CN114840212B - System optimization method, device, equipment and storage medium - Google Patents
System optimization method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to artificial intelligence and provides a system optimization method, device, equipment and storage medium. The method comprises the steps of obtaining a system problem of a system to be optimized according to a system maintenance request when the system maintenance request is received, obtaining a system technical document of the system to be optimized, obtaining user behavior data of the system to be optimized, extracting document key information in the system technical document, inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, matching a solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem, and optimizing the system to be optimized based on the solution to improve the optimization efficiency. Furthermore, the present invention also relates to blockchain techniques, which may be stored in the blockchain.
Description
Technical Field
The present invention relates to the field of artificial intelligence technologies, and in particular, to a system optimization method, apparatus, device, and storage medium.
Background
At present, the technical capability of software system developers is uneven, so that the system problems of blocking and the like frequently occur in the later stage of a partially developed software system, and the software system is difficult to dimension. When such systems are problematic, it is often necessary for the operation and maintenance user to find a suitable solution by analyzing and verifying the system problems one by one, resulting in inefficiency in optimizing the system and adverse to the system dimensions.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a system optimization method, apparatus, device, and storage medium that can improve system optimization efficiency.
In one aspect, the present invention proposes a system optimization method, including:
when a system maintenance request is received, acquiring a system problem of a system to be optimized according to the system maintenance request;
acquiring a system technical document of the system to be optimized, and acquiring user behavior data of the system to be optimized;
extracting document key information in the system technical document;
Inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized;
Matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem;
and carrying out optimization processing on the system to be optimized based on the solution.
According to a preferred embodiment of the present invention, the acquiring the system problem of the system to be optimized according to the system maintenance request includes:
positioning a request triggering interface of the system maintenance request;
identifying an interface prompt position in the request triggering interface based on a preset prompt box;
And acquiring information on the interface prompt position as the system problem.
According to a preferred embodiment of the present invention, before inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, the method further includes:
Acquiring a design document of a historical system from a preset website, and acquiring historical operation and maintenance problems of the historical system and the problem occurrence time of the historical operation and maintenance problems;
identifying a plurality of functional modules of the historian system from the design document;
Classifying the historical operation and maintenance problems to obtain module problems corresponding to each functional module;
calculating the problem frequency of the module problem in a preset period based on the problem occurrence time;
And constructing the pre-trained trend prediction model according to the functional modules, the preset time period, the module problems and the problem frequency.
According to a preferred embodiment of the present invention, the pre-trained trend prediction model includes a module prediction network of each functional module, the module prediction network includes a prediction graph of each module problem in the functional module, and the inputting the document key information and the user behavior data into the pre-trained trend prediction model, to obtain a system development trend of the system to be optimized includes:
identifying a module prediction network matched with the system to be optimized as a target prediction network based on the document key information;
identifying a prediction graph matched with the user behavior data from the target prediction network as a system trend graph;
Identifying the system input time of the system to be optimized according to the user behavior data;
acquiring a module problem from the system trend graph as a target problem, and acquiring a problem frequency corresponding to the system input time from the system trend graph as a target frequency;
And determining the target problem and the target frequency as the system development trend.
According to a preferred embodiment of the present invention, the extracting the document key information in the system technical document includes:
Extracting requirement module information from the system technical document, wherein the requirement module information comprises a plurality of vocabulary information;
acquiring module identification information of the plurality of functional modules from the design document;
calculating the information similarity of each piece of vocabulary information and the module identification information;
and if the information similarity is greater than a preset similarity threshold, determining the vocabulary information as the document key information.
According to a preferred embodiment of the present invention, the matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem includes:
Determining the target problem that the target frequency is larger than a preset frequency threshold as a problem to be processed;
the processing mode matched with the problem to be processed is obtained from the preset operation and maintenance shared library as a first mode, and the processing mode matched with the system problem is obtained from the preset operation and maintenance shared library as a second mode;
Detecting whether the first mode and the second mode conflict;
If the first mode and the second mode do not conflict, the first mode and the second mode are combined to serve as the solution.
According to a preferred embodiment of the present invention, the optimizing the system to be optimized based on the solution includes:
acquiring scheme code information corresponding to the solution;
and running the scheme code information to execute the optimization processing of the system to be optimized.
