CN112990466A - Redundancy rule detection method and device and server - Google Patents
Redundancy rule detection method and device and server Download PDFInfo
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- CN112990466A CN112990466A CN202110352130.1A CN202110352130A CN112990466A CN 112990466 A CN112990466 A CN 112990466A CN 202110352130 A CN202110352130 A CN 202110352130A CN 112990466 A CN112990466 A CN 112990466A
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Abstract
The application is applicable to the field of artificial intelligence, and particularly relates to a redundancy detection method, a redundancy detection device and a server, wherein the method comprises the following steps: acquiring a rule list, wherein the rule list comprises at least one rule file; analyzing a rule file in the rule list; and calculating the redundancy degree of each rule file according to a preset redundancy rule file. Therefore, in the embodiment of the application, the preset redundant rule file is generated by performing repeatability detection and logic detection on the rule files in the rule list, and the redundancy degree of each rule file in the rule list is calculated according to the redundant rule file, so that the effect of automatically detecting the redundant rule is achieved without manual detection.
Description
Technical Field
The application belongs to the technical field of artificial intelligence, and particularly relates to a redundancy rule detection method, a redundancy rule detection device and redundancy rule detection equipment.
Background
The rule engine is a branch of artificial intelligence, and is widely applied to an expert knowledge system, and the expert system converts expert knowledge into rules by an expert and adds the rules to a rule base. In the later maintenance of the system, the system needs to be maintained by an expert continuously adding new rules. With the continuous expansion of the rule base, the expert system often generates a large number of redundant rules, and the redundant rules can not be detected in a manual mode in many times.
Disclosure of Invention
The embodiment of the application provides a method, a device and a device for detecting a redundancy rule, and can solve the problem that a redundancy rule file can be generated only by manual detection in the prior art.
In a first aspect, an embodiment of the present application provides a method, including:
acquiring a rule list, wherein the rule list comprises at least one rule file;
analyzing a rule file in the rule list;
and calculating the redundancy degree of each rule file according to a preset redundancy rule file.
In a possible implementation manner of the first aspect, before calculating the redundancy degree of each rule file according to a preset redundancy rule file, the method further includes:
and generating the preset redundant rule file.
In a possible implementation manner of the first aspect, generating the preset redundancy rule file includes:
carrying out repeatability detection on the rule files in the rule list to obtain candidate redundant rule files;
and logically detecting the candidate redundancy rule file to obtain the preset redundancy rule file.
In a possible implementation manner of the first aspect, the rule file includes a rule name, an execution condition, and execution content;
performing repeatability detection on the rule files in the rule list to obtain candidate redundant rule files, wherein the method comprises the following steps:
extracting a rule name in the rule file;
performing first similarity calculation between the rule names to obtain first similarity;
extracting the execution conditions in the rule file;
performing second similarity calculation on the execution contents to obtain second similarity;
screening out rule files corresponding to the condition that the first similarity is greater than a first similarity threshold and the second similarity is greater than a second similarity threshold at the same time as a target rule file;
extracting the execution content in the target rule file;
performing third similarity calculation on the execution content to obtain a third similarity;
and determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
In a possible implementation manner of the first aspect, after performing repeatability detection on the rule file in the rule list to obtain a candidate redundant rule file, the method further includes:
and merging the candidate redundant rule files to obtain an abnormal rule file.
In a second aspect, an embodiment of the present application provides a redundancy rule detection apparatus, including:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a rule list, and the rule list comprises at least one rule file;
the analysis module is used for analyzing the rule files in the rule list;
and the calculating module is used for calculating the redundancy degree of each rule file according to a preset redundancy rule file.
In one possible implementation manner of the second aspect, the apparatus includes:
and the generating module is used for generating the preset redundant rule file.
In a possible implementation manner of the second aspect, the generating module includes:
the repeatability detection unit is used for carrying out repeatability detection on the rule files in the rule list to obtain candidate redundancy rule files;
and the logical detection unit is used for logically detecting the candidate redundancy rule file to obtain the preset redundancy rule file.
