each historical analysis report in the historical analysis report library, the total number of used indexes and the number of indexes in the index set corresponding to the related service, and/or,
and updating the index value score of each index in the index set corresponding to the related service based on the updated service value score of the related service, the number of the indexes in the index set corresponding to the related service and the total number of the indexes used by each historical analysis report in the historical analysis report library.
6. The method of claim 1, wherein after generating a business analysis report for the business analysis task based on the set of target metrics and the target analysis template, the method further comprises:
and updating the historical analysis report base based on the business analysis report and the target analysis demand characteristics.
7. The method of claim 1, wherein prior to generating a business analysis report for the business analysis task based on the set of target metrics and the target analysis template, the method further comprises:
judging whether the target index set is stored in a business analysis system for generating a business analysis report;
if the judgment result is negative, the indexes which are not stored in the business analysis system in the target index set are extracted from the corresponding business basic system and stored in the business analysis system.
8. A traffic analyzing apparatus, comprising:
the demand characteristic acquisition module is used for acquiring target analysis demand characteristics of a service analysis task to be processed;
the first determining module is used for determining a historical analysis report and a target analysis template matched with the business analysis task based on the target analysis demand characteristic and a business analysis demand characteristic and an analysis template corresponding to a historical analysis report in a preset historical analysis report library;
the second determining module is used for performing clustering analysis on the index set used by the matched historical analysis report based on a preset corresponding relation among a set clustering algorithm, the target analysis demand characteristics and the service characteristics and the index set of different services to obtain a target index set matched with the service analysis task;
and the report generation module is used for generating a business analysis report of the business analysis task based on the target index set and the target analysis template.
9. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 7.
10. A computer-readable storage medium in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method of any of claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116703140A (en) * | 2023-05-23 | 2023-09-05 | 汇链通产业供应链数字科技(厦门)有限公司 | Operation system and method based on AI and RPA |
| CN116737814A (en) * | 2023-06-14 | 2023-09-12 | 浙江天正思维信息技术有限公司 | Rapid integration method and system based on multi-source heterogeneous big data fusion |
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2020
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116703140A (en) * | 2023-05-23 | 2023-09-05 | 汇链通产业供应链数字科技(厦门)有限公司 | Operation system and method based on AI and RPA |
| CN116737814A (en) * | 2023-06-14 | 2023-09-12 | 浙江天正思维信息技术有限公司 | Rapid integration method and system based on multi-source heterogeneous big data fusion |
| CN116737814B (en) * | 2023-06-14 | 2023-12-19 | 浙江天正思维信息技术有限公司 | Rapid integration method and system based on multi-source heterogeneous big data fusion |
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