In another aspect, the present invention also proposes a system optimization apparatus, including:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a system problem of a system to be optimized according to a system maintenance request when the system maintenance request is received;
the acquisition unit is further used for acquiring a system technical document of the system to be optimized and acquiring user behavior data of the system to be optimized;
an extracting unit, configured to extract document key information in the system technical document;
the input unit is used for inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized;
The matching unit is used for matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problems;
And the optimizing unit is used for optimizing the system to be optimized based on the solution.
In another aspect, the present invention also proposes an electronic device, including:
A memory storing computer readable instructions, and
And a processor executing computer readable instructions stored in the memory to implement the system optimization method.
In another aspect, the present invention also proposes a computer readable storage medium having stored therein computer readable instructions that are executed by a processor in an electronic device to implement the system optimization method.
According to the technical scheme, the document key information in the system technical document is extracted, the system development trend can be predicted by utilizing the document key information, so that interference of the interference information in the system technical document to the system development trend is avoided, meanwhile, the pre-trained trend prediction model does not need to analyze the whole system technical document, the prediction efficiency of the system development trend can be improved, the system development trend of the system to be optimized can be accurately predicted by combining the document key information and the user behavior data, further, the solution can be matched from a preset operation and maintenance shared library by combining the system development trend and the system problem, and the system problem can be solved by optimizing the system to be optimized based on the solution. The invention can improve the optimization efficiency of the system to be optimized because the solutions do not need to be adapted one by one.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the system optimization method of the present invention.
FIG. 2 is a functional block diagram of a preferred embodiment of the system optimization device of the present invention.
Fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the present invention for implementing the system optimization method.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a flow chart of a preferred embodiment of the system optimization method of the present invention. The order of the steps in the flowchart may be changed and some steps may be omitted according to various needs.
The system optimization method can acquire and process related data based on artificial intelligence technology. Wherein artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) is the theory, method, technique, and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend, and expand human intelligence, sense the environment, acquire knowledge, and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
The system optimization method is applied to one or more electronic devices, wherein the electronic devices are devices capable of automatically performing numerical calculation and/or information processing according to preset or stored computer readable instructions, and the hardware of the electronic devices comprises, but is not limited to, microprocessors, application SPECIFIC INTEGRATED Circuits (ASICs), programmable gate arrays (Field-Programmable GATE ARRAY, FPGA), digital signal processors (DIGITAL SIGNAL processors, DSPs), embedded devices and the like.
The electronic device may be any electronic product that can interact with a user in a human-computer manner, such as a Personal computer, a tablet computer, a smart phone, a Personal digital assistant (Personal DIGITAL ASSISTANT, PDA), a game console, an interactive internet protocol television (Internet Protocol Television, IPTV), a smart wearable device, etc.
The electronic device may comprise a network device and/or a user device. Wherein the network device includes, but is not limited to, a single network electronic device, a group of electronic devices made up of multiple network electronic devices, or a Cloud based Cloud Computing (Cloud Computing) made up of a large number of hosts or network electronic devices.
The network in which the electronic device is located includes, but is not limited to, the internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (Virtual Private Network, VPN), and the like.
S10, when a system maintenance request is received, acquiring a system problem of a system to be optimized according to the system maintenance request.
In at least one embodiment of the present invention, the system maintenance request is a request that triggers generation when a user fails to perform an operation on the system to be optimized. The system maintenance request carries an interface identifier corresponding to the interface generated by the trigger request.
The system to be optimized refers to a system needing to be optimized.
The system problem refers to a problem generated when a user performs an operation on the system to be optimized, for example, the system problem may be a problem of blocking or the like.
In at least one embodiment of the present invention, the electronic device obtaining, according to the system maintenance request, a system problem of a system to be optimized includes:
positioning a request triggering interface of the system maintenance request;
identifying an interface prompt position in the request triggering interface based on a preset prompt box;
And acquiring information on the interface prompt position as the system problem.
The preset prompt box stores the system problems, and the preset prompt box can be a prompt box designed in advance by a research and development user of the system to be optimized.
The request triggering interface can be accurately positioned through the system maintenance request, and the interface prompt position can be rapidly positioned through the preset prompt box, so that the accuracy of the system problem is improved.
Specifically, the electronic device analyzes the message of the system maintenance request to obtain data information carried by the message, extracts the interface identifier from the data information, and determines an interface corresponding to the interface identifier as the request triggering interface.
Specifically, the electronic device captures the position of the preset prompt box in the request triggering interface as the interface prompt position.
S11, acquiring a system technical document of the system to be optimized, and acquiring user behavior data of the system to be optimized.
