CN112632281A - Fusion delimitation method and device based on early warning complaint data - Google Patents
Fusion delimitation method and device based on early warning complaint data Download PDFInfo
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Abstract
The embodiment of the application discloses a fusion delimitation method and a fusion delimitation device based on early warning complaint data, wherein the method comprises the following steps: receiving an early warning indication signal; the early warning indication signal is related to the set early warning task; acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the delimitation set rule is obtained according to the early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to all delimitation items; acquiring current early warning complaint data related to the boundary set rule according to the boundary set rule; according to the delimitation rules corresponding to each delimitation item in the delimitation set rules, performing delimitation analysis on the current early warning complaint data respectively to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses. After the early warning is generated, the delimitation analysis is automatically executed according to a delimitation set rule configured by a user; after indexes in the delimitation set rule are changed, re-delimitation can be immediately carried out according to the modified delimitation set rule, and the real-time performance is high.
Description
Technical Field
The application relates to the technical field of data services, in particular to a fusion delimitation method and device based on early warning complaint data.
Background
In recent years, network quality expectations have continued to remain at a high level. With the rapid development of mobile network services, real-time monitoring of networks and complaint handling capability requirements face continuous challenges.
At present, the complaint early warning system can realize refined delimitation for the reason of early warning generation, including initial delimitation and comparison delimitation, wherein the initial delimitation is based on information such as an Optical Line Terminal (OLT), a notice, weak coverage and a Terminal, which are stored when a network throws a multi-point trigger intelligent preprocessing flow statement. After early warning is found, the stored data are taken out based on the early warning complaint work order, the responsibility body and the delimitation abnormal reason are automatically analyzed according to a predefined delimitation rule, and delimitation result data are displayed in a mode of a delimitation module in a modularized mode; the comparison delimitation is to compare the worksheets in the user-defined time period and the early warning complaint worksheets according to the worksheet screening conditions of the user-defined time period, the service types, the cities and the like according to a predefined delimitation rule, and to display comparison delimitation result data in a form of a delimitation module in a module division mode.
Although the complaint early warning system effectively makes up the defects that the traditional means can not find content side equipment, soft hanging and other hidden and non-full-resistance faults in time, and the early warning accuracy rate is up to 100 percent after the system is on line. However, the delimitation rule of the complaint early warning system is well defined in advance, and various delimitation items and indexes cannot be flexibly configured; and for the delimitation result data of the early warning complaint data of the complaint early warning system, as shown in fig. 1, the delimitation result data is only simply ranked, and can provide data support for early warning to a certain extent, but cannot provide a final delimitation conclusion of early warning. Therefore, how to quickly and intelligently delimit automatically provides data support for the early warning closed loop, improves the efficiency of discovering and solving network problems, and becomes a key point for subsequent breakthrough.
Disclosure of Invention
The embodiment of the application provides a fusion delimitation method and device based on early warning complaint data. The method is used for solving the two technical problems that various delimitation items and indexes in the delimitation rule of the existing complaint early warning system cannot be flexibly configured, delimitation result data of the complaint early warning system cannot be flexibly configured, and a final early warning delimitation conclusion cannot be provided. The technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a fusion delimitation method based on early warning complaint data, including:
receiving an early warning indication signal; the early warning indication signal is related to a set early warning task;
acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the early warning task configuration method comprises the following steps that a delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items;
acquiring current early warning complaint data related to the delimitation set rule according to the delimitation set rule;
carrying out delimitation analysis on the current early warning complaint data respectively according to delimitation rules corresponding to each delimitation item in the delimitation set rules to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
In one possible implementation, the warning indication signal is generated in case the number of current warning complaint data related to the warning task is larger than a preset threshold.
In one possible implementation, the delimiting rule corresponding to each delimiting item includes: the early warning amplification starting time delimitation rule, the current trend delimitation rule, the artificial intelligence AI recording keyword refining delimitation rule, the complaint phenomenon delimitation rule, the complaint area delimitation rule and/or the error code delimitation rule.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
carrying out delimitation analysis on the current early warning complaint data according to an early warning amplification starting time delimitation rule; the early warning amplification starting time delimitation rule refers to starting time that the current early warning complaint data related to the set early warning task in a certain time period is increased by more than a first threshold value compared with the current early warning complaint data related to the set early warning task in a previous time period, and early warning amplification starting time is output; or the starting time when the number of the current early warning complaint data related to the set early warning task in a certain time period is larger than the second threshold value, and outputting early warning amplification starting time.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
carrying out delimitation analysis on the current early warning complaint data according to a current trend delimitation rule; the current trend delimiting rule refers to the percentage of increase or decrease of current early warning complaint data related to the set early warning task in a certain time period compared with the percentage of increase or decrease of the current early warning complaint data related to the set early warning task in a previous time period, and the current trend is output; or the number of the current early warning complaint data related to the set early warning task in a certain time period is increased or reduced compared with the number of the current early warning complaint data related to the set early warning task in the previous time period, and the current trend is output.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
refining a delimitation rule according to artificial intelligence AI recording keywords, and carrying out delimitation analysis on the current early warning complaint data; the artificial intelligent AI recording keyword refining delimitation rule is that current early warning complaint data related to a set early warning task are converted into a standard and structured text which can be analyzed, the text is refined to obtain keywords of the current early warning complaint data, the keywords are classified, complaint percentage of each type of keywords in all the keywords is determined, and the keywords with the first complaint percentage are output.
