CN111147375A - Network operation method, device, computer equipment and medium - Google Patents
Network operation method, device, computer equipment and medium Download PDFInfo
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- CN111147375A CN111147375A CN201911411125.2A CN201911411125A CN111147375A CN 111147375 A CN111147375 A CN 111147375A CN 201911411125 A CN201911411125 A CN 201911411125A CN 111147375 A CN111147375 A CN 111147375A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/02—Topology update or discovery
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/302—Route determination based on requested QoS
- H04L45/306—Route determination based on the nature of the carried application
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Abstract
The invention discloses a network operation method, a network operation device, computer equipment and a medium, wherein the method comprises the following steps: acquiring a task processing request input by a user; the task processing request carries a task execution condition; according to the task execution condition, searching a task processing flow corresponding to the task processing request in the established knowledge graph; displaying the searched task processing flow to obtain a selection instruction aiming at the task processing flow; and performing network operation according to the target task processing flow corresponding to the selection instruction. According to the method and the device, the executed task processing flow matched with the task execution condition is obtained in the knowledge graph through the task execution condition and is displayed to the user, so that the user can quickly determine a target task processing flow to perform network operation in the found task processing flow, the processing time of the user is saved, and the processing efficiency of the user on the task is improved.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a network operation method, apparatus, computer device, and medium.
Background
With the development of science and technology, more and more tasks need to be processed through the internet, and one task requirement may include a plurality of processing steps, so that in order to facilitate the processing operation of a user on the task, the processing steps corresponding to the task are all transferred to the internet, so that the user processes the task according to the steps embodied in the internet.
Generally, in the process of processing a task, a user needs to fully understand the task (including a use environment of the task, a purpose of the task, a processing flow of the task, and the like), and find a corresponding operation in the internet according to the understood situation, but the process of determining the operation of the task consumes a lot of time of the user, and the processing efficiency is low.
Disclosure of Invention
In view of this, an object of the present application is to provide a network operation method, an apparatus, a computer device, and a medium, so as to solve the problem in the prior art how to improve the processing efficiency of a user on a task.
In a first aspect, an embodiment of the present application provides a network operation method, including:
acquiring a task processing request input by a user; the task processing request carries a task execution condition;
according to the task execution condition, searching a task processing flow corresponding to the task processing request in the established knowledge graph;
displaying the searched task processing flow to obtain a selection instruction aiming at the task processing flow;
and performing network operation according to the target task processing flow corresponding to the selection instruction.
Optionally, if the task processing request carries requirement information for representing optimal efficiency, finding a task processing flow corresponding to the task processing request in the constructed knowledge graph according to the task execution condition, including:
and searching a task processing flow corresponding to the task processing request from the established knowledge graph by adopting a shortest path searching method according to the task execution condition.
Optionally, if the task processing request carries demand information for characterizing optimal return, finding a task processing flow corresponding to the task processing request in the constructed knowledge graph according to the task execution condition, where the task processing flow includes:
and searching the task processing flow corresponding to the task processing request from the constructed knowledge graph according to the task execution condition and the processing result evaluation value corresponding to each task processing flow.
Optionally, displaying the searched task processing flow to obtain a selection instruction for the task processing flow, where the method includes:
and displaying the searched task processing flow in the form of the task processing flow in the knowledge graph so as to obtain a selection instruction aiming at the task processing flow.
Optionally, the displaying the searched task processing flow in the form of the task processing flow in the knowledge graph to obtain a selection instruction for the task processing flow includes:
and displaying the searched task processing flow and the use information corresponding to each node in the searched task processing flow in a form in the knowledge graph to acquire a selection instruction aiming at the task processing flow.
Optionally, the task execution condition includes any one or more of the following:
the task management system comprises use environment information of the task, execution destination information of the task and executive person identity information of the task.