In at least one embodiment of the present invention, the system technical document refers to a development requirement document of the system to be optimized, and the system technical document includes information such as a functional module diagram of the system to be optimized and implementation codes of each module.
The user behavior data comprise information such as operation of a certain module in the system to be optimized by an operation user.
In at least one embodiment of the present invention, the electronic device obtains the system technology document from a document library based on a system identification of the system to be optimized.
In at least one embodiment of the present invention, the electronic device obtaining user behavior data of the system to be optimized includes:
acquiring a system log corresponding to the system to be optimized from a preset log library;
and extracting information corresponding to a preset behavior label from the system log to serve as the user behavior data.
The preset behavior label is used for indicating the operation behavior of the user.
S12, extracting document key information in the system technical document.
In at least one embodiment of the present invention, the document key information includes vocabulary information corresponding to a system module in the system to be optimized, and the document key information is stored in requirement module information in the system technology document.
In at least one embodiment of the present invention, the electronic device extracting document key information in the system technology document includes:
Extracting requirement module information from the system technical document, wherein the requirement module information comprises a plurality of vocabulary information;
acquiring module identification information of a plurality of functional modules from a design document;
calculating the information similarity of each piece of vocabulary information and the module identification information;
and if the information similarity is greater than a preset similarity threshold, determining the vocabulary information as the document key information.
The plurality of vocabulary information is used for indicating a system module in the system to be optimized.
The preset similarity threshold may be set according to actual requirements, for example, the preset similarity threshold may be 90%.
The design document refers to a research and development requirement document of a historical system, and the plurality of functional modules refer to historical system modules of the historical system.
By calculating the information similarity, the problem that the document key information cannot be accurately extracted due to the fact that the identifiers of the system modules are different can be avoided.
And S13, inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain the system development trend of the system to be optimized.
In at least one embodiment of the present invention, the pre-trained trend prediction model may be used to predict problems and problem frequencies that occur in a system module in the system to be optimized in a preset period.
In at least one embodiment of the present invention, before inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, the method further includes:
Acquiring a design document of a historical system from a preset website, and acquiring historical operation and maintenance problems of the historical system and the problem occurrence time of the historical operation and maintenance problems;
identifying a plurality of functional modules of the historian system from the design document;
Classifying the historical operation and maintenance problems to obtain module problems corresponding to each functional module;
calculating the problem frequency of the module problem in a preset period based on the problem occurrence time;
And constructing the pre-trained trend prediction model according to the functional modules, the preset time period, the module problems and the problem frequency.
Wherein, the preset website shares a plurality of research and development requirement documents of the system.
The historical operation and maintenance problem can refer to a large amount of BUG information appearing in the historical system, and the problem occurrence time refers to a time difference between the time when the historical operation and maintenance problem occurs and the time when the historical system is put into production.
For example, the plurality of functional modules include a module a, the module problem corresponding to the module a includes a problem 1, where the number of occurrences of the problem 1 is 200, the problem 1 has a problem occurrence time corresponding to 50 times of 1 month, the problem 1 has a problem occurrence time corresponding to 150 times of 2 months, the frequency of occurrence of the problem a in the 1 st month is 50, and the frequency of occurrence of the problem a in the 2 nd month is 150.
By the implementation mode, the frequency of the problem of each module in the plurality of functional modules can be accurately calculated, and therefore the trend prediction model can be accurately constructed.
In at least one embodiment of the present invention, the pre-trained trend prediction model includes a module prediction network of each functional module, the module prediction network includes a prediction graph of each module problem in the functional module, and the electronic device inputs the document key information and the user behavior data into the pre-trained trend prediction model, and obtaining the system development trend of the system to be optimized includes:
identifying a module prediction network matched with the system to be optimized as a target prediction network based on the document key information;
identifying a prediction graph matched with the user behavior data from the target prediction network as a system trend graph;
Identifying the system input time of the system to be optimized according to the user behavior data;
acquiring a module problem from the system trend graph as a target problem, and acquiring a problem frequency corresponding to the system input time from the system trend graph as a target frequency;
And determining the target problem and the target frequency as the system development trend.
The target prediction network refers to a module prediction network of a system module in the system to be optimized.
The system trend graph refers to a prediction graph corresponding to an operation module matched with the user behavior data, and if the operation module matched with the user behavior data comprises a plurality of module problems, the system trend graph comprises a plurality of prediction graphs.
