CN111292094A - Complaint early warning method, device, equipment and medium based on big data technology - Google Patents
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Abstract
The application discloses a complaint early warning method, a complaint early warning device, complaint early warning equipment and a complaint early warning medium based on a big data technology. The method comprises the following steps: preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set; determining the probability of each complaint event corresponding to a preset alarm event based on the alarm data set and the complaint work order data set; and obtaining the complaint events matched with the preset alarm events according to the preset rules and the probability of each complaint event corresponding to the preset alarm. According to the embodiment of the invention, the complaint event can be predicted more accurately.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a complaint early warning method, a complaint early warning device, complaint early warning equipment and complaint early warning media based on a big data technology.
Background
Large enterprises all have own monitoring alarm system and complaint work order processing system. The monitoring alarm system is used by Information Technology (IT) operation maintenance personnel, and is mainly used for monitoring the operation state of the IT system in real time. The complaint work order system is used by customer service personnel and IT operation and maintenance personnel and is mainly used for processing various consultation, complaint and the like of customers.
Currently, these two systems are relatively independent. When some system alarms appear, the influence of the alarms on the number of the complaint work orders of which types can be caused cannot be predicted, and meanwhile, a prediction mechanism for complaints is lacked, so that customer service personnel cannot prepare related order receiving in advance, and further the customer satisfaction of complaint management is influenced.
Therefore, there is a technical problem that a complaint work order that may occur cannot be predicted by an alarm.
Disclosure of Invention
The embodiment of the invention provides a method, a device, equipment and a medium for early warning of complaints based on a big data technology, which can predict the possibly-occurring complaint work orders through alarming.
In one aspect of the embodiments of the present invention, a method for early warning of complaints based on big data technology is provided, where the method includes:
preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set;
determining the probability of each complaint event corresponding to a preset alarm event based on the alarm data set and the complaint work order data set;
and obtaining the complaint events matched with the preset alarm events according to the preset rules and the probability of each complaint event corresponding to the preset alarm.
In another aspect of the embodiments of the present invention, a device for early warning of complaints based on big data technology is provided, where the device includes:
the preprocessing module is used for preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set;
the probability module is used for determining the probability of each complaint event corresponding to the preset alarm event based on the alarm data set and the complaint work order data set;
and the early warning module is used for obtaining the complaint events matched with the preset warning events according to the preset rules and the probability of each complaint event corresponding to the preset warning.
According to another aspect of the embodiments of the present invention, there is provided a complaint early warning apparatus based on big data technology, the apparatus including:
a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the method for complaint warning based on big data technology as provided above in any aspect of embodiments of the present invention.
According to another aspect of the embodiments of the present invention, there is provided a computer storage medium having computer program instructions stored thereon, where the computer program instructions, when executed by a processor, implement a method for complaint early warning based on big data technology as provided in any aspect of the embodiments of the present invention.
The embodiment of the invention provides a complaint early warning method, a complaint early warning device, complaint early warning equipment and a complaint early warning medium based on a big data technology. The accuracy of the service classification of the complaint work order is improved by preprocessing the alarm data and the complaint work order data, and the complaint event can be predicted more accurately by performing probability calculation by combining the alarm data and the complaint work order data.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a complaint warning method based on big data technology according to an embodiment of the invention;
FIG. 2 shows a flow diagram of a method for complaint warning based on big data technology according to another embodiment of the invention;
FIG. 3 is a result diagram illustrating a cause of a complaint event according to an embodiment of the invention;
FIG. 4 is a schematic diagram illustrating complaint warning in accordance with one embodiment of the present invention;
FIG. 5 is a schematic structural diagram of a complaint warning device based on big data technology according to an embodiment of the present invention;
FIG. 6 sets forth a block diagram of an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for complaint warning based on big data technology according to embodiments of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The method, the device, the equipment and the medium for the complaint early warning based on the big data technology according to the embodiment of the invention are described in detail below with reference to the attached drawings. It should be noted that these examples are not intended to limit the scope of the present disclosure.