In a second aspect, an embodiment of the present application provides a network operating apparatus, including:
the acquisition module is used for acquiring a task processing request input by a user; the task processing request carries a task execution condition;
the searching module is used for searching a task processing flow corresponding to the task processing request in the established knowledge graph according to the task execution condition;
the display module is used for displaying the searched task processing flow so as to obtain a selection instruction aiming at the task processing flow;
and the operation module is used for performing network operation according to the target task processing flow corresponding to the selection instruction.
Optionally, if the task processing request carries the requirement information for representing the optimal efficiency, the searching module includes:
and the shortest path searching unit is used for searching the task processing flow corresponding to the task processing request from the established knowledge graph by adopting a shortest path searching method according to the task execution condition.
In a third aspect, an embodiment of the present application provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, performs the steps of the method described above.
The network operation method includes the steps that firstly, a task processing request input by a user is obtained; the task processing request carries a task execution condition; secondly, according to the task execution condition, searching a task processing flow corresponding to the task processing request in the established knowledge graph; thirdly, displaying the searched task processing flow to obtain a selection instruction aiming at the task processing flow; and finally, performing network operation according to the target task processing flow corresponding to the selection instruction.
In the prior art, when a user processes a task, the user needs to deeply understand the task, and understand a use environment, a task purpose, a task processing flow and the like corresponding to the task, but the process of understanding the task needs the user to continuously talk with other staff, but the talk process needs to consume a large amount of time of the user, and the work efficiency of the user is reduced. In the method, the executed task processing flow matched with the task execution condition is obtained in the knowledge graph through the task execution condition and displayed to the user, so that the user determines a target task processing flow to perform network operation in the found task processing flow, the user does not need to determine the task processing flow through continuous conversation with other users when the user executes the task, the processing time of the user is saved, and the task processing efficiency of the user is improved.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic flowchart of a network operation method according to an embodiment of the present application;
FIG. 2 is a schematic illustration of a knowledge-graph provided by an embodiment of the present application;
fig. 3 is a schematic structural diagram of a network operating device according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a computer device 400 according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In the prior art, when a user processes a task, the user needs to deeply understand the task, and understand a use environment, a task purpose, a task processing flow and the like corresponding to the task, but the process of understanding the task needs the user to continuously talk with other staff, but the talk process needs to consume a large amount of time of the user, and the work efficiency of the user is reduced.
Based on the above problem, as shown in fig. 1, the present application provides a network operation method, including:
s101, acquiring a task processing request input by a user; the task processing request carries a task execution condition;
s102, according to the task execution condition, searching a task processing flow corresponding to the task processing request in the established knowledge graph;
s103, displaying the searched task processing flow to obtain a selection instruction aiming at the task processing flow;
and S104, performing network operation according to the target task processing flow corresponding to the selection instruction.
In the step S101, the task processing request may be a trigger condition for enabling the server to start processing the task corresponding to the task processing request, and the task processing request may be generated by a client (the client includes a mobile phone, a tablet computer, a notebook computer, etc.) or may be generated by the server (the server may be a tablet computer, a notebook computer, a computer, etc.). The task execution condition carried in the task processing request may be information required for executing the task, and the task execution condition may include one or more of the following: the task management system comprises use environment information of the task, execution destination information of the task and executive person identity information of the task. The service environment information of the task may be an application field (e.g., marketing industry, medical industry, etc.) corresponding to the task, the task may be executed for an effect (e.g., increase of product input amount, etc.) corresponding to an execution result obtained after the task is executed, and the identity information of the task executor may be a job of a task executor (e.g., marketing staff, medical staff, etc.).
Specifically, it is necessary to know what the task is to execute a task quickly, so that the user is required to input a task processing request, and only after the user inputs the task processing request and the server acquires the task processing request, the server can perform the next operation on the task, that is, only after the task processing request is acquired through step S101, the subsequent steps S102 to S104 can be performed.