By combining the document key information and the user behavior data, the target problem and the target frequency can be accurately identified from the pre-trained trend prediction model, and the accuracy of the system development trend is improved.
S14, matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem.
It is emphasized that the above solution may also be stored in a blockchain node in order to further guarantee privacy and security of the above solution.
In at least one embodiment of the present invention, the preset operation and maintenance shared library shares a plurality of operation and maintenance problems and corresponding problem solving codes, etc.
The solution refers to specific code information capable of solving the system problem.
In at least one embodiment of the present invention, the matching, by the electronic device, the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem includes:
Determining the target problem that the target frequency is larger than a preset frequency threshold as a problem to be processed;
the processing mode matched with the problem to be processed is obtained from the preset operation and maintenance shared library as a first mode, and the processing mode matched with the system problem is obtained from the preset operation and maintenance shared library as a second mode;
Detecting whether the first mode and the second mode conflict;
If the first mode and the second mode do not conflict, the first mode and the second mode are combined to serve as the solution.
The preset frequency threshold may be set according to a user requirement, for example, the preset frequency threshold may be 1000 times.
For example, the first mode is to set the value of the first index to be less than 50, and the second mode is to set the value of the second index to be more than 50, and then the first mode is determined to conflict with the second mode.
The problem that the system optimization is required to be performed can be determined by self-defining according to the user requirements by comparing the target frequency with the preset frequency threshold value, so that the problem can be avoided when a user operates in the follow-up mode, and the problem to be processed and the system problem can not be solved due to the fact that whether the first mode and the second mode conflict with each other or not can be detected, so that the accuracy of the system optimization is improved.
In other embodiments, if the first mode conflicts with the second mode, an alert message is generated.
And S15, optimizing the system to be optimized based on the solution.
In at least one embodiment of the present invention, the electronic device performing optimization processing on the system to be optimized based on the solution includes:
acquiring scheme code information corresponding to the solution;
and running the scheme code information to execute the optimization processing of the system to be optimized.
By the implementation mode, the scheme code information can be directly called to execute the optimization processing of the system to be optimized, so that the optimization efficiency of the system to be optimized is improved.
According to the technical scheme, the document key information in the system technical document is extracted, the system development trend can be predicted by utilizing the document key information, so that interference of the interference information in the system technical document to the system development trend is avoided, meanwhile, the pre-trained trend prediction model does not need to analyze the whole system technical document, the prediction efficiency of the system development trend can be improved, the system development trend of the system to be optimized can be accurately predicted by combining the document key information and the user behavior data, further, the solution can be matched from a preset operation and maintenance shared library by combining the system development trend and the system problem, and the system problem can be solved by optimizing the system to be optimized based on the solution. The invention can improve the optimization efficiency of the system to be optimized because the solutions do not need to be adapted one by one.
FIG. 2 is a functional block diagram of a preferred embodiment of the system optimization device of the present invention. The system optimization device 11 includes an acquisition unit 110, an extraction unit 111, an input unit 112, a matching unit 113, an optimization unit 114, an identification unit 115, a classification unit 116, a calculation unit 117, and a construction unit 118. The module/unit referred to herein is a series of computer readable instructions capable of being retrieved by the processor 13 and performing a fixed function and stored in the memory 12. In the present embodiment, the functions of the respective modules/units will be described in detail in the following embodiments.
When receiving a system maintenance request, the acquisition unit 110 acquires a system problem of a system to be optimized according to the system maintenance request.
In at least one embodiment of the present invention, the system maintenance request is a request that triggers generation when a user fails to perform an operation on the system to be optimized. The system maintenance request carries an interface identifier corresponding to the interface generated by the trigger request.
The system to be optimized refers to a system needing to be optimized.
The system problem refers to a problem generated when a user performs an operation on the system to be optimized, for example, the system problem may be a problem of blocking or the like.
In at least one embodiment of the present invention, the acquiring unit 110 acquires a system problem of a system to be optimized according to the system maintenance request, including:
positioning a request triggering interface of the system maintenance request;
identifying an interface prompt position in the request triggering interface based on a preset prompt box;
And acquiring information on the interface prompt position as the system problem.
The preset prompt box stores the system problems, and the preset prompt box can be a prompt box designed in advance by a research and development user of the system to be optimized.
The request triggering interface can be accurately positioned through the system maintenance request, and the interface prompt position can be rapidly positioned through the preset prompt box, so that the accuracy of the system problem is improved.