The method for early complaint warning based on big data technology according to the embodiment of the invention is described in detail below with reference to fig. 1 to 4.
For better understanding of the present invention, the method for early warning complaints based on big data technology according to an embodiment of the present invention is described in detail below with reference to fig. 1, and fig. 1 is a flowchart illustrating the method for early warning complaints based on big data technology according to an embodiment of the present invention.
As shown in fig. 1, a method 100 for early complaint warning based on big data technology in an embodiment of the present invention includes the following steps:
and S110, preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set.
Specifically, the alarm data may include: alarm resource identification ID, alarm title, alarm content and alarm occurrence time. Complaint work order data may include: complaint work order ID, complaint content, and type of service. The alarm data set may include: historical alarm data and alarm data for currently occurring alarm events. The complaint work order data set may include: historical complaint work order data and complaint work order data for currently occurring complaint events. Thus, the alarm data set and complaint work order data set are one dynamically expanding data set.
As an example, the service type of the alarm event may be determined using the service system and the alarm resource ID, the alarm title and the alarm content may be used to determine the occurrence type of the alarm event, and the alarm occurrence time may be used to correlate the occurrence time of the complaint work order. The type of service in the complaint work order data may be used to correlate with the type of service in the alarm data. The occurrence type may refer to a port alarm or a storage space alarm.
In one embodiment of the present invention, when the alarm data is incomplete, the alarm data needs to be refined to ensure that the complaint early warning can be performed according to the alarm data.
And the word segmentation device can be used for carrying out word segmentation on the complaint content in the complaint worksheet data to obtain a text entry. And then, automatically correcting the service types in the complaint work order data. The automatic error correction process may be: and extracting complaint keywords from the obtained text entries according to a semantic analysis function in the big data analysis platform. And then comparing the complaint keywords with the service type keywords in the complaint work order automatic error correction dictionary, when the comparison result is consistent, starting to judge whether the service type in the complaint work order data is consistent with the service type in the complaint work order automatic error correction dictionary, and when the judgment result is inconsistent, automatically correcting the service type in the complaint work order data.
In another example of the present invention, eight-level classification of complaint work order data may also be corrected using auto-error correction. Wherein the eight-level classification refers to the service classification of the complaint time based on the complaint work order data.
In the embodiment of the invention, the accuracy of the service classification of the complaint work order can be improved by preprocessing the alarm data and the complaint work order data, and the accuracy of the complaint early warning can be further improved.
In another embodiment of the present invention, the alarm data set and the resource configuration data set may also be associated. The resource configuration data set may be data information required to include the alarm data set. By associating the alarm data set with the resource configuration data set, the alarm data set can include data information required for complaint early warning.
And S120, determining the probability of each complaint event corresponding to the preset alarm event based on the alarm data set and the complaint work order data set.
First, the probability of the occurrence of the same kind of alarm is determined based on the alarm data set, as shown in expression (1).
Wherein, P (A)i) Representing homogeneous alarms A in an alarm data set AiProbability of occurrence, AiThe number of the same type of alarm events is shown, and the same type of alarm events refers to the alarm resource ID and the alarm title phase in the alarm data set AThe same alarm event.
The probability of occurrence of a complaint event is also determined based on the complaint work order data set, as shown in expression (2).
Wherein, P (B)i) Is the probability of occurrence of a complaint event, BiThe number of the complaint work orders corresponding to a complaint event is shown, and B is the number of the complaint work orders.
Next, the probability of the preset alarm event corresponding to each complaint event is calculated, as shown in expression (3).
Wherein, BinMeans that the alarm A is in the same classiThe number of complaint work orders corresponding to a complaint event in a preset time period, BnIs referred to as a similar alarm event AiThe number of all complaint work orders within a preset time period of occurrence.
It should be noted that the generation of a complaint work order will generally lag behind the occurrence of an alarm event, but the lag time will typically not exceed 48 hours. Therefore, in the embodiment of the present invention, 24 hours may be selected as the preset time period, but the preset time period of 24 hours is only exemplary and is not particularly limited.
