CN110222936A - A kind of root of business scenario is because of localization method, system and electronic equipment - Google Patents
A kind of root of business scenario is because of localization method, system and electronic equipment Download PDFInfo
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Abstract
This specification embodiment provides a kind of root of business scenario because of localization method, system and electronic equipment, the root of the business scenario includes: at least one data dimension of srvice instance in the first preset time period where the time of origin point based on current alerts because of localization method, determines the contextual data of the current alerts；Using the contextual data of the current alerts as root because of the input of location model, to obtain the current alerts corresponding because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are obtained because of training；Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
Description
Technical field
This specification embodiment is related to technical field of data processing more particularly to a kind of root of business scenario because of positioning side
Method, system and electronic equipment.
Background technique
With the fast development of information age, the business of each enterprise is maked rapid progress, and supports the platform type of each business numerous
It is more.As code frequent on each platform alternates, platform feature update and platform configuration parameter modification etc. cause to emerge one after another
Abnormal alarm, bring potential economic loss and security risk to enterprise.Therefore, the root of business scenario is because of positioning to Guan Chong
It wants.
The root of existing business scenario is because of localization method, by analyzing reason similar in numerous alarm scenes, from general character
Angle is set out, determine alarm scene in frequently occur the reason of be exactly alarm root because.But the program has the following deficiencies:
Need to count various frequent item sets, algorithm complexity is higher.Therefore, the root of existing business scenario is because of localization method algorithm complexity
Spend it is higher, can not in time locating alarming root because.
Summary of the invention
This specification embodiment provides a kind of root of business scenario because of localization method, system and electronic equipment, to solve now
The root of some business scenarios because localization method algorithm complexity is higher, can not in time locating alarming root because the problem of.
This specification embodiment adopts the following technical solutions:
In a first aspect, providing a kind of root of business scenario because of localization method, comprising:
At least one data of srvice instance in the first preset time period where time of origin point based on current alerts
Dimension determines the contextual data of the current alerts；
It is corresponding to obtain the current alerts using the contextual data of the current alerts as root because of the input of location model
Root because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because of item
The training of part probability distribution obtains；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
Second aspect provides a kind of root of business scenario because of positioning system, comprising:
First data determining module, for industry in the first preset time period where the time of origin point based on current alerts
At least one data dimension of pragmatic example, determines the contextual data of the current alerts；
Input module, for using the contextual data of the current alerts as root because of the input of location model, to obtain
Current alerts corresponding is stated because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history
And corresponding because conditional probability distribution training obtain；
First because of determining module, described in, because of conditional probability distribution, being determined based on the current alerts corresponding
Corresponding of current alerts because.
The third aspect provides a kind of electronic equipment, comprising: memory, processor and is stored on the memory simultaneously
The computer program that can be run on the processor realizes following step when the computer program is executed by the processor
It is rapid:
At least one data of srvice instance in the first preset time period where time of origin point based on current alerts
Dimension determines the contextual data of the current alerts；
It is corresponding to obtain the current alerts using the contextual data of the current alerts as root because of the input of location model
Root because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because of item
The training of part probability distribution obtains；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
Fourth aspect provides a kind of computer readable storage medium, is stored on the computer readable storage medium
Computer program, the computer program realize following steps when being executed by processor:
At least one data of srvice instance in the first preset time period where time of origin point based on current alerts
Dimension determines the contextual data of the current alerts；
It is corresponding to obtain the current alerts using the contextual data of the current alerts as root because of the input of location model
Root because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because of item
The training of part probability distribution obtains；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
This specification embodiment use at least one above-mentioned technical solution can reach it is following the utility model has the advantages that
This specification embodiment is based on srvice instance in the first preset time period where the time of origin point of current alerts
At least one data dimension, determine the contextual data of current alerts, more alarm fields can be provided because of positioning for subsequent
Scape information improves root because of the accuracy of positioning；By using the contextual data of current alerts as root because of the input of location model, with
Current alerts corresponding is obtained because of conditional probability distribution, then is determined based on current alerts corresponding because of conditional probability distribution
Current alerts corresponding because by, because location model carries out root because of positioning, simplifying root because of positioning side using trained
The algorithm complexity of method, can provide in time when alarming and occurring causes the root of alarm because to achieve the purpose that stop loss in time.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand this specification, forms part of this specification,
The illustrative embodiments and their description of this specification do not constitute the improper restriction to this specification for explaining this specification.