In one possible implementation manner of the second aspect, the rule file includes a rule name, an execution condition, and execution content;
the reproducibility detecting unit includes:
the first extraction subunit is used for extracting the rule name in the rule file;
the first calculation unit is used for calculating the first similarity between the rule names to obtain the first similarity;
the second extraction subunit is used for extracting the execution conditions in the rule file;
the second calculating subunit is configured to perform second similarity calculation on the execution contents to obtain a second similarity;
the screening subunit is used for screening out the rule files corresponding to the condition that the first similarity is greater than the first similarity threshold and the second similarity is greater than the second similarity threshold at the same time as the target rule file;
the third extraction subunit is used for extracting the execution content in the target rule file;
the third calculation subunit is used for performing third similarity calculation on the execution content to obtain a third similarity;
and the determining unit is used for determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
In one possible implementation manner of the second aspect, the repeatability detection unit includes:
and the rechecking subunit is used for merging the candidate redundant rule files to obtain an abnormal rule file.
In a third aspect, an embodiment of the present application provides a server, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the computer program, when executed by the processor, implements the method of the first aspect.
In a fourth aspect, the present application provides a readable storage medium, and the computer program when executed by a processor implements the method as described in the first aspect.
Compared with the prior art, the embodiment of the application has the advantages that:
in the embodiment of the application, the preset redundant rule file is generated by performing repeatability detection and logic detection on the rule files in the rule list, and the redundancy degree of each rule file in the rule list is calculated according to the redundant rule file, so that the effect of automatically detecting the redundant rule is achieved without manual detection.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart of a redundancy rule detection method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a redundancy rule detection apparatus according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to" determining "or" in response to detecting ". Similarly, the phrase "if it is determined" or "if [ a described execution condition or event ] is detected" may be interpreted, depending on the context, to mean "upon determining" or "in response to determining" or "upon detecting [ a described execution condition or event ]" or "in response to detecting [ a described execution condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless expressly specified otherwise.
In order to further understand the technical problem of the present application, the following further elaboration on the technical problem is made: under the prior art scheme, all rule updates of an expert system need to be regularly updated through field experts, an effective method for editing the rules of the expert system is lacked in the updating process, two methods exist in the current rule updating mode, one method is a document format only enabling business experts to learn a rule engine, and then the rules are automatically converted into rule languages. There is also a way for the expert to post-apply the rules for conversion by the developer. This results in a large number of redundant rules for the patented system that are far from meeting the needs of the prior art by relying only on manual detection.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
Referring to fig. 1, a flow of a redundancy rule detection method provided in the embodiment of the present application is schematically illustrated, where the method is applied to a server, where the server may be a computing device such as a cloud server, and the method includes the following steps:
and step S101, acquiring a rule list.
Wherein the rule list comprises at least one rule file.
It will be appreciated that the rule list may be obtained directly from an expert repository.
And S102, analyzing the rule file in the rule list.
The rule file is composed of three parts, namely rules (rule name), while (execution condition) and then (execution content).
And step S103, calculating the redundancy degree of each rule file according to the preset redundancy rule file.
Specifically, the calculation method for calculating the redundancy degree of each rule file according to the preset redundancy rule file may be a similarity calculation method, such as an edit distance, a hamming distance, a euclidean distance, or a cosine similarity.
Preferably, before calculating the redundancy degree of each rule file according to the preset redundancy rule file, the method further includes:
and generating a preset redundancy rule file.
Illustratively, generating a preset redundancy rule file includes:
firstly, carrying out repeatability detection on the rule files in the rule list to obtain candidate redundant rule files.
In specific application, the method for detecting the repeatability of the rule files in the rule list to obtain the candidate redundant rule files comprises the following steps:
1. and extracting the rule name in the rule file.
2. And performing first similarity calculation on the rule names to obtain first similarity.
The first similarity calculation may be an edit distance, a hamming distance, a euclidean distance, or a cosine similarity.
3. The execution conditions in the rule file are extracted.
4. And performing second similarity calculation on the executed contents to obtain second similarity.
The second similarity calculation may be an edit distance, a hamming distance, a euclidean distance, or a cosine similarity.
5. And screening out the rule files corresponding to the condition that the first similarity is greater than the first similarity threshold and the second similarity is greater than the second similarity threshold at the same time as the target rule file.