In one possible implementation, the obtaining, according to the delimiting set rule, current early warning complaint data related to the delimiting set rule includes:
and acquiring the current early warning complaint data and the historical early warning complaint data related to the boundary set rule according to the boundary set rule.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
according to the complaint phenomenon delimitation rule, delimitation analysis is carried out on the current early warning complaint data; the complaint phenomenon delimiting rule refers to that the complaint duty ratio of current early warning complaint data respectively related to various complaint phenomena contained in a set early warning task in the current early warning complaint data related to the set early warning task is compared with historical early warning complaint data, the complaint duty ratio is synchronously increased to exceed a third threshold value, the increment of the complaint duty ratio exceeds a fourth threshold value, and the complaint duty ratio is larger than the historical early warning complaint data, and the first complaint phenomenon meeting the condition is output in any two days in three days in the same period.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
according to the complaint area delimitation rule, delimitation analysis is carried out on the current early warning complaint data; the complaint region delimitation rule refers to that complaint duty ratios of current early warning complaint data, related to the set early warning task, of various cities/counties in the current early warning complaint data, related to the set early warning task, synchronously rise to exceed a fifth threshold value and increase to exceed a sixth threshold value, and the complaint duty ratios are larger than any two days in three days in the same period of the historical early warning complaint data, and the first city/county meeting the conditions is output.
In a possible implementation, the performing, according to a delimiting rule corresponding to each delimiting item in a delimiting set rule, delimiting analysis on the current early warning complaint data includes:
carrying out delimitation analysis on the current early warning complaint data according to an error code delimitation rule; the error code delimitation rule refers to that the complaint percentage of the current early warning complaint data recorded with the error codes in the current early warning complaint data related to the set early warning task exceeds a seventh threshold, the obvious aggregation degree appears when the error codes are output, and otherwise, the obvious aggregation degree does not appear when the error codes are output.
In a possible implementation, the delimiting rules corresponding to the delimiting items in the delimiting set rule are used to perform delimiting analysis on the current early warning complaint data, and after a fusion delimiting conclusion is obtained, the method further includes:
and under the condition that the fusion delimitation conclusion does not accord with the preset standard, acquiring the modified delimitation set rule.
In one possible implementation, the error code delimiting rule is that the complaint percentage of the current early warning complaint data recorded with error codes in the current early warning complaint data related to the early warning task exceeds a seventh threshold, the output error codes have obvious aggregation, otherwise, the output error codes do not have obvious aggregation.
In a second aspect, an embodiment of the present application further provides a fusion delimiting device based on early warning complaint data, where the fusion delimiting device includes:
the receiving module is used for receiving the early warning indication signal; the early warning indication signal is related to a set early warning task;
the acquisition module is used for acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the early warning task configuration method comprises the following steps that a delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items;
the acquisition module is further used for acquiring the related current early warning complaint data according to the delimitation set rule;
the fusion delimitation module is used for performing delimitation analysis on the current early warning complaint data according to delimitation rules corresponding to all delimitation items in the delimitation set rules to obtain fusion delimitation conclusions; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
In a third aspect, an embodiment of the present application provides a fusion delimiting apparatus based on early warning complaint data, including at least one processor, where the processor is configured to execute a program stored in a memory, and when the program is executed, the apparatus is caused to perform the steps of the method in the first aspect and various possible implementations.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method in the first aspect and in various possible implementations.