In the accompanying drawings:
Fig. 1 is flow chart of the root because of localization method for the business scenario that one embodiment of this specification provides；
Fig. 2 is structural block diagram of the root because of positioning system for the business scenario that one embodiment of this specification provides；
Fig. 3 is the structural block diagram for the electronic equipment that one embodiment of this specification provides.
Specific embodiment
To keep the purposes, technical schemes and advantages of this specification clearer, it is embodied below in conjunction with this specification
This specification technical solution is clearly and completely described in example and corresponding attached drawing.Obviously, described embodiment is only this
Specification a part of the embodiment, instead of all the embodiments.The embodiment of base in this manual, ordinary skill people
Member without making creative work determined by every other embodiment, belong to this specification protection range.
This specification embodiment provides a kind of root of business scenario because of localization method, system and electronic equipment, to solve now
The root of some business scenarios because localization method algorithm complexity is higher, can not in time locating alarming root because the problem of.This specification
Embodiment provides the root of business scenario a kind of because of localization method, the executing subject of this method, can be, but not limited to electronic equipment or
It can be configured as executing the device or system of this method that this specification embodiment provides.
For ease of description, the embodiment of this method is introduced hereafter by taking electronic equipment as an example.It is appreciated that should
The executing subject of method is that electronic equipment is a kind of illustrative explanation, is not construed as the restriction to this method.
Fig. 1 is flow chart of the root of business scenario that provides of this specification embodiment because of localization method, and the method for Fig. 1 can be with
It is executed by electronic equipment, as shown in Figure 1, this method may include:
Srvice instance is at least in the first preset time period where step 110, the time of origin point based on current alerts
One data dimension, determines the contextual data of the current alerts.
First preset time period can be arranged according to actual needs, and this specification embodiment is not especially limited.
It will be appreciated that at least one data dimension is the data dimension with distinction.
This step specifically can be achieved are as follows: when alarm occur when, determine current alerts occur the moment where first it is default when
Between section, obtain at least one data dimension of srvice instance in first preset time period；Again based in the first preset time period
At least one data dimension of srvice instance determines the contextual data of current alerts.
Illustratively, it is assumed that occurs for current alerts for 9 points of March 1 in 2019 moment, and the first preset time period is 2019
10 minutes 9 points of March 1 of 50 minutes to 2019 8 points of March 1, at this point, obtaining at least one data dimension of srvice instance, such as at least
One data dimension includes: Appname (application name) (area) (qualified item) current
The informative abstract (MD5) of moment all srvice instance is gathered.
Specifically, being based on this at least if at least one data dimension includes production time, production parameter etc.
One data dimension, it may be determined that the scene of current alerts is production scene, and determines the contextual data of production scene；If at least one
A data dimension includes the sales mode etc. of the consumption sum of product, product, then is based at least one data dimension, and determination is worked as
The scene of preceding alarm is sale scene, and determines the contextual data of the sale scene.
Step 120, using the contextual data of the current alerts as root because of the input of location model, it is described current to obtain
Corresponding is alarmed because of conditional probability distribution.
Wherein, root is because of conditional probability distribution, can refer to current alerts it is corresponding all because probability scenarios.
Wherein, the described contextual data alarmed by location model based on history and corresponding are obtained because of training.
The root is because the contextual data that the training data of location model is history alarm and corresponding are because of, wherein history report
Alert contextual data be based on history alarm moment time of origin point where the second preset time period in srvice instance at least
What one data dimension determined, history alarms corresponding because can summarize based on the working experience of technical staff, or
Person is obtained based on Frequent Pattern Mining.