Specifically, the obtaining unit 110 analyzes the message of the system maintenance request to obtain data information carried by the message, extracts the interface identifier from the data information, and determines an interface corresponding to the interface identifier as the request triggering interface.
Specifically, the acquiring unit 110 captures the position of the preset prompt box in the request triggering interface as the interface prompt position.
The obtaining unit 110 obtains a system technical document of the system to be optimized, and obtains user behavior data of the system to be optimized.
In at least one embodiment of the present invention, the system technical document refers to a development requirement document of the system to be optimized, and the system technical document includes information such as a functional module diagram of the system to be optimized and implementation codes of each module.
The user behavior data comprise information such as operation of a certain module in the system to be optimized by an operation user.
In at least one embodiment of the present invention, the obtaining unit 110 obtains the system technical document from a document library based on a system identifier of the system to be optimized.
In at least one embodiment of the present invention, the acquiring unit 110 acquires user behavior data of the system to be optimized, including:
acquiring a system log corresponding to the system to be optimized from a preset log library;
and extracting information corresponding to a preset behavior label from the system log to serve as the user behavior data.
The preset behavior label is used for indicating the operation behavior of the user.
The extraction unit 111 extracts document key information in the system technology document.
In at least one embodiment of the present invention, the document key information includes vocabulary information corresponding to a system module in the system to be optimized, and the document key information is stored in requirement module information in the system technology document.
In at least one embodiment of the present invention, the extracting unit 111 extracts document key information in the system technical document includes:
Extracting requirement module information from the system technical document, wherein the requirement module information comprises a plurality of vocabulary information;
acquiring module identification information of a plurality of functional modules from a design document;
calculating the information similarity of each piece of vocabulary information and the module identification information;
and if the information similarity is greater than a preset similarity threshold, determining the vocabulary information as the document key information.
The plurality of vocabulary information is used for indicating a system module in the system to be optimized.
The preset similarity threshold may be set according to actual requirements, for example, the preset similarity threshold may be 90%.
The design document refers to a research and development requirement document of a historical system, and the plurality of functional modules refer to historical system modules of the historical system.
By calculating the information similarity, the problem that the document key information cannot be accurately extracted due to the fact that the identifiers of the system modules are different can be avoided.
The input unit 112 inputs the document key information and the user behavior data into a pre-trained trend prediction model, so as to obtain a system development trend of the system to be optimized.
In at least one embodiment of the present invention, the pre-trained trend prediction model may be used to predict problems and problem frequencies that occur in a system module in the system to be optimized in a preset period.
In at least one embodiment of the present invention, before inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, the obtaining unit 110 obtains a design document of a historical system from a preset website, and obtains a historical operation and maintenance problem of the historical system and a problem occurrence time of the historical operation and maintenance problem;
The identifying unit 115 identifies a plurality of functional modules of the history system from the design document;
The classifying unit 116 classifies the historical operation and maintenance problems to obtain module problems corresponding to each functional module;
The calculation unit 117 calculates a problem frequency in which the module problem occurs within a preset period based on the problem occurrence time;
The construction unit 118 constructs the pre-trained trend prediction model according to the plurality of functional modules, the preset time period, the plurality of module questions, and the frequency of the questions.
Wherein, the preset website shares a plurality of research and development requirement documents of the system.
The historical operation and maintenance problem can refer to a large amount of BUG information appearing in the historical system, and the problem occurrence time refers to a time difference between the time when the historical operation and maintenance problem occurs and the time when the historical system is put into production.
For example, the plurality of functional modules include a module a, the module problem corresponding to the module a includes a problem 1, where the number of occurrences of the problem 1 is 200, the problem 1 has a problem occurrence time corresponding to 50 times of 1 month, the problem 1 has a problem occurrence time corresponding to 150 times of 2 months, the frequency of occurrence of the problem a in the 1 st month is 50, and the frequency of occurrence of the problem a in the 2 nd month is 150.
By the implementation mode, the frequency of the problem of each module in the plurality of functional modules can be accurately calculated, and therefore the trend prediction model can be accurately constructed.
In at least one embodiment of the present invention, the pre-trained trend prediction model includes a module prediction network of each functional module, the module prediction network includes a prediction graph of each module problem in the functional module, and the input unit 112 inputs the document key information and the user behavior data into the pre-trained trend prediction model, and obtaining the system development trend of the system to be optimized includes:
identifying a module prediction network matched with the system to be optimized as a target prediction network based on the document key information;
identifying a prediction graph matched with the user behavior data from the target prediction network as a system trend graph;
Identifying the system input time of the system to be optimized according to the user behavior data;
acquiring a module problem from the system trend graph as a target problem, and acquiring a problem frequency corresponding to the system input time from the system trend graph as a target frequency;
And determining the target problem and the target frequency as the system development trend.