By way of example and not limitation, the first similarity threshold may be 80% and the second similarity threshold may be 80%.
6. And extracting the execution content in the target rule file.
7. And performing third similarity calculation on the executed content to obtain a third similarity.
The third similarity calculation may be an edit distance, a hamming distance, a euclidean distance, or a cosine similarity.
8. And determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
Preferably, after performing the repeatability detection on the rule file in the rule list to obtain the candidate redundant rule file, the method further includes:
and merging the candidate redundant rule files to obtain an abnormal rule file.
It will be appreciated that a manual review may follow from the exception rule file.
And secondly, logically detecting the candidate redundancy rule file to obtain a preset redundancy rule file.
In the process of logic detection, the conditional logic judgment symbols of the candidate redundancy rule file are analyzed item by item, and if the symbols are opposite, the rule has a logic error, and the candidate redundancy rule file is determined as the preset redundancy rule file.
In the embodiment of the application, the preset redundant rule file is generated by performing repeatability detection and logic detection on the rule files in the rule list, and the redundancy degree of each rule file in the rule list is calculated according to the redundant rule file, so that the effect of automatically detecting the redundant rule is achieved without manual detection.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 2 shows a block diagram of a redundancy rule detection apparatus provided in the embodiment of the present application, corresponding to a redundancy detection method described in the above embodiment, and only the relevant parts of the embodiment of the present application are shown for convenience of description.
Referring to fig. 2, the apparatus includes:
an obtaining module 21, configured to obtain a rule list, where the rule list includes at least one rule file;
the analysis module 22 is used for analyzing the rule files in the rule list;
and the calculating module 23 is configured to calculate the redundancy degree of each rule file according to a preset redundancy rule file.
In one possible implementation manner of the second aspect, the apparatus includes:
and the generating module is used for generating the preset redundant rule file.
In a possible implementation manner of the second aspect, the generating module includes:
the repeatability detection unit is used for carrying out repeatability detection on the rule files in the rule list to obtain candidate redundancy rule files;
and the logical detection unit is used for logically detecting the candidate redundancy rule file to obtain the preset redundancy rule file.
In one possible implementation manner of the second aspect, the rule file includes a rule name, an execution condition, and execution content;
the reproducibility detecting unit includes:
the first extraction subunit is used for extracting the rule name in the rule file;
the first calculation unit is used for calculating the first similarity between the rule names to obtain the first similarity;
the second extraction subunit is used for extracting the execution conditions in the rule file;
the second calculating subunit is configured to perform second similarity calculation on the execution contents to obtain a second similarity;
the screening subunit is used for screening out the rule files corresponding to the condition that the first similarity is greater than the first similarity threshold and the second similarity is greater than the second similarity threshold at the same time as the target rule file;
the third extraction subunit is used for extracting the execution content in the target rule file;
the third calculation subunit is used for performing third similarity calculation on the execution content to obtain a third similarity;
and the determining unit is used for determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
In one possible implementation manner of the second aspect, the repeatability detection unit includes:
and the rechecking subunit is used for merging the candidate redundant rule files to obtain an abnormal rule file.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
Fig. 3 is a schematic structural diagram of a server according to an embodiment of the present application. As shown in fig. 3, the server 3 of this embodiment includes: at least one processor 30, a memory 31 and a computer program 32 stored in the memory 31 and executable on the at least one processor 30, the processor 30 implementing the steps of any of the various method embodiments described above when executing the computer program 32.
The server 3 may be a computing device such as a cloud server. The server may include, but is not limited to, a processor 30, a memory 31. Those skilled in the art will appreciate that fig. 3 is merely an example of the server 3, and does not constitute a limitation of the server 3, and may include more or less components than those shown, or combine some components, or different components, such as input and output devices, network access devices, etc.
The Processor 30 may be a Central Processing Unit (CPU), and the Processor 30 may be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 31 may in some embodiments be an internal storage unit of the server 3, such as a hard disk or a memory of the server 3. The memory 31 may also be an external storage device of the server 3 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the server 3. Further, the memory 31 may also include both an internal storage unit and an external storage device of the server 3. The memory 31 is used for storing an operating system, an application program, a BootLoader (BootLoader), data, and other programs, such as program codes of the computer program. The memory 31 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific rule names of the functional units and modules are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The embodiment of the present application further provides a readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps that can be implemented in the above method embodiments.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting 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; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A method for redundant rule detection, the method comprising:
acquiring a rule list, wherein the rule list comprises at least one rule file;
analyzing a rule file in the rule list;
and calculating the redundancy degree of each rule file according to a preset redundancy rule file.