Step 130 is based on the current alerts corresponding because of conditional probability distribution, determines that the current alerts are corresponding
Root because.
This step specifically can be achieved are as follows: based on current alerts corresponding because of conditional probability distribution, determination meets predetermined item
The root of part because corresponding of probability because as corresponding of current alerts because.Wherein, predetermined condition can be selected according to actual needs
It takes, for example, predetermined condition is the condition, etc. of maximum probability.
This specification embodiment is based on srvice instance in the first preset time period where the time of origin point of current alerts
At least one data dimension, determine the contextual data of current alerts, more alarm fields can be provided because of positioning for subsequent
Scape information improves root because of the accuracy of positioning；By using the contextual data of current alerts as root because of the input of location model, with
Current alerts corresponding is obtained because of conditional probability distribution, then is determined based on current alerts corresponding because of conditional probability distribution
Current alerts corresponding because by, because location model carries out root because of positioning, simplifying root because of positioning side using trained
The algorithm complexity of method, can provide in time when alarming and occurring causes the root of alarm because to achieve the purpose that stop loss in time.
Optionally, as one embodiment, step 130 specifically be can be achieved are as follows:
Based on the prior probability of the current alerts scene, target root because prior probability, and in target root because of appearance
In the case of scene be the current alerts scene conditional probability, determine that the current alerts scene is by target root because of generation
Posterior probability, the target root because be corresponding of the current alerts because any one root in conditional probability distribution because；
The maximum target of posterior probability is selected because in because of the root in conditional probability distribution at the current alerts corresponding
Root because as corresponding of the current alerts because.
Wherein, prior probability (prior probability) refers to the probability obtained according to previous experiences and analysis.
Wherein, the determination current alerts scene is by target root because the posterior probability specific implementation of generation can be with
Are as follows:
Based on the prior probability of the current alerts scene, target root because prior probability, and in target root because of appearance
In the case of scene be the current alerts scene conditional probability, by Bayes principle determine the current alerts scene be by
Posterior probability of the target root because of generation.
Specifically, it is assumed that using two variables Bayesian formula, the formula are as follows:
Determine that current alerts scene is the posterior probability by target root because of generation；
Wherein, P (A) indicates target root because of the prior probability of A；The prior probability of P (B) expression current alerts scenario B；P(B/
A) indicate that scene is the conditional probability of current alerts scenario B in the case where target root is because of A appearance；P (B/A) indicates current alerts
Scenario B is the posterior probability generated by target root by A.
Illustratively, it is assumed that scene has sale scene, production scene and processing scene, the sale scene, production if it exists
Scene and processing scene mutual exclusion, then the scene of current alerts is respectively that the priori of sale scene, production scene and processing scene is general
Rate is 1/3；
If target root because including: target root because a, target root are because b, target root are because c and target root are because of d, the target root because a,
Target root because b, target root because of c and target root because d is mutual exclusion root because then target root is because a, target root are because b, target root are because of c and mesh
Root is marked because the prior probability of d is 1/4；
If it is 1/a that scene, which is the conditional probability of sale scene, in the case that target root occurs because of a, target root occurs because of b
In the case of scene be that sell the conditional probability of scene be 1/b, scene be the condition of sale scene in the case that target root occurs because of c
Probability is 1/c, and it is 1/d that scene, which is the conditional probability of sale scene, in the case that target root occurs because of d, then:
It is the posterior probability generated by target root by a in sale scene
It is the posterior probability generated by target root by b in sale scene
It is the posterior probability generated by target root by c in sale scene
It is the posterior probability generated by target root by d in sale scene
Wherein, if a > b > c > d, selling scene is the posterior probability maximum generated by target root by d, it may be determined that pin
Selling scene is by target root because d is generated, i.e., the root of sale scene is because of target root because of d.
This specification embodiment by corresponding of current alerts because the root in conditional probability distribution selects posteriority because in
The target root of maximum probability because as corresponding of current alerts because the root that can be positioned in time when alarming and occurring is because in
Possibility maximum because improving accuracy of the root because of positioning.