In step S102, the constructed knowledge graph may be constructed according to the historical operations corresponding to each user in an organization (e.g., team, department, etc.). The knowledge graph comprises a plurality of nodes, and each node can represent any one of the following information: the user (such as a user name, a user identifier, and the like), the user identity information, the use environment information of the user for executing the task, the purpose information of the user for executing the task, each operation step corresponding to the user for executing the task, and the like. The two user nodes may have a hierarchical relationship or a flat-level relationship. If the two users are in the relationship of upper and lower levels, the two users are related through the job level. If there is a flat relationship between two users, then the two users are connected by a node that is common when performing the task. In the knowledge graph, the node corresponding to the execution step further includes an attribute value, and the attribute value may be information included in a task execution condition of the task executed by the execution step.
Specifically, the execution steps matched with the information in the task execution bar can be screened out from the knowledge graph spectrum according to the information in the task execution bar, and the execution steps matched with the task execution conditions are arranged according to the execution sequence to obtain the task processing flow. Because the knowledge graph has a plurality of users, and each user is likely to process the task corresponding to the same task execution condition, a plurality of task processing flows corresponding to the task processing requests can be found in the knowledge graph through the task execution conditions.
For more detailed knowledge graph understanding, as shown in fig. 2, the embodiment of the present application provides a knowledge graph corresponding to a task that the user can perform when the task is a task for converting the advertisement into a target for improving registration. In the knowledge graph, an executor executing a task is Xiaoming, the identity of the executor is an advertisement optimizer, the Xiaoming wants to realize the target result of improving the registration conversion in the advertisement marketing scene, and the execution steps include that an advertisement analysis system is used, a report module (a sub-module of the advertisement analysis system) under the advertisement analysis system is used, data index analysis is carried out according to the report module to determine the distribution condition of the registered gender, then, a gender orientation module of the advertisement delivery system is used for analyzing the male-female proportion to obtain that the registered number of the male is higher, the delivery amount of the advertisement to the male is adjusted (the delivery amount of the advertisement to the male is increased), and further the registration conversion rate is improved.
In step S103, the selection instruction may be obtained by the user operating the client, the selection instruction may be a task processing flow used by the user when determining to process the task, the selection instruction may carry identification information of the target task processing flow, and the identification information may be a preset character, where the preset character includes a number, a letter, a punctuation mark, and the like. The target task processing flow may be one of task processing flows for processing a task.
Specifically, in order to facilitate the user to know the task processing flow, the server may directly push the found task processing flow to the client, so that the client displays the processing flow in the display interface, and the user can observe what task processing flows of the task are through the client. In order to meet the processing requirements of the user and enable the user to have a better sense of participation, the client can determine the selection instruction of the user according to the operation of the user in the display interface of the client, and the client sends the determined selection instruction to the server.
In the step S104, the network operation may be a process implemented according to a task processing flow, and a processing result of the task may be obtained when the network operation is finished.
Specifically, the found identification information of all task processing flows is traversed, the task processing flow matched with the identification information carried by the selection instruction is screened out to serve as a target task processing flow, and network operation is carried out according to the target task processing flow so as to solve the task purpose corresponding to the task.
In the four steps, the executed task processing flow matched with the task execution condition is obtained in the knowledge graph through the task execution condition and is displayed to the user, so that the user determines a target task processing flow to perform network operation in the found task processing flows, the task processing flow is determined through continuous conversation with other users when the user executes the task, the processing time of the user is saved, and the task processing efficiency of the user is improved.
When finding a task processing flow in a constructed knowledge graph, in addition to information related to a task (information included in the task execution condition), information of the task processing flow itself needs to be considered, such as processing efficiency, and if a task processing request also carries requirement information with optimal representation efficiency, step S102 includes:
step 1021, according to the task execution conditions, a shortest path searching method is adopted to search out the task processing flow corresponding to the task processing request from the established knowledge graph.
In the step 1021, the shortest path searching method may be the method with the least steps executed in the search processing flow.