2. The method for detecting redundant rules according to claim 1, wherein before calculating the redundancy level of each of the rule files according to the preset redundant rule file, the method further comprises:
and generating the preset redundant rule file.
3. The method of claim 2, wherein generating the preset redundancy rule file comprises:
carrying out repeatability detection on the rule files in the rule list to obtain candidate redundant rule files;
and logically detecting the candidate redundancy rule file to obtain the preset redundancy rule file.
4. The redundant rule detection method according to claim 3, wherein the rule file includes a rule name, an execution condition, and an execution content;
performing repeatability detection on the rule files in the rule list to obtain candidate redundant rule files, wherein the method comprises the following steps:
extracting a rule name in the rule file;
performing first similarity calculation between the rule names to obtain first similarity;
extracting the execution conditions in the rule file;
performing second similarity calculation on the execution contents to obtain second similarity;
screening out rule files corresponding to the condition that the first similarity is greater than a first similarity threshold and the second similarity is greater than a second similarity threshold at the same time as a target rule file;
extracting the execution content in the target rule file;
performing third similarity calculation on the execution content to obtain a third similarity;
and determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
5. The method according to claim 3 or 4, wherein after performing the repetitive detection on the rule files in the rule list to obtain the candidate redundant rule file, the method further comprises:
and merging the candidate redundant rule files to obtain an abnormal rule file.
6. A redundant rule detecting apparatus, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a rule list, and the rule list comprises at least one rule file;
the analysis module is used for analyzing the rule files in the rule list;
and the calculating module is used for calculating the redundancy degree of each rule file according to a preset redundancy rule file.
7. The redundant rule detection apparatus of claim 6, wherein the apparatus comprises:
and the generating module is used for generating the preset redundant rule file.
8. The redundant rule detection apparatus of claim 7 wherein the generation module comprises:
the repeatability detection unit is used for carrying out repeatability detection on the rule files in the rule list to obtain candidate redundancy rule files;
and the logical detection unit is used for logically detecting the candidate redundancy rule file to obtain the preset redundancy rule file.
9. The redundant rule detection apparatus of claim 8 wherein the rule file includes a rule name, an execution condition, and an execution content;
the reproducibility detecting unit includes:
the first extraction subunit is used for extracting the rule name in the rule file;
the first calculation unit is used for calculating the first similarity between the rule names to obtain the first similarity;
the second extraction subunit is used for extracting the execution conditions in the rule file;
the second calculating subunit is configured to perform second similarity calculation on the execution contents to obtain a second similarity;
the screening subunit is used for screening out the rule files corresponding to the condition that the first similarity is greater than the first similarity threshold and the second similarity is greater than the second similarity threshold at the same time as the target rule file;
the third extraction subunit is used for extracting the execution content in the target rule file;
the third calculation subunit is used for performing third similarity calculation on the execution content to obtain a third similarity;
and the determining unit is used for determining the target rule file meeting the condition that the third similarity is greater than the third similarity threshold value as a candidate redundancy rule file.
10. A server comprising a memory, a processor and a computer program stored in the memory and running on the processor, wherein the computer program, when executed by the processor, implements the method of any of claims 1 to 4.
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| CN116756004A (en) * | 2023-05-29 | 2023-09-15 | 成都赛力斯科技有限公司 | Rule set generation method and device for static inspection |
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| CN106161743A (en) * | 2015-04-03 | 2016-11-23 | 腾讯科技（深圳）有限公司 | A kind of method for processing media resource, device and terminal |
| CN107329946A (en) * | 2016-04-29 | 2017-11-07 | 阿里巴巴集团控股有限公司 | The computational methods and device of similarity |
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| CN116756004A (en) * | 2023-05-29 | 2023-09-15 | 成都赛力斯科技有限公司 | Rule set generation method and device for static inspection |
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