Optionally, it as one embodiment, is corresponded in the contextual data alarmed based on the history and history alarm
Root because training described because of location model before, determine that history alarms corresponding because can specifically use following two side
Formula:
The first, based within the unit time history root because frequency and the history root because weighted value, determine described in
History alarm corresponding because；Wherein, the history root because be before the history alarms the moment root that occurred because.
Second, based on history root because and the probability that occurs simultaneously of history alarm, and the history is alarmed the case where occurring
Lower because the history root because conditional probability, determine the history alarm corresponding because；Wherein, the history root is because being
Before the history alarms the moment root that occurred because.
Specifically, if the first probability and the second probability are minimum value, it is determined that the history root is because as the history
The root of alarm because.Wherein, first probability are as follows: in the case that history alarm occurs root because be history root because condition it is general
Rate；Second probability are as follows: the history root because and the history alarm simultaneously appearance probability.
This specification embodiment by history root because and history alarm determine history alarm corresponding because of Yi Gen Yinding
Bit model prepares training sample data, when alarm occurs, by the way that the contextual data of current alerts is inputted root because of location model
The correspondence roots of current alerts be can be obtained because and according to the correspondence root of the current alerts of acquisition because it is corresponding to obtain current alerts
Root is because of conditional probability distribution, and without expending the more calculating time, real-time is higher.
More than, the root of the business scenario of this specification embodiment is described in detail because of localization method, in the following, combining figure in Fig. 1
2, the root of the business scenario of this specification embodiment is described in detail because of positioning system.
Fig. 2 shows the roots of the business scenario of this specification embodiment offer because of the structural schematic diagram of positioning system, such as Fig. 2
Shown, the root of the business scenario may include: because of positioning system 200
First data determining module 210, for the first preset time period where the time of origin point based on current alerts
At least one data dimension of interior srvice instance, determines the contextual data of the current alerts；
Input module 220, for using the contextual data of the current alerts as root because of the input of location model, to obtain
Corresponding of the current alerts are because of conditional probability distribution, wherein the described scene number alarmed by location model based on history
According to and corresponding because training obtain；
First determines institute for being based on the current alerts corresponding because of conditional probability distribution because of determining module 230
State corresponding of current alerts because.
In one embodiment, described first includes: because of determining module 230
First probability determining unit, for the prior probability based on the current alerts scene, target root because priori it is general
Rate, and in the case where target root is because occurring, scene is the conditional probability of the current alerts scene, determines the current alerts
Scene is the posterior probability by target root because of generation, and the target root is because being the current alerts corresponding because of conditional probability point
Any one root in cloth because；
Selection unit, for selecting posteriority general because in because of the root in conditional probability distribution at the current alerts corresponding
The maximum target root of rate because as corresponding of the current alerts because.
In one embodiment, first probability determining unit includes:
Determine the probability subelement, for the prior probability based on the current alerts scene, target root because prior probability,
And in the case where target root is because occurring, scene is the conditional probability of the current alerts scene, determines institute by Bayes principle
Stating current alerts scene is the posterior probability by target root because of generation.
In one embodiment, the root of the business scenario includes: because of positioning system 200
Second data determining module 240, for the second preset time where moment time of origin point of being alarmed based on history
At least one data dimension of srvice instance in section determines the contextual data of the history alarm；
Training module 250, contextual data and the history for being alarmed based on the history alarm corresponding because of item
Described of part probability distribution training is because of location model.
In one embodiment, the root of the business scenario includes: because of positioning system 200
Second because of determining module 260, for based within the unit time history root because frequency and the history root because
Weighted value, determine that the history alarms corresponding because, wherein the history root is because being before the history alarms the moment
The root occurred because.
In one embodiment, the root of the business scenario includes: because of positioning system 200
Third root because of determining module 280, for based on history root because and history alarm appearance simultaneously probability, and described go through
History alarm occur in the case where root because the history root because conditional probability, determine the history alarm corresponding because,
In, the history root because be before the history alarms the moment root that occurred because.