According to the technical scheme, after the early warning is generated, the delimitation analysis is automatically executed according to the user-defined delimitation set rule, and the problem that a newly-built early warning task cannot carry out delimitation analysis but needs manual analysis to obtain a delimitation conclusion is effectively solved; after indexes in the delimitation set rule are changed, re-delimitation can be immediately carried out according to the modified delimitation set rule, and the real-time performance is high; compared with the existing complaint early warning system, the early warning system integrates the delimitation conclusion, can display the delimitation result of the current early warning more visually, has higher accuracy, and provides more powerful data support for the effective closed loop of the early warning.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is delimited result data obtained by using an existing complaint warning system according to an embodiment of the present disclosure;
FIG. 2 is a schematic process diagram of a fusion bound analysis performed by an improved complaint warning system according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of a fusion delimitation method based on early warning complaint data according to an embodiment of the present application;
fig. 4 is a schematic process diagram of performing delimitation analysis according to an AI recording keyword delimitation rule according to the embodiment of the present application;
FIG. 5 is a schematic diagram of a process of performing delimitation analysis according to a complaint phenomenon delimitation rule according to an embodiment of the present application;
fig. 6 is a schematic process diagram of performing delimitation analysis according to the complaint area delimitation rule according to the embodiment of the present application;
fig. 7 is a schematic process diagram of performing delimitation analysis according to an error code delimitation rule according to the embodiment of the present application;
FIG. 8 is a schematic diagram of a fusion bound conclusion provided by an embodiment of the present application;
fig. 9 is a schematic structural diagram of a fusion delimiting device based on early warning complaint data according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following describes in detail specific embodiments of the present application with reference to the accompanying drawings.
It should be noted that the term "and/or" in this application is only one kind of association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. The terms "first" and "second," and the like, in the description and in the claims of the embodiments of the present application are used for distinguishing between different objects and not for describing a particular order of the objects. For example, the first and second acquisition modules, etc. are used to distinguish different results, rather than to describe a particular order of the target objects. In the embodiments of the present application, words such as "exemplary," "for example," or "such as" are used to mean serving as examples, illustrations, or illustrations. Any embodiment or design described herein as "exemplary," "for example," or "such as" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion. In the description of the embodiments of the present application, the meaning of "a plurality" means two or more unless otherwise specified.
With the rapid development of mobile network services, the real-time monitoring and complaint handling capability requirements of the network face a serious challenge. In a possible implementation, the existing complaint early warning system effectively makes up the defect that the traditional means can not find content-side equipment, soft hanging and other hidden and non-full-resistance faults in time. After the system is on line, the early warning accuracy rate is up to 100%. However, the system has inflexible delimiting rules, the delimiting rules are well defined in advance, and various delimiting items and indexes cannot be flexibly configured. The delimitation result data of the early warning complaint data can provide data support for early warning, but the final delimitation conclusion of early warning cannot be provided, and the final delimitation conclusion can be obtained after manual analysis according to the initial delimitation result data and the comparative delimitation result data, so that time and labor are wasted. Therefore, the embodiment of the application provides an improved complaint early warning system, Artificial Intelligence (AI) and big data technology are deeply applied, delimiting capability of early warning complaints is comprehensively improved, custom configuration delimiting rules are realized, after early warning is generated, delimiting data based on the complaint early warning system is combined with recording AI delimiting and AI algorithms, fusion delimiting analysis is adopted, a fusion delimiting conclusion is obtained, and the closed loop effect of early warning is further improved.
FIG. 2 shows a process diagram for fused bounding analysis using an improved complaint warning system. As shown in fig. 2, after the pre-warning is generated, the system automatically obtains the corresponding bounding set rule configured according to the pre-warning task. And then, acquiring early warning complaint data according to the delimitation set rule, such as current early warning complaint data and historical early warning complaint data, and executing fusion delimitation analysis. And storing the fusion and delimitation conclusion into a corresponding database table, and presenting the fusion and delimitation conclusion in a foreground. And if the fusion delimitation conclusion does not meet the preset standard, manually modifying the delimitation set rule, and performing fusion re-delimitation by using the modified delimitation set rule.
In the embodiment of the present application, fig. 3 shows a flowchart of a fusion delimiting method based on early warning complaint data. The flow diagram includes S301-S304.
Before the early warning complaint data-based fusion delimitation method is implemented, corresponding delimitation set rules are configured in a user-defined mode according to the difference and the particularity of early warning tasks, and indexes and rules are configured in the user-defined mode for one or more delimitation items contained in the early warning tasks. In the embodiment of the application, each delimiting item in the delimiting set rule is early warning amplification starting time, current trend, AI recording keyword extraction, complaint phenomenon, complaint area and/or error code, and the like. The delimiting rule formulated for each delimiting item is: the early warning amplification starting time delimitation rule, the current trend delimitation rule, the artificial intelligence AI recording keyword refining delimitation rule, the complaint phenomenon delimitation rule, the complaint area delimitation rule and/or the error code delimitation rule.