The target prediction network refers to a module prediction network of a system module in the system to be optimized.
The system trend graph refers to a prediction graph corresponding to an operation module matched with the user behavior data, and if the operation module matched with the user behavior data comprises a plurality of module problems, the system trend graph comprises a plurality of prediction graphs.
By combining the document key information and the user behavior data, the target problem and the target frequency can be accurately identified from the pre-trained trend prediction model, and the accuracy of the system development trend is improved.
The matching unit 113 matches the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem.
It is emphasized that the above solution may also be stored in a blockchain node in order to further guarantee privacy and security of the above solution.
In at least one embodiment of the present invention, the preset operation and maintenance shared library shares a plurality of operation and maintenance problems and corresponding problem solving codes, etc.
The solution refers to specific code information capable of solving the system problem.
In at least one embodiment of the present invention, the matching unit 113 matches the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem, including:
Determining the target problem that the target frequency is larger than a preset frequency threshold as a problem to be processed;
the processing mode matched with the problem to be processed is obtained from the preset operation and maintenance shared library as a first mode, and the processing mode matched with the system problem is obtained from the preset operation and maintenance shared library as a second mode;
Detecting whether the first mode and the second mode conflict;
If the first mode and the second mode do not conflict, the first mode and the second mode are combined to serve as the solution.
The preset frequency threshold may be set according to a user requirement, for example, the preset frequency threshold may be 1000 times.
For example, the first mode is to set the value of the first index to be less than 50, and the second mode is to set the value of the second index to be more than 50, and then the first mode is determined to conflict with the second mode.
The problem that the system optimization is required to be performed can be determined by self-defining according to the user requirements by comparing the target frequency with the preset frequency threshold value, so that the problem can be avoided when a user operates in the follow-up mode, and the problem to be processed and the system problem can not be solved due to the fact that whether the first mode and the second mode conflict with each other or not can be detected, so that the accuracy of the system optimization is improved.
In other embodiments, if the first mode conflicts with the second mode, an alert message is generated.
The optimization unit 114 performs optimization processing on the system to be optimized based on the solution.
In at least one embodiment of the present invention, the optimizing unit 114 performs an optimization process on the system to be optimized based on the solution, including:
acquiring scheme code information corresponding to the solution;
and running the scheme code information to execute the optimization processing of the system to be optimized.
By the implementation mode, the scheme code information can be directly called to execute the optimization processing of the system to be optimized, so that the optimization efficiency of the system to be optimized is improved.
According to the technical scheme, the document key information in the system technical document is extracted, the system development trend can be predicted by utilizing the document key information, so that interference of the interference information in the system technical document to the system development trend is avoided, meanwhile, the pre-trained trend prediction model does not need to analyze the whole system technical document, the prediction efficiency of the system development trend can be improved, the system development trend of the system to be optimized can be accurately predicted by combining the document key information and the user behavior data, further, the solution can be matched from a preset operation and maintenance shared library by combining the system development trend and the system problem, and the system problem can be solved by optimizing the system to be optimized based on the solution. The invention can improve the optimization efficiency of the system to be optimized because the solutions do not need to be adapted one by one.
Fig. 3 is a schematic structural diagram of an electronic device according to a preferred embodiment of the present invention for implementing the system optimization method.
In one embodiment of the invention, the electronic device 1 includes, but is not limited to, a memory 12, a processor 13, and computer readable instructions, such as a system optimization program, stored in the memory 12 and executable on the processor 13.
It will be appreciated by those skilled in the art that the schematic diagram is merely an example of the electronic device 1 and does not constitute a limitation of the electronic device 1, and may include more or less components than illustrated, or may combine certain components, or different components, e.g. the electronic device 1 may further include input-output devices, network access devices, buses, etc.
The Processor 13 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor 13 is an operation core and a control center of the electronic device 1, connects various parts of the entire electronic device 1 using various interfaces and lines, and executes an operating system of the electronic device 1 and various installed applications, program codes, etc.