In one embodiment, the third root includes: because of determining module 280
Root is because of determination unit, if being minimum value for the first probability and the second probability, it is determined that the history root is because making
For the history alarm root because；
Wherein, first probability are as follows: in the case that history alarm occurs root because be history root because conditional probability；
Second probability are as follows: the history root because and the history alarm simultaneously appearance probability.
This specification embodiment is based on srvice instance in the first preset time period where the time of origin point of current alerts
At least one data dimension, determine the contextual data of current alerts, more alarm fields can be provided because of positioning for subsequent
Scape information improves root because of the accuracy of positioning；By using the contextual data of current alerts as root because of the input of location model, with
Current alerts corresponding is obtained because of conditional probability distribution, then is determined based on current alerts corresponding because of conditional probability distribution
Current alerts corresponding because by, because location model carries out root because of positioning, simplifying root because of positioning side using trained
The algorithm complexity of method, can provide in time when alarming and occurring causes the root of alarm because to achieve the purpose that stop loss in time.
Fig. 3 is the structural schematic diagram for the electronic equipment that one embodiment of this specification provides.Referring to FIG. 3, in hardware
Level, the electronic equipment include processor, optionally further comprising internal bus, network interface, memory.Wherein, memory can
It can include memory, such as high-speed random access memory (Random-AccessMemory, RAM), it is also possible to further include non-volatile
Property memory (non-volatile memory), for example, at least 1 magnetic disk storage etc..Certainly, which is also possible to wrap
Include hardware required for other business.
Processor, network interface and memory can be connected with each other by internal bus, which can be ISA
(Industry Standard Architecture, industry standard architecture) bus, PCI (Peripheral
Component Interconnect, Peripheral Component Interconnect standard) bus or EISA (Extended Industry Standard
Architecture, expanding the industrial standard structure) bus etc..The bus can be divided into address bus, data/address bus, control always
Line etc..Only to be indicated with a four-headed arrow in Fig. 3, it is not intended that an only bus or a type of convenient for indicating
Bus.
Memory, for storing program.Specifically, program may include program code, and said program code includes calculating
Machine operational order.Memory may include memory and nonvolatile memory, and provide instruction and data to processor.
Processor is from the then operation into memory of corresponding computer program is read in nonvolatile memory, in logical layer
The associated apparatus of resource increment object and resource object is formed on face.Processor executes the program that memory is stored, and specific
For performing the following operations:
At least one data of srvice instance in the first preset time period where time of origin point based on current alerts
Dimension determines the contextual data of the current alerts；
It is corresponding to obtain the current alerts using the contextual data of the current alerts as root because of the input of location model
Root because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because of instruction
It gets；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
This specification embodiment is based on srvice instance in the first preset time period where the time of origin point of current alerts
At least one data dimension, determine the contextual data of current alerts, more alarm fields can be provided because of positioning for subsequent
Scape information improves root because of the accuracy of positioning；By using the contextual data of current alerts as root because of the input of location model, with
Current alerts corresponding is obtained because of conditional probability distribution, then is determined based on current alerts corresponding because of conditional probability distribution
Current alerts corresponding because by, because location model carries out root because of positioning, simplifying root because of positioning side using trained
The algorithm complexity of method, can provide in time when alarming and occurring causes the root of alarm because to achieve the purpose that stop loss in time.