In the embodiment of the present application, it is assumed that the early warning task is home broadband. In the case that the number of the current early warning complaint data related to the home broadband exceeds 100, an early warning is generated. S301, the improved complaint early warning system receives an early warning indication signal. It should be noted that the warning indication signal is related to the set warning task. For example, if the early warning task is set as a home broadband, the early warning indication signal received by the improved complaint early warning system is 1, the early warning task is set as a basic voice call, the early warning indication signal received by the improved complaint early warning system is 2, the early warning task is set as a value-added service, and the early warning indication signal received by the improved complaint early warning system is 3. S302, according to the received early warning indication signal, a delimitation set rule corresponding to a set early warning task (namely, a family broadband) is obtained, and the delimitation set rule comprises delimitation rules corresponding to all delimitation items. And S303, acquiring current early warning complaint data corresponding to the delimitation set rule, namely the current early warning complaint data related to the family broadband. S304, according to the delimitation rules corresponding to each delimitation item in the delimitation set rules, performing fusion delimitation analysis on the current early warning complaint data related to the family broadband, namely performing delimitation analysis on the current early warning complaint data related to the family broadband according to the early warning amplification starting time delimitation rules, the current trend delimitation rules, the AI recording keyword extraction delimitation rules, the complaint phenomenon delimitation rules, the complaint area delimitation rules and/or the error code delimitation rules, and finally obtaining a fusion delimitation conclusion which is a set of conclusions of various delimitation analyses.
In the embodiment of the application, the early warning amplification starting time delimiting rule refers to starting time when the current early warning complaint data related to the set early warning task in a certain time period is increased by more than a first threshold value than the current early warning complaint data related to the set early warning task in a previous time period, and early warning amplification starting time is output; or the starting time when the number of the current early warning complaint data related to the set early warning task in a certain time period is larger than the second threshold value, and outputting early warning amplification starting time. For example, for the home broadband early warning task, the early warning amplification start time delimiting rule refers to a start time at which the current early warning complaint data related to the home broadband in a certain time period is increased by more than 20% compared with the current early warning complaint data related to the home broadband in a previous time period, and outputs an early warning amplification start time or a start time at which the number of the current early warning complaint data related to the home broadband in a certain time period is greater than 30, and outputs the early warning amplification start time. And (3) carrying out delimitation analysis on the current early warning complaint data related to the family broadband according to an early warning amplification starting time delimitation rule, wherein the delimitation analysis refers to the analysis result of the early warning complaint data in the family broadband, for example, 2:00-3 in the afternoon of 12 months and 1 day in 2020: the number of current early warning complaint data related to family broadband appearing at 00 is 125, 12 months in 2020, 1 st pm 1: 00-2: 00 is 100, then it can be determined that 12 months and 1 st pm in 2020 is 2: 00-3: 00 present current early warning complaint data related to home broadband than 1: 00-2: the current early warning complaint data related to the family broadband appearing at 00 increases by 25% and exceeds 20%, so the early warning amplification starting time is 3:00 pm at 12 months and 1 day of 2020. By way of further example, 1 st pm 4: 00-5/12/2020: the number of current early warning complaint data related to home broadband appearing at 00 is 150, 3:00-4 in 1 pm on 12 months in 2020: 00 is 100, then it can be determined that 12 months and 1 st pm in 2020 is 4: 00-5: 00 present current early warning complaint data related to home broadband than 3: 00-4: the current early warning complaint data related to the family broadband appearing at 00 increases by 50 and more than 30, so the output early warning amplification starting time is 12 months at 2020 and 1 st afternoon at 5: 00.
In the embodiment of the application, the current trend delimiting rule refers to the percentage of increase or decrease of the current early warning complaint data related to the set early warning task in a certain time period compared with the current early warning complaint data related to the set early warning task in a previous time period, and the current trend is output; or the number of the current early warning complaint data related to the set early warning task in a certain time period is increased or reduced compared with the number of the current early warning complaint data related to the set early warning task in the previous time period, and the current trend is output. For example, for the home broadband early warning task, the current trend delimiting rule refers to a percentage of increase or decrease of current early warning complaint data related to the home broadband in a certain time period compared with the current early warning complaint data related to the home broadband in a previous time period, and outputs a current trend; or the number of the current early warning complaint data related to the family broadband in a certain time period is increased or reduced compared with the number of the current early warning complaint data related to the family broadband in the previous time period, and the current trend is output. And performing delimitation analysis on the current early warning complaint data related to the family broadband according to the current trend delimitation rule, wherein the current early warning complaint data refers to, for example, the early warning complaint data in the month of 12 and 1 in 2020 at 2:00-3 in the afternoon: the number of current early warning complaint data related to family broadband appearing at 00 is 200, 1 afternoon at 12 months in 2020 at 1 st 1: 00-2: 00 is 100, then it can be determined that 12 months and 1 st pm in 2020 is 2: 00-3: 00 present current early warning complaint data related to home broadband than 1: 00-2: 00 the current early warning complaint data related to the family broadband increases by 100%, the current trend is output to be rapidly increasing.