Illustratively, the computer readable instructions may be partitioned into one or more modules/units that are stored in the memory 12 and executed by the processor 13 to complete the present invention. The one or more modules/units may be a series of computer readable instructions capable of performing a specific function, the computer readable instructions describing a process of executing the computer readable instructions in the electronic device 1. For example, the computer readable instructions may be divided into an acquisition unit 110, an extraction unit 111, an input unit 112, a matching unit 113, an optimization unit 114, an identification unit 115, a classification unit 116, a calculation unit 117, and a construction unit 118.
The memory 12 may be used to store the computer readable instructions and/or modules, and the processor 13 may implement various functions of the electronic device 1 by executing or executing the computer readable instructions and/or modules stored in the memory 12 and invoking data stored in the memory 12. The memory 12 may mainly include a storage program area that may store an operating system, application programs required for at least one function (such as a sound playing function, an image playing function, etc.), etc., and a storage data area that may store data created according to the use of the electronic device, etc. Memory 12 may include non-volatile and volatile memory such as a hard disk, memory, a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), at least one disk storage device, a flash memory device, or other storage device.
The memory 12 may be an external memory and/or an internal memory of the electronic device 1. Further, the memory 12 may be a physical memory, such as a memory bank, a TF card (Trans-FLASH CARD), or the like.
The integrated modules/units of the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the present invention may also be implemented by implementing all or part of the processes in the methods of the embodiments described above, by instructing the associated hardware by means of computer readable instructions, which may be stored in a computer readable storage medium, the computer readable instructions, when executed by a processor, implementing the steps of the respective method embodiments described above.
Wherein the computer readable instructions comprise computer readable instruction code which may be in the form of source code, object code, executable files, or in some intermediate form, etc. The computer readable medium may include any entity or device capable of carrying the computer readable instruction code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory).
The blockchain is a novel application mode of computer technologies such as distributed system optimization, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The blockchain (Blockchain), essentially a de-centralized database, is a string of data blocks that are generated in association using cryptographic methods, each of which contains information from a batch of network transactions for verifying the validity (anti-counterfeit) of its information and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
In connection with fig. 1, the memory 12 in the electronic device 1 stores computer readable instructions for implementing a system optimization method, the processor 13 being executable to implement:
when a system maintenance request is received, acquiring a system problem of a system to be optimized according to the system maintenance request;
acquiring a system technical document of the system to be optimized, and acquiring user behavior data of the system to be optimized;
extracting document key information in the system technical document;
Inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized;
Matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem;
and carrying out optimization processing on the system to be optimized based on the solution.
In particular, the specific implementation method of the processor 13 on the computer readable instructions may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.
In the several embodiments provided in the present invention, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The computer readable storage medium has stored thereon computer readable instructions, wherein the computer readable instructions when executed by the processor 13 are configured to implement the steps of:
when a system maintenance request is received, acquiring a system problem of a system to be optimized according to the system maintenance request;
acquiring a system technical document of the system to be optimized, and acquiring user behavior data of the system to be optimized;
extracting document key information in the system technical document;
Inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized;
Matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem;
and carrying out optimization processing on the system to be optimized based on the solution.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
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. Any reference signs in the claims shall not be construed as limiting the claim concerned.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. The units or means may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (8)
1. A system optimization method, the system optimization method comprising:
when a system maintenance request is received, acquiring a system problem of a system to be optimized according to the system maintenance request;
acquiring a system technical document of the system to be optimized, and acquiring user behavior data of the system to be optimized;
extracting document key information in the system technical document;
Inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, wherein the pre-trained trend prediction model comprises a module prediction network of each functional module, the module prediction network comprises a prediction graph of each module problem in the functional module, the document key information and the user behavior data are input into the pre-trained trend prediction model to obtain the system development trend of the system to be optimized, the method comprises the steps of identifying the module prediction network matched with the system to be optimized based on the document key information as a target prediction network, identifying the prediction graph matched with the user behavior data from the target prediction network as a system trend graph, identifying the system input time of the system to be optimized according to the user behavior data, obtaining module problems from the system trend graph as target problems, and obtaining the problem frequency corresponding to the system input time from the system trend graph as target frequency, and determining the target problems and the target frequency as the system development trend;
Matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem;
Optimizing the system to be optimized based on the solution;
Before inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain the system development trend of the system to be optimized, the method further comprises the following steps:
Acquiring a design document of a historical system from a preset website, and acquiring historical operation and maintenance problems of the historical system and the problem occurrence time of the historical operation and maintenance problems;
identifying a plurality of functional modules of the historian system from the design document;
Classifying the historical operation and maintenance problems to obtain module problems corresponding to each functional module;
calculating the problem frequency of the module problem in a preset period based on the problem occurrence time;
And constructing the pre-trained trend prediction model according to the functional modules, the preset time period, the module problems and the problem frequency.
2. The system optimization method of claim 1, wherein the acquiring the system problem of the system to be optimized according to the system maintenance request comprises:
positioning a request triggering interface of the system maintenance request;
identifying an interface prompt position in the request triggering interface based on a preset prompt box;
And acquiring information on the interface prompt position as the system problem.
3. The system optimization method of claim 1, wherein the extracting document key information in the system technology document comprises:
Extracting requirement module information from the system technical document, wherein the requirement module information comprises a plurality of vocabulary information;
acquiring module identification information of the plurality of functional modules from the design document;
calculating the information similarity of each piece of vocabulary information and the module identification information;
and if the information similarity is greater than a preset similarity threshold, determining the vocabulary information as the document key information.
4. The system optimization method according to claim 1, wherein the matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problem comprises:
Determining the target problem that the target frequency is larger than a preset frequency threshold as a problem to be processed;
the processing mode matched with the problem to be processed is obtained from the preset operation and maintenance shared library as a first mode, and the processing mode matched with the system problem is obtained from the preset operation and maintenance shared library as a second mode;
Detecting whether the first mode and the second mode conflict;
If the first mode and the second mode do not conflict, the first mode and the second mode are combined to serve as the solution.
5. The system optimization method of claim 1, wherein the optimizing the system to be optimized based on the solution comprises:
acquiring scheme code information corresponding to the solution;
and running the scheme code information to execute the optimization processing of the system to be optimized.
6. A system optimization device, characterized in that the system optimization device comprises:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a system problem of a system to be optimized according to a system maintenance request when the system maintenance request is received;
the acquisition unit is further used for acquiring a system technical document of the system to be optimized and acquiring user behavior data of the system to be optimized;
an extracting unit, configured to extract document key information in the system technical document;
The input unit is used for inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain a system development trend of the system to be optimized, wherein the pre-trained trend prediction model comprises a module prediction network of each functional module, the module prediction network comprises a prediction graph of each module problem in the functional module, the document key information and the user behavior data are input into the pre-trained trend prediction model to obtain the system development trend of the system to be optimized, the module prediction network matched with the system to be optimized is identified based on the document key information and used as a target prediction network, the prediction graph matched with the user behavior data is identified from the target prediction network and used as a system trend graph, the system input time of the system to be optimized is identified according to the user behavior data, the module problem is obtained from the system trend graph and used as a target problem, and the problem frequency corresponding to the system input time is obtained from the system trend graph and used as a target frequency;
The matching unit is used for matching the solution of the system to be optimized from a preset operation and maintenance shared library based on the system development trend and the system problems;
The optimizing unit is used for optimizing the system to be optimized based on the solution;
before inputting the document key information and the user behavior data into a pre-trained trend prediction model to obtain the system development trend of the system to be optimized, the device further comprises:
the acquisition unit is also used for acquiring a design document of the history system from a preset website and acquiring the history operation and maintenance problems of the history system and the problem occurrence time of the history operation and maintenance problems;
an identifying unit for identifying a plurality of functional modules of the history system from the design document;
The classifying unit is used for classifying the historical operation and maintenance problems to obtain module problems corresponding to each functional module;
a calculating unit, configured to calculate, based on the problem occurrence time, a problem frequency of occurrence of the module problem within a preset period;
The construction unit is used for constructing the pre-trained trend prediction model according to the functional modules, the preset time period, the module problems and the problem frequency.
7. An electronic device, the electronic device comprising:
a memory storing computer readable instructions, and
A processor executing computer readable instructions stored in the memory to implement the system optimization method of any one of claims 1-5.
8. A computer readable storage medium having stored therein computer readable instructions for execution by a processor in an electronic device to implement the system optimization method of any one of claims 1-5.
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| CN111401042A (en) * | 2020-03-26 | 2020-07-10 | 支付宝(杭州)信息技术有限公司 | Method and system for training text key content extraction model |
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| CN105392154A (en) * | 2014-09-05 | 2016-03-09 | 中兴通讯股份有限公司 | Resource occupation prediction method and system |
| CN111401042A (en) * | 2020-03-26 | 2020-07-10 | 支付宝(杭州)信息技术有限公司 | Method and system for training text key content extraction model |
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