The root of business scenario disclosed in the above-mentioned embodiment illustrated in fig. 1 such as this specification can be applied to handle because of localization method
In device, or realized by processor.Processor may be a kind of IC chip, the processing capacity with signal.It is realizing
In the process, each step of the above method can pass through the integrated logic circuit of the hardware in processor or the instruction of software form
It completes.Above-mentioned processor can be general processor, including central processing unit (Central Processing Unit,
CPU), network processing unit (Network Processor, NP) etc.；It can also be digital signal processor (Digital Signal
Processor, DSP), it is specific integrated circuit (Application Specific Integrated Circuit, ASIC), existing
Field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device are divided
Vertical door or transistor logic, discrete hardware components.It may be implemented or execute this specification one or more embodiment
In disclosed each method, step and logic diagram.General processor can be microprocessor or the processor is also possible to
Any conventional processor etc..The step of method in conjunction with disclosed in this specification one or more embodiment, can directly embody
Execute completion for hardware decoding processor, or in decoding processor hardware and software module combination execute completion.Software
Module can be located at random access memory, flash memory, read-only memory, programmable read only memory or electrically erasable programmable storage
In the storage medium of this fields such as device, register maturation.The storage medium is located at memory, and processor reads the letter in memory
Breath, in conjunction with the step of its hardware completion above method.
The electronic equipment can also carry out the root of the business scenario of Fig. 2 because of the root of the business scenario of Fig. 1 performed by positioning system
Because of localization method, details are not described herein for this specification.
Certainly, other than software realization mode, other implementations are not precluded in the electronic equipment of this specification, such as
Logical device or the mode of software and hardware combining etc., that is to say, that the executing subject of following process flow is not limited to multiple
Logic unit is also possible to hardware or logical device.
This specification embodiment also provides a kind of computer readable storage medium, is stored on computer readable storage medium
Computer program, the computer program realize multiple processes of above-mentioned multiple embodiments of the method when being executed by processor, and can reach
To identical technical effect, to avoid repeating, which is not described herein again.Wherein, the computer readable storage medium, it is such as read-only
Memory (Read-Only Memory, abbreviation ROM), random access memory (Random Access Memory, abbreviation
RAM), magnetic or disk etc..
It should be understood by those skilled in the art that, the embodiment of this specification can provide as method, system or computer journey
Sequence product.Therefore, in terms of this specification can be used complete hardware embodiment, complete software embodiment or combine software and hardware
Embodiment form.Moreover, it wherein includes computer usable program code that this specification, which can be used in one or more,
The computer implemented in computer-usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of program product.
This specification is referring to the method, equipment (system) and computer program product according to this specification embodiment
Flowchart and/or the block diagram describes.It should be understood that can be realized by computer program instructions every in flowchart and/or the block diagram
The combination of process and/or box in one process and/or box and flowchart and/or the block diagram.It can provide these computers
Processor of the program instruction to general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices
To generate a machine, so that generating use by the instruction that computer or the processor of other programmable data processing devices execute
It is in realize the function of specifying in one or more flows of the flowchart and/or one or more blocks of the block diagram
System.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of system, the instruction system realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It is above-mentioned that specification specific embodiment is described.Other embodiments are within the scope of the appended claims.
In some cases, the movement recorded in detail in the claims or step can be executed according to the sequence being different from embodiment
And desired result still may be implemented.In addition, process depicted in the drawing not necessarily require the particular order shown or
Person's consecutive order is just able to achieve desired result.In some embodiments, multitasking and parallel processing are also possible
Or it may be advantageous.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including element
There is also other identical elements in process, method, commodity or equipment.
The above is only the embodiments of this specification, are not limited to this specification.For those skilled in the art
For, this specification can have various modifications and variations.All any modifications made within the spirit and principle of this specification,
Equivalent replacement, improvement etc., should be included within the scope of the claims of this specification.
Claims (10)
1. a kind of root of business scenario is because of localization method, comprising:
At least one data dimension of srvice instance in the first preset time period where time of origin point based on current alerts,
Determine the contextual data of the current alerts；
Using the contextual data of the current alerts as root because of the input of location model, to obtain the current alerts corresponding
Because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because trained
It arrives；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
2. the method as described in claim 1, described to be based on the current alerts corresponding because of conditional probability distribution, institute is determined
State corresponding of current alerts because, comprising:
Based on the prior probability of the current alerts scene, target root because prior probability, and in target root because of the case where occurring
Lower scene is the conditional probability of the current alerts scene, determines that the current alerts scene is the posteriority by target root because of generation
Probability, the target root because be corresponding of the current alerts because any one root in conditional probability distribution because；
Selected because at the current alerts corresponding because of the root in conditional probability distribution the maximum target root of posterior probability because
As corresponding of the current alerts because.