In the embodiment of the application, the artificial intelligent AI recording keyword refining delimitation rule is to convert the current early warning complaint data related to the set early warning task into a standard and structured text which can be analyzed, refine the text to obtain keywords of the current early warning complaint data, classify the keywords, determine the complaint percentage of each type of keywords in all the keywords, and output the keyword with the first complaint percentage. For example, for the early warning task of home broadband, the AI recording keyword delimiting rule is to convert the current early warning complaint data (audio file) related to the home broadband into an analyzable standardized and structured text, extract and obtain information such as keywords of the current early warning complaint data by using algorithms such as machine learning and AI big data processing technology, classify the keywords, determine the complaint percentage of each type of keywords in all the keywords, and output the keyword with the complaint percentage of TOP 1. According to the AI recording keyword delimiting rule, the current early warning complaint data related to the home broadband is subjected to delimiting analysis, for example, an audio file related to the home broadband is converted into a standardized and structured text which can be analyzed, and keywords related to the home broadband are extracted as "internet surfing incapable" and "network card", respectively, wherein the keywords "internet surfing incapable" is 70, the keywords "network card" is 30, the complaint ratio of the keywords "internet surfing incapable" related to the home broadband is 70/(70+30) — 70%, the complaint ratio of the output internet surfing incapable is 70%, and a specific flow is shown in fig. 4.
It should be noted that, in the embodiment of the present application, in addition to obtaining the current early warning complaint data related thereto according to the delimiting set rule, historical early warning complaint data related thereto may also be obtained.
In the embodiment of the application, the complaint phenomenon delimiting rule refers to that the complaint duty ratio of current early warning complaint data respectively related to various complaint phenomena contained in a set early warning task in the current early warning complaint data related to the set early warning task is synchronously increased over a third threshold value and is incrementally increased over a fourth threshold value, and the complaint duty ratio is greater than the complaint duty ratio of historical early warning complaint data for any two days in three days in the same period, and the first complaint phenomenon meeting the condition is output. For example, for the early warning task of the home broadband, the complaint phenomenon delimiting rule means that, when the complaint proportion of each current early warning complaint data respectively related to various complaint phenomena contained in the home broadband is more than 10PP compared with the historical early warning complaint data in the same period (average value in three days) and the increment is more than 5, and the complaint proportion is more than any two days in three days in the same period of the historical early warning complaint data, the TOP1 complaint phenomenon meeting the condition is output. And according to the complaint phenomenon delimitation rule, acquiring the service codes corresponding to the current early warning complaint data and the historical early warning complaint data related to the family broadband, performing service code distribution analysis, and performing delimitation analysis on the current early warning complaint data related to the family broadband. It should be noted that the first four digits of the current early warning complaint data correspond to different complaint phenomena, for example, 1101 represents internet access failure, 1102 represents a network card, and 1103 represents network slowness. For example, complaints about home broadband include "internet not available", "network card", and "network slow". As shown in table 1, if the current early warning complaint data corresponding to the complaint phenomenon "internet not available" is 70, the current early warning complaint data corresponding to the complaint phenomenon "network card" is 20, and the current early warning complaint data corresponding to the complaint phenomenon "network slow" is 10, it can be determined that the complaint percentage of the complaint phenomenon "internet not available" is 70%. The complaint rate of the complaint phenomenon "network card" is 20%. The complaint rate of the complaint phenomenon "network slow" is 10%. And the historical early warning complaint data corresponding to the complaint phenomenon that the network can not be accessed is 30 (45, 30 and 15 in three days), the historical early warning complaint data synchronous complaint percentage is 50% (75, 50 and 25 in three days), the historical early warning complaint data corresponding to the complaint phenomenon that the network card is 18, the historical early warning complaint data synchronous complaint percentage is 30%, the historical early warning complaint data corresponding to the complaint phenomenon that the network is slow is 12, and the historical early warning complaint data synchronous complaint percentage is 20%. According to the content, the complaint duty of the complaint phenomenon that the network can not be accessed is synchronously increased by 20PP and 40 compared with the historical early warning complaint data, the complaint duty of the complaint phenomenon that the network card is slow is reduced by 10PP and 2 compared with the historical early warning complaint data, and the complaint duty of the complaint phenomenon that the network is slow is reduced by 10PP and 2 compared with the historical early warning complaint data. Therefore, the output complaint phenomenon is concentrated on the condition that the network can not be accessed, the complaint accounts for 20PP (propene Polymer) which is increased by 40 compared with the historical early warning complaint data, and the specific flow is shown in figure 5.