Specifically, in the constructed knowledge graph, a plurality of task processing flows matched with the task execution conditions are found according to the task execution conditions, but in order to improve the execution efficiency of the task, a task processing flow with fewer execution steps can be determined from the plurality of task processing flows found. In step S103, when the task processing flows with fewer execution steps are displayed to the user, the user does not need to further select the task processing flows, and the task processing flows with higher processing efficiency can be directly obtained.
For example, there are two task processing flows, the task processing flow 1 includes step a, step B, step C, step D, and step F, and the task processing flow 2 includes step E, step D, and step F, in the above description, the task processing flow 1 includes 5 execution steps, and the task processing flow 2 includes 3 execution steps, obviously, the execution steps of the task processing flow 2 are fewer, so the task processing flow 2 can be directly selected by using the shortest path search method.
When acquiring the task processing flow, the task processing flow to be selected needs to be determined according to the actual situation, and if the user wants that the processing result of the task can bring greater benefit to the user, that is, if the task processing request carries the requirement information for representing the optimal return, step S102 includes:
step 1022, according to the task execution condition and the processing result evaluation value corresponding to each task processing flow, the task processing flow corresponding to the task processing request is found from the constructed knowledge graph.
In step 1031, the processing result evaluation value is used to represent the degree of benefit to the user from the processing result obtained after the task is executed by the task processing flow, and the higher the processing result evaluation value is, the greater the degree of benefit to the user from the processing result obtained after the task is executed by the task processing flow is, whereas the lower the processing result evaluation value is, the smaller the degree of benefit to the user from the processing result obtained after the task is executed by the task processing flow is. The demand information with the best return may be the demand information that brings the greatest benefit to the user.
Specifically, in the constructed knowledge graph, a plurality of task processing flows matching the task execution conditions are found according to the task execution conditions, but in order to improve the benefit degree of the processing result of the task, the task processing flow with the maximum benefit degree of the processing result can be determined from the plurality of found task processing flows. The degree of benefit may be the highest degree of accuracy, or may be the highest degree of conversion, etc., and may be determined on an as-needed basis. When the benefit degree is the highest accuracy, comparing the historical processing result corresponding to the searched task processing flow with the historical standard value, screening the task processing flow with the smallest difference with the historical standard value, wherein the processing result corresponding to the screened task processing flow when executing the task can bring the greatest benefit to the user; when the benefit degree is that the conversion rate is the highest, the task processing flow with the highest conversion rate corresponding to the history processing result is screened out directly according to the history processing result corresponding to each task processing flow, and the processing result corresponding to the screened out task processing flow when the task is executed can bring the maximum benefit to the user. In step S103, when the task processing flow that brings the greatest benefit to the user is displayed to the user, the user does not need to further select the task processing flow, and can directly obtain the task processing flow with higher benefit.
For example, there are three task processing flows for calculating the conversion rate, the task processing flow 1 includes step a, step B, step C, step D, and step F, the task processing flow 2 includes step E, step D, and step F, and the task processing flow 3 includes step a, step B, step G, step H, step I, and step F, where the conversion rate of the task processing flow 1 is 50%, the conversion rate of the task processing flow 2 is 38%, and the conversion rate of the task processing flow 3 is 85%, and it is obvious that the conversion rate of the task processing flow 3 is the highest for a user to want a task processing flow for improving the conversion rate, so the user can directly select the task processing flow 3.
In order to enable the user to comprehensively understand the task processing flow and reduce confusion of the user about the task processing flow, when the task processing flow is displayed, step S103 includes:
and step 1031, displaying the searched task processing flow in the form of the task processing flow in the knowledge graph so as to obtain a selection instruction for the task processing flow.
In the above step 1031, the form in the knowledge graph may be a screenshot of the position of the task processing flow in the knowledge graph, or a node connection diagram corresponding to the task processing flow in the knowledge graph.