3. method according to claim 2, the prior probability based on the current alerts scene, target root because priori
Probability, and in the case where target root is because occurring, scene is the conditional probability of the current alerts scene, determines the current report
Alert scene is the posterior probability by target root because of generation, comprising:
Based on the prior probability of the current alerts scene, target root because prior probability, and in target root because of the case where occurring
Lower scene is the conditional probability of the current alerts scene, determines that the current alerts scene is by target by Bayes principle
Posterior probability of the root because of generation.
4. the method as described in claim 1, using the contextual data of the current alerts as root because of the input of location model,
Before obtaining the current alerts corresponding because of conditional probability distribution, comprising:
At least one data dimension based on srvice instance in the second preset time period where history alarm moment time of origin point
Degree determines the contextual data of the history alarm；
Contextual data and the history based on history alarm alarm corresponding because training described because of location model.
5. method as claimed in claim 4, corresponding in the contextual data alarmed based on the history and history alarm
Root because training described because of location model before, comprising:
Based within the unit time history root because frequency and the history root because weighted value, determine history alarm pair
The root answered because, wherein the history root because be the root that occurred before the history alarms the moment because.
6. method as claimed in claim 4, corresponding in the contextual data alarmed based on the history and history alarm
Root because training described because of location model before, comprising:
Based on history root because and history alarm simultaneously occur probability, and the history alarm occur in the case where root because described in
History root because conditional probability, determine the history alarm corresponding because, wherein the history root is because being in the history report
The root occurred before the alert moment because.
7. method as claimed in claim 6, the root of determination history alarm because, comprising:
If the first probability and the second probability are minimum value, it is determined that the history root because the root alarmed as the history because；
Wherein, first probability are as follows: in the case that history alarm occurs root because be history root because conditional probability；
Second probability are as follows: the history root because and the history alarm simultaneously appearance probability.
8. a kind of root of business scenario is because of positioning system, comprising:
First data determining module, it is real for business in the first preset time period where the time of origin point based on current alerts
At least one data dimension of example, determines the contextual data of the current alerts；
Input module, for using the contextual data of the current alerts as root because of the input of location model, to work as described in obtaining
Preceding corresponding of alarm is because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and right
The root answered is obtained because of training；
First determines described current because of determining module for being based on the current alerts corresponding because of conditional probability distribution
Alarm corresponding because.
9. a kind of electronic equipment, comprising: memory, processor and be stored on the memory and can transport on the processor
Capable computer program, the computer program realize following steps when being executed by the processor:
At least one data dimension of srvice instance in the first preset time period where time of origin point based on current alerts,
Determine the contextual data of the current alerts；
Using the contextual data of the current alerts as root because of the input of location model, to obtain the current alerts corresponding
Because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because trained
It arrives；
Based on corresponding of the current alerts because of conditional probability distribution, determine corresponding of the current alerts because.
10. a kind of computer readable storage medium, computer program, the meter are stored on the computer readable storage medium
Calculation machine program realizes following steps when being executed by processor:
At least one data dimension of srvice instance in the first preset time period where time of origin point based on current alerts,
Determine the contextual data of the current alerts；
Using the contextual data of the current alerts as root because of the input of location model, to obtain the current alerts corresponding
Because of conditional probability distribution, wherein the described contextual data alarmed by location model based on history and corresponding are because trained
It arrives；
Based on the current alerts corresponding because of conditional probability distribution, corresponding of the current alerts scene is determined.
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| CN201910383396.5A CN110222936B (en) | 2019-05-09 | 2019-05-09 | Root cause positioning method and system of business scene and electronic equipment |
| CN202310995880.XA CN117035452A (en) | 2019-05-09 | 2019-05-09 | Root cause positioning method and system of business scene and electronic equipment |
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| CN110222936B (en) | 2023-08-29 |
| CN117035452A (en) | 2023-11-10 |
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