TABLE 1
| Current early warning complaint data numbering | Service coding |
| 1 | 1101041501039900 |
| 2 | 1101143301256970 |
| … | … |
| 69 | 1101254615462156 |
| 70 | 1101254687566845 |
| 71 | 1102547854465825 |
| 72 | 1102021488796549 |
| … | … |
| 89 | 1102012546987845 |
| 90 | 1102564454489452 |
| 91 | 1103132456458896 |
| 92 | 1103245465565544 |
| … | … |
| 99 | 1103212122154544 |
| 100 | 1103445668587487 |
In the embodiment of the application, the complaint region definition rule refers to that complaint duty ratios of current early warning complaint data, related to the set early warning task, of various cities/counties in the current early warning complaint data related to the set early warning task synchronously rise to exceed a fifth threshold value and increase to exceed a sixth threshold value, and the complaint duty ratios are larger than the complaint ratios of the historical early warning complaint data in any two days in three days in the same period, and the first city/county meeting the conditions is output. For example, for the early warning task of home broadband, the complaint area delimiting rule means that the current early warning complaint data related to home broadband in each city/county rises by more than 10PP and increases by more than 5 in the same period (average value in three days) as compared with the historical early warning complaint data, and the complaint ratio is larger than the historical early warning complaint data, and TOP1 city/county satisfying the condition is output in any two days in the same three days. According to the complaint region delimitation rule, acquiring a city/district corresponding to the current early warning complaint data and the historical early warning complaint data related to the family broadband, performing geographical position distribution analysis, and performing delimitation analysis on the current early warning complaint data related to the family broadband, wherein the city/district corresponding to the current early warning complaint data and the historical early warning complaint data related to the family broadband comprises a coastal river region, a west lake region and a Yunzhou region. As shown in table 2, if the current early warning complaint data corresponding to the coastal river region is 40, the current early warning complaint data corresponding to the west lake region is 5, and the current early warning complaint data corresponding to the remaining hangzhong region is 5, it can be determined that the complaint percentage of the coastal river region is 80%, and the complaint percentages of the west lake region and the remaining hangzhong region are 10%, respectively. And the historical early warning complaint data corresponding to the coastal river area is 20 (30, 20 and 10 in three days), the percentage of the historical early warning complaint data in the same period is 50% (75, 50 and 25 in three days), the historical early warning complaint data corresponding to the western lake area is 10, the percentage of the historical early warning complaint data in the same period is 25%, the percentage of the historical early warning complaint data corresponding to the remaining Hangzhou area is 10, and the percentage of the historical early warning complaint data in the same period is 25%. According to the content, the complaint duty of the coastal river area is increased by 30PP and 20 in number compared with the historical early warning complaint data, the complaint duty of the west lake area is reduced by 15PP and 10 in number compared with the historical early warning complaint data, and the complaint duty of the rest Hangzhou area is reduced by 15PP and 10 in number compared with the historical early warning complaint data. Therefore, the output complaint area is concentrated in the coastal river area, the complaint proportion is increased by 30PP at the same time compared with the historical early warning complaint data, the number is increased by 20, and the specific process is shown in FIG. 6.
TABLE 2
| Current early warning complaint data numbering | Prefecture/prefecture |
| 1 | Bin river area |
| 2 | Bin river area |
| … | … |
| 39 | Bin river area |
| 40 | Bin river area |
| 41 | West lake region |
| … | … |
| 45 | West lake region |
| 46 | Zone of Yuhang |
| … | … |
| 50 | Zone of Yuhang |
In the embodiment of the application, the error code delimiting rule refers to that the complaint percentage of the current early warning complaint data recorded with the error codes in the current early warning complaint data related to the set early warning task exceeds a seventh threshold, the output error codes have obvious aggregation, otherwise, the output error codes do not have obvious aggregation. For example, for the home broadband early warning task, the error code delimitation rule refers to that the complaint percentage of the current early warning complaint data related to the home broadband, which is recorded with the error codes, in the current early warning complaint data related to the home broadband exceeds 30%, the obvious aggregation degree occurs in the output error codes, otherwise, the obvious aggregation degree does not occur in the output error codes }. Acquiring error codes of current early warning complaint data records related to the home broadband according to an error code delimiting rule, and carrying out delimiting analysis on the current early warning complaint data related to the home broadband, wherein for example, 50 error codes are recorded in 100 pieces of the current early warning complaint data related to the home broadband, the percentage of error code complaints is 50%, and exceeds 30% of the error code delimiting rule, so that obvious aggregation occurs in output error codes, otherwise, the obvious aggregation does not occur in the output error codes, and the specific flow is shown in fig. 7.
In the embodiment of the present application, after the above-mentioned bounding analysis, a fused bounding conclusion is displayed, as shown in fig. 8.