In the embodiment of the invention, the probability of each complaint event corresponding to the preset alarm event can be obtained through the expression, so that the complaint event which is most likely to occur under the condition that the preset alarm event occurs can be determined according to the probability.
And S130, obtaining the complaint event matched with the preset alarm event according to the preset rule and the probability of each complaint event corresponding to the preset alarm event.
In one embodiment of the present invention, the preset rule may be to arrange the complaint events in order of probability values from large to small based on the probability of occurrence of each complaint event in the case where the preset alarm event occurs. In which complaint events with an occurrence probability of 0 can be ignored.
Next, according to the ranked complaint events, the first a complaint events can be obtained as the complaint events that are most likely to occur when the preset alarm event occurs, that is, the obtained first a complaint events are taken as the complaint events matched with the preset alarm event. It should be noted that a should take a positive integer.
As shown in table 1, table 1 shows a schematic diagram of the complaint warning effect of an embodiment of the invention. The process state is exhausted as a preset alarm event, and the top 3 complaint events are obtained from the arranged complaint events and are used as the most probable complaint events when the process state is exhausted.
TABLE 1
By the method for the complaint early warning based on the big data technology, accuracy of service classification of the complaint work orders is improved by preprocessing alarm data and complaint work order data, the probability of each complaint work order corresponding to the preset alarm is sequenced according to the preset rule, and the most likely complaint work order under the condition that the preset alarm event occurs can be obtained, so that the complaint early warning of the preset alarm event is realized.
For ease of understanding, fig. 2 shows a flowchart of a method for complaint early warning based on big data technology according to another embodiment of the present invention. The steps in fig. 2 that are the same as in fig. 1 are given the same reference numerals.
As shown in fig. 2, the method 200 for early warning of complaints based on big data technology has the same steps as the method 100 for early warning of complaints based on big data technology shown in fig. 1, and is not repeated here. The method 200 for early warning of complaints based on big data technology in the embodiment of the invention further comprises the following steps:
and S210, determining the probability of each preset complaint event corresponding to each alarm event based on the Bayesian algorithm, the alarm data set and the complaint work order data set.
In an embodiment of the present invention, the probability of occurrence of a similar alarm in the alarm data set a obtained through the expression (1), the probability of occurrence of a certain complaint event in the complaint work order data set B obtained through the expression (2), and the probability of each complaint event corresponding to the preset alarm event obtained through the expression (3) may be obtained according to a bayesian formula, that is, the expression (4), where the probability P (a) of each alarm event corresponding to the preset complaint event may be obtainedi|Bi)。
Therefore, the probability P (A) of each alarm event corresponding to the preset complaint event can be obtainedi|Bi)。
And S220, obtaining the alarm event matched with the preset complaint event according to the preset rule and the probability of each alarm event corresponding to the preset complaint event.
In an embodiment of the present invention, each alarm event may be arranged according to an order of a probability of occurrence from large to small based on a probability of each alarm event corresponding to a preset complaint event. Wherein an alarm event with an occurrence probability of 0 may be ignored.
Next, according to the ranked alarm events, the first b alarm events can be obtained therefrom as the most likely alarm events that will occur under the condition that the preset complaint event occurs, that is, the obtained first b alarm events are the most likely root cause of the preset complaint event. It should be noted that b should take a positive integer.
As shown in fig. 3, fig. 3 is a diagram illustrating the result of the cause of the complaint event according to an embodiment of the invention. The package is changed to be used as a preset complaint event, the first 3 alarm events are obtained from the arranged alarm events, and the 3 alarm events are considered to have the maximum possibility as the root cause of the preset complaint event.
In the embodiment of the invention, the centralized optimization processing can be carried out according to the most likely root cause of the obtained preset complaint event, and the occurrence frequency of the alarm event is reduced as much as possible, so that the occurrence frequency of the preset complaint event can be effectively reduced, and the product experience of a user is further improved.