Specifically, the found task processing flow is displayed in a form of the task processing flow in a knowledge graph, so that the user can clearly know the processing process of the task processing flow, and can know relevant information (such as a plurality of execution purposes corresponding to the execution steps, a plurality of use scenes corresponding to the execution steps, and the like) outside the execution steps in the task processing flow, so that the user can further know each execution step in the task processing flow, and when the user executes other tasks, the relevant information of the execution steps can have a reference value, so that the user can find the accurate execution step corresponding to the other tasks when executing the other tasks.
After the searched task processing flow is displayed to the user, the user still cannot decide which task processing flow to use, and at this time, some reference information is needed to improve the decision efficiency of the user, and step S103 includes:
step 1032, displaying the searched task processing flow and the use information corresponding to each node in the searched task processing flow in the form in the knowledge graph to obtain a selection instruction for the task processing flow.
In 1032 above, the usage information corresponding to each node may include one or more of the following information: the number of times a node is used, the number of times a node is currently being used, the number of times a node has processed a current task, etc.
Specifically, when the searched task processing flow is displayed, the related information corresponding to each node in the processing flow is displayed to the user together, so that more reference information is added when the user selects the task processing flow, the user can more accurately determine the task processing flow matched with the task, and the efficiency and the accuracy of selecting the task processing flow by the user are improved.
For example, there are two task processing flows corresponding to a task 1 and a task 1, the related information corresponding to each execution step in the task flow is the number of times that the task 1 has been executed, the task processing flow 1 includes a step a, a step B, a step C, a step D, and a step F, and the task processing flow 2 includes a step E, a step D, and a step F, in the above description, the number of times that the task 1 has been executed corresponding to the step a, the step B, the step C, the step D, and the step F in the task processing flow 1 is 10, 30, 25, 21, and 150, respectively, the number of times that the task 1 has been executed corresponding to the step E, the step D, and the step F in the task processing flow 2 is 98, 105, and 150, respectively, it is obvious that the number of times that the task 1 has been executed by the execution steps in the task processing flow 2 is greater, it indicates that more users have selected the task flow 2 to execute the task, therefore, the user can select the task processing flow 2 to execute the task 1 according to the relevant information corresponding to each step.
As shown in fig. 3, an embodiment of the present application provides a network operating apparatus, including:
an obtaining module 301, configured to obtain a task processing request input by a user; the task processing request carries a task execution condition;
the searching module 302 is configured to search a task processing flow corresponding to the task processing request in the constructed knowledge graph according to the task execution condition;
the display module 303 is configured to display the searched task processing flow to obtain a selection instruction for the task processing flow;
and the operation module 304 is configured to perform a network operation according to the target task processing flow corresponding to the selection instruction.
Optionally, if the task processing request carries the requirement information for representing the optimal efficiency, the searching module 302 includes:
and the optimal efficiency searching unit is used for searching the task processing flow corresponding to the task processing request from the established knowledge graph by adopting a shortest path searching method according to the task execution conditions.
Optionally, if the task processing request carries the requirement information for characterizing the optimal return, the searching module 302 includes:
and the return optimal searching unit is used for searching the task processing flow corresponding to the task processing request from the constructed knowledge graph according to the task execution condition and the processing result evaluation value corresponding to each task processing flow.
Optionally, the display module 303 includes:
and the display unit is used for displaying the searched task processing flow in the form of the task processing flow in the knowledge graph so as to obtain a selection instruction aiming at the task processing flow.
Optionally, the display unit includes:
and the display subunit is used for displaying the searched task processing flow and the use information corresponding to each node in the searched task processing flow in the form in the knowledge graph so as to obtain a selection instruction for the task processing flow.
Optionally, the task execution condition includes any one or more of the following:
the task management system comprises use environment information of the task, execution destination information of the task and executive person identity information of the task.
Corresponding to the network operation method in fig. 1, an embodiment of the present application further provides a computer device 400, as shown in fig. 4, the device includes a memory 401, a processor 402, and a computer program stored on the memory 401 and executable on the processor 402, wherein the processor 402 implements the steps of the network operation method when executing the computer program.