It should be noted that, if the fusion and delimitation conclusion does not meet the preset standard, the delimitation set rule is modified manually, and S303 and S304 are executed repeatedly according to the modified delimitation set rule. It should be noted that the preset criterion may be that the fusion and delimitation conclusion is not displayed within a specified time. The reason why the fusion and delimitation conclusion is not displayed within the specified time may be that a threshold value in a delimitation rule corresponding to a certain delimiting item is set too high, for example, the complaint proportion of the current early-warning complaint data in the complaint phenomenon delimitation rule, which is respectively related to various complaints contained in the home broadband, in the current early-warning complaint data related to the home broadband rises above 10PP compared with the thresholds 10PP and 5 in any two days in the same period (average value in three days) of the historical early-warning complaint data, and the complaint proportion is greater than the thresholds 10PP and 5 in any two days in the same period three days of the historical early-warning complaint data, if the thresholds are set to be 100PP and 500, the two threshold values are hard to reach, accordingly, the complaint phenomenon delimitation conclusion cannot appear in the fusion and delimitation conclusion cannot appear, and at this time, the interface displays "the fusion. And executing S303 and S304 after the user manually modifies the delimitation set rule.
In conclusion, compared with the prior art that the prior complaint early warning system can only acquire the delimiting result data, but cannot perform delimiting analysis to acquire the delimiting conclusion, the improved complaint early warning system in the embodiment of the application automatically executes the delimiting analysis according to the self-defined boundary set rule to acquire the fused delimiting conclusion after the early warning is generated, thereby effectively solving the problem that the newly-built early warning task cannot perform the delimiting analysis but needs manual analysis to acquire the delimiting conclusion; after indexes in the delimitation set rule are changed, re-delimitation can be immediately carried out according to the modified delimitation set rule, and the real-time performance is high; in addition, compared with the existing complaint early warning system, the early warning system integrates a delimitation conclusion, can display the delimitation result of the current early warning more intuitively, has higher accuracy, and provides more powerful data support for the effective closed loop of the early warning.
Fig. 9 shows a schematic structural diagram of a fusion delimiting device based on early warning complaint data, where the schematic structural diagram includes:
the device comprises a receiving module 901, an obtaining module 902 and a fusion delimitation module 903;
a receiving module 901, configured to receive an early warning indication signal; the early warning indication signal is related to a set early warning task;
an obtaining module 902, configured to obtain, according to the early warning indication signal, a delimitation set rule corresponding to the set early warning task; the early warning task configuration method comprises the following steps that a delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items;
the obtaining module 902 is further configured to obtain, according to the delimiting set rule, current early warning complaint data related to the delimiting set rule;
the fusion delimitation module 903 is used for performing delimitation analysis on the current early warning complaint data according to delimitation rules corresponding to each delimitation item in the delimitation set rules to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
The embodiment of the present application further provides a fusion delimiting device based on early warning complaint data, which includes at least one processor, where the processor is configured to execute a program stored in a memory, and when the program is executed, the device executes the following steps:
receiving an early warning indication signal; the early warning indication signal is related to a set early warning task; acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the early warning task configuration method comprises the following steps that a delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items; acquiring current early warning complaint data related to the delimitation set rule according to the delimitation set rule; carrying out delimitation analysis on the current early warning complaint data respectively according to delimitation rules corresponding to each delimitation item in the delimitation set rules to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when executed by a processor, the computer program implements the following steps:
receiving an early warning indication signal; the early warning indication signal is related to a set early warning task; acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the early warning task configuration method comprises the following steps that a delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items; acquiring current early warning complaint data related to the delimitation set rule according to the delimitation set rule; carrying out delimitation analysis on the current early warning complaint data respectively according to delimitation rules corresponding to each delimitation item in the delimitation set rules to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
It should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (14)
1. A fusion delimitation method based on early warning complaint data is characterized by comprising the following steps:
receiving an early warning indication signal; the early warning indication signal is related to a set early warning task;
acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items;
acquiring current early warning complaint data related to the delimitation set rule according to the delimitation set rule;
carrying out delimitation analysis on the current early warning complaint data respectively according to delimitation rules corresponding to each delimitation item in the delimitation set rules to obtain a fusion delimitation conclusion; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
2. The method of claim 1, wherein the early warning indication signal is generated if the number of current early warning complaint data related to early warning tasks is greater than a preset threshold.
3. The method of claim 1, wherein the delimiting rule corresponding to each delimiting item comprises: the early warning amplification starting time delimitation rule, the current trend delimitation rule, the artificial intelligence AI recording keyword refining delimitation rule, the complaint phenomenon delimitation rule, the complaint area delimitation rule and/or the error code delimitation rule.