In another embodiment of the present invention, as shown in fig. 4, fig. 4 is a schematic diagram illustrating a complaint warning according to an embodiment of the present invention. And taking the complaint worksheet set processed by the complaint worksheet error correction algorithm, the resource data set processed by the alarm associated service influence algorithm, the alarm data set, the service system log set, the user data and the order information set as a data training set.
And calculating prior probability and posterior probability through a Bayesian algorithm based on data information in the data training set, finally obtaining a complaint work order prediction scene based on the prior probability, and obtaining a complaint reason analysis scene based on the posterior probability.
The following describes in detail an apparatus for early complaint warning based on big data technology according to an embodiment of the present invention with reference to fig. 5, where the apparatus for early complaint warning based on big data technology corresponds to the method for early complaint warning based on big data technology.
Fig. 5 is a schematic structural diagram of a complaint warning device based on big data technology according to an embodiment of the present invention.
As shown in fig. 5, the apparatus 500 for early complaint warning based on big data technology includes:
and a preprocessing module 510, configured to preprocess the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set.
And a probability module 520, configured to determine a probability that each complaint event corresponds to a preset alarm event based on the alarm data set and the complaint work order data set.
The early warning module 530 is configured to obtain a complaint event matched with the preset warning event according to the preset rule and the probability that the preset warning corresponds to each complaint event.
With the apparatus for early warning of complaints based on big data technology according to the above embodiment, the accuracy of service classification of the complaint work order can be improved by preprocessing the alarm data and the complaint work order data through the preprocessing module 510, and complaint events that are most likely to occur under the condition that the preset alarm event occurs are obtained through the probability module 520 and the early warning module 530, so as to achieve the early warning of complaints.
In an embodiment of the present invention, the preprocessing module 510 is specifically configured to refine the alarm data to obtain an alarm data set. And automatically correcting the service types in the complaint work order data. Wherein the automatic error correction comprises: the method comprises the steps of carrying out word segmentation on complaint contents in complaint work order data to obtain text entries, and determining complaint keywords based on the text entries and a big data analysis platform. And automatically correcting the service type in the complaint work order data according to the complaint keyword and the automatic error correction dictionary table. Wherein the alarm data includes: the ID of the alarm resource identity, the alarm title, the alarm content and the alarm occurrence time, and the complaint work order data comprises: complaint work order ID, complaint content, and type of service. The alarm data set includes: historical alarm data and alarm data for currently occurring alarm events. The complaint work order data set includes: historical complaint work order data and complaint work order data for currently occurring complaint events. And determining the service type of the alarm event based on the service system and the alarm resource ID.
In an embodiment of the present invention, the preprocessing module 510 is further configured to associate the alarm data set with the resource configuration data set.
In an embodiment of the present invention, the early warning module 530 is specifically configured to obtain, based on the complaint events sorted according to the preset rule, the first a complaint events as complaint events matched with the preset alarm event, where a is a positive integer. The preset rules include: and sequencing each complaint event according to the sequence of the probability of each complaint event corresponding to the preset alarm event from large to small.
In an embodiment of the present invention, the apparatus 500 for early complaint warning based on big data technology further includes:
and the analysis module 540 is configured to determine, based on the bayesian algorithm, the alarm data set and the complaint work order data set, a probability that each preset complaint event corresponds to each alarm event. And obtaining the alarm event matched with the preset complaint event according to the preset rule and the probability of each alarm event corresponding to the preset complaint event.
FIG. 6 sets forth a block diagram of an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for complaint warning based on big data technology according to embodiments of the present invention.
As shown in fig. 6, computing device 600 includes an input device 601, an input interface 602, a central processor 603, a memory 604, an output interface 605, and an output device 606. The input interface 602, the central processing unit 603, the memory 604, and the output interface 605 are connected to each other via a bus 610, and the input device 601 and the output device 606 are connected to the bus 610 via the input interface 602 and the output interface 605, respectively, and further connected to other components of the computing device 600.
Specifically, the input device 601 receives input information from the outside, and transmits the input information to the central processor 603 through the input interface 602; the central processor 603 processes input information based on computer-executable instructions stored in the memory 604 to generate output information, stores the output information temporarily or permanently in the memory 604, and then transmits the output information to the output device 606 through the output interface 605; output device 606 outputs output information to the exterior of computing device 600 for use by a user.
