Parameter configuration method and device, storage medium and electronic equipment

Abstract

The invention provides a parameter configuration method and device, a storage medium and electronic equipment, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring existing service scene parameter configuration information; the existing service scene parameter configuration information comprises supporting capacity corresponding to an existing service scene and parameter configuration corresponding to the supporting capacity; determining a business scene heterogeneous graph and a support capability and parameter bipartite graph according to the existing business scene parameter configuration information; and according to parameter demand information of the target supporting capability in the target service scene, performing graph convolution on the service scene heterogeneous graph and the supporting capability and parameter bipartite graph, and determining parameter configuration of the target supporting capability in the target service scene. According to the method, automatic generation of the parameter configuration of the supporting capacity is realized, so that designers do not need to manually cut global parameter configuration, the accuracy of parameter configuration design is improved, the labor force of business scene designers can be released, and the business scene design efficiency is improved.

Description