4. The method according to claim 3, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
carrying out delimitation analysis on the current early warning complaint data according to an early warning amplification starting time delimitation rule; the early warning amplification starting time delimitation rule refers to starting time that the current early warning complaint data related to the set early warning task in a certain time period is increased by more than a first threshold value compared with the current early warning complaint data related to the set early warning task in a previous time period, and early warning amplification starting time is output; or the starting time when the number of the current early warning complaint data related to the set early warning task in a certain time period is larger than the second threshold value, and outputting early warning amplification starting time.
5. The method according to claim 3, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
carrying out delimitation analysis on the current early warning complaint data according to a current trend delimitation rule; the current trend delimiting rule refers to the percentage of increase or decrease of current early warning complaint data related to the set early warning task in a certain time period compared with the percentage of increase or decrease of the current early warning complaint data related to the set early warning task in a previous time period, and the current trend is output; or the number of the current early warning complaint data related to the set early warning task in a certain time period is increased or reduced compared with the number of the current early warning complaint data related to the set early warning task in the previous time period, and the current trend is output.
6. The method according to claim 3, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
refining a delimitation rule according to artificial intelligence AI recording keywords, and carrying out delimitation analysis on the current early warning complaint data; the artificial intelligent AI recording keyword refining delimitation rule is that current early warning complaint data related to a set early warning task are converted into a standard and structured text which can be analyzed, the text is refined to obtain keywords of the current early warning complaint data, the keywords are classified, complaint percentage of each type of keywords in all the keywords is determined, and the keywords with the first complaint percentage are output.
7. The method of claim 3, wherein obtaining current early warning complaint data related to the delimiter set rule according to the delimiter set rule comprises:
and acquiring the current early warning complaint data and the historical early warning complaint data related to the boundary set rule according to the boundary set rule.
8. The method according to claim 7, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
according to the complaint phenomenon delimitation rule, delimitation analysis is carried out on the current early warning complaint data; the complaint phenomenon delimiting rule refers to that the complaint duty ratio of current early warning complaint data respectively related to various complaint phenomena contained in a set early warning task in the current early warning complaint data related to the set early warning task is compared with historical early warning complaint data, the complaint duty ratio is synchronously increased to exceed a third threshold value, the increment of the complaint duty ratio exceeds a fourth threshold value, and the complaint duty ratio is larger than the historical early warning complaint data, and the first complaint phenomenon meeting the condition is output in any two days in three days in the same period.
9. The method according to claim 7, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
according to the complaint area delimitation rule, delimitation analysis is carried out on the current early warning complaint data; the complaint region delimitation rule refers to that complaint duty ratios of current early warning complaint data, related to the set early warning task, of various cities/counties in the current early warning complaint data, related to the set early warning task, synchronously rise to exceed a fifth threshold value and increase to exceed a sixth threshold value, and the complaint duty ratios are larger than any two days in three days in the same period of the historical early warning complaint data, and the first city/county meeting the conditions is output.
10. The method according to claim 3, wherein the delimiting analysis is performed on the current early warning complaint data according to the delimiting rules corresponding to the delimiting items in the delimiting set rules, respectively, and includes:
carrying out delimitation analysis on the current early warning complaint data according to an error code delimitation rule; the error code delimitation rule refers to that the complaint percentage of the current early warning complaint data recorded with the error codes in the current early warning complaint data related to the set early warning task exceeds a seventh threshold, the obvious aggregation degree appears when the error codes are output, and otherwise, the obvious aggregation degree does not appear when the error codes are output.
11. The method according to claim 1, wherein the current early warning complaint data is subjected to delimitation analysis according to delimitation rules corresponding to each delimitation item in the delimitation set rules, and after a fusion delimitation conclusion is obtained, the method further comprises:
and under the condition that the fusion delimitation conclusion does not accord with the preset standard, acquiring the modified delimitation set rule and re-delimitating according to the modified delimitation set rule.
12. The utility model provides a fuse and delimit device based on early warning complaint data which characterized in that includes:
the receiving module is used for receiving the early warning indication signal; the early warning indication signal is related to a set early warning task;
the acquisition module is used for acquiring a delimitation set rule corresponding to the set early warning task according to the early warning indication signal; the delimitation set rule is obtained according to early warning task configuration, and the delimitation set rule comprises delimitation rules corresponding to delimitation items;
the acquisition module is further used for acquiring the related current early warning complaint data according to the delimitation set rule;
the fusion delimitation module is used for performing delimitation analysis on the current early warning complaint data according to delimitation rules corresponding to all delimitation items in the delimitation set rules to obtain fusion delimitation conclusions; the fused delimited conclusion is a collection of conclusions for various delimited analyses.
13. A fusion delimited apparatus based on early warning complaint data, comprising at least one processor configured to execute a program stored in a memory, the program, when executed, causing the apparatus to perform the method of any of claims 1-11.
14. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the method according to any one of claims 1-11.
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