That is, the computing device shown in fig. 6 may also be implemented with a device for complaint early warning based on big data technology, and the device for complaint early warning based on big data technology may include: a memory storing computer-executable instructions; and a processor that when executing computer executable instructions may implement the method and apparatus for complaint warning based on big data technology described in conjunction with fig. 1-5.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium has computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the method and apparatus for complaint early warning based on big data technology provided by the embodiments of the present invention.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention. The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
The present invention may be embodied in other specific forms without departing from its spirit or essential characteristics. For example, the algorithms described in the specific embodiments may be modified without departing from the basic spirit of the invention. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (13)
1. A complaint early warning method based on big data technology is characterized by comprising the following steps:
preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set;
determining the probability of each complaint event corresponding to a preset alarm event based on the alarm data set and the complaint work order data set;
and obtaining the complaint event matched with the preset alarm event according to the preset rule and the probability of each complaint event corresponding to the preset alarm event.
2. The big data technology-based complaint warning method according to claim 1, wherein the warning data comprises: the alarm resource identity ID, the alarm title, the alarm content and the alarm occurrence time, wherein the complaint work order data comprises: complaint work order ID, complaint content, and type of service.
3. The big data technology-based complaint warning method of claim 1, wherein the alarm data set comprises: historical alarm data and alarm data for currently occurring alarm events,
the complaint work order dataset includes: historical complaint work order data and complaint work order data for currently occurring complaint events.
4. The big data technology-based complaint warning method according to claim 2, wherein the service type of the alarm event is determined based on a service system and the alarm resource ID.
5. The method for early warning of complaints based on big data technology as claimed in claim 1, wherein said preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set comprises:
perfecting the alarm data to obtain an alarm data set;
and automatically correcting the service types in the complaint work order data.
6. The big-data-technology-based complaint early warning method according to claim 5, wherein the automatic error correction comprises:
performing word segmentation processing on the complaint content in the complaint worksheet data to obtain a text entry;
determining complaint keywords based on the text entries and the big data analysis platform;
and automatically correcting the service type in the complaint work order data according to the complaint keyword and the automatic error correction dictionary table.
7. The big data technology-based complaint early warning method according to claim 1, wherein the preset rules include: and sequencing each complaint event according to the sequence of the probability of each complaint event corresponding to the preset alarm event from large to small.
8. The method for complaint early warning based on big data technology as claimed in claim 7, wherein the obtaining of the complaint event matching the preset alarm event according to the preset rule and the probability of each complaint event corresponding to the preset alarm comprises:
and acquiring the first a complaint events as the complaint events matched with the preset alarm event based on the complaint events sequenced according to the preset rule, wherein a is a positive integer.
9. The big data technology-based complaint early warning method according to claim 1, further comprising:
based on a Bayesian algorithm, the alarm data set and the complaint work order data set, the probability of each alarm event corresponding to a preset complaint event is determined;
and obtaining the alarm event matched with the preset complaint event according to the preset rule and the probability of each alarm event corresponding to the preset complaint event.
10. The big data technology-based complaint early warning method according to claim 1, further comprising:
and associating the alarm data set with the resource configuration data set.
11. The utility model provides a device of complaint early warning based on big data technology which characterized in that includes:
the preprocessing module is used for preprocessing the alarm data and the complaint work order data to obtain an alarm data set and a complaint work order data set;
the probability module is used for determining the probability of each complaint event corresponding to a preset alarm event based on the alarm data set and the complaint work order data set;
and the early warning module is used for obtaining the complaint events matched with the preset alarm events according to the preset rules and the probability of each complaint event corresponding to the preset alarm.
12. An apparatus for complaint early warning based on big data technology, the apparatus comprising: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements a method for complaint warning based on big data technology as claimed in any of claims 1-10.
13. A computer storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method for big data technology based complaint warning according to any of claims 1-10.
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