Specifically, the memory 401 and the processor 402 can be general memories and processors, which are not specifically limited herein, and when the processor 402 runs a computer program stored in the memory 401, the network operation method can be executed, so as to solve the problem of how to improve the task processing efficiency of a user in the prior art, a task processing flow matched with a task execution condition that has been executed is obtained in a knowledge graph through the task execution condition and is displayed to the user, so that the user determines a target task processing flow to perform network operation in the found task processing flow, and the user does not need to determine the task processing flow through continuous conversation with other users when executing the task, thereby saving the processing time of the user and improving the task processing efficiency of the user.
Corresponding to the network operation method in fig. 1, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and the computer program is executed by a processor to perform the steps of the network operation method.
Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, and the like, when a computer program on the storage medium is run, the network operation method can be executed, so as to improve the task processing efficiency of a user, the task processing flow matched with the task execution condition, which has been executed, is obtained in the knowledge graph through the task execution condition, and is displayed to the user, so that the user determines a target task processing flow to perform network operation in the found task processing flow, the user does not need to determine the task processing flow through continuous conversation with other users when executing the task, the processing time of the user is saved, and the task processing efficiency of the user on the task is improved.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, 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.
In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A method of network operation, comprising:
acquiring a task processing request input by a user; the task processing request carries a task execution condition;
according to the task execution condition, searching a task processing flow corresponding to the task processing request in the established knowledge graph;
displaying the searched task processing flow to obtain a selection instruction aiming at the task processing flow;
and performing network operation according to the target task processing flow corresponding to the selection instruction.
2. The method according to claim 1, wherein if the task processing request carries requirement information for representing optimal efficiency, finding a task processing flow corresponding to the task processing request in the constructed knowledge graph according to the task execution condition comprises:
and searching a task processing flow corresponding to the task processing request from the established knowledge graph by adopting a shortest path searching method according to the task execution condition.
3. The method according to claim 1, wherein if the task processing request carries demand information for characterizing optimal return, finding a task processing flow corresponding to the task processing request in the constructed knowledge graph according to the task execution condition comprises:
and searching the task processing flow corresponding to the task processing request from the constructed knowledge graph according to the task execution condition and the processing result evaluation value corresponding to each task processing flow.
4. The method according to claim 1, wherein the displaying the searched task processing flow to obtain a selection instruction for the task processing flow comprises:
and displaying the searched task processing flow in the form of the task processing flow in the knowledge graph so as to obtain a selection instruction aiming at the task processing flow.
5. The method according to claim 4, wherein the displaying the task processing flow to be found in the form of the task processing flow in the knowledge graph to obtain a selection instruction for the task processing flow comprises:
and displaying the searched task processing flow and the use information corresponding to each node in the searched task processing flow in a form in the knowledge graph to acquire a selection instruction aiming at the task processing flow.
6. The method of claim 1, wherein the task execution conditions include any one or more of:
the task management system comprises use environment information of the task, execution destination information of the task and executive person identity information of the task.
7. A network operating apparatus, comprising:
the acquisition module is used for acquiring a task processing request input by a user; the task processing request carries a task execution condition;
the searching module is used for searching a task processing flow corresponding to the task processing request in the established knowledge graph according to the task execution condition;
the display module is used for displaying the searched task processing flow so as to obtain a selection instruction aiming at the task processing flow;
and the operation module is used for performing network operation according to the target task processing flow corresponding to the selection instruction.
8. The apparatus according to claim 7, wherein if the task processing request carries the requirement information for representing the optimal efficiency, the searching module includes:
and the optimal efficiency searching unit is used for searching the task processing flow corresponding to the task processing request from the established knowledge graph by adopting a shortest path searching method according to the task execution condition.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of the preceding claims 1-6 are implemented by the processor when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is adapted to carry out the steps of the method of any one of the preceding claims 1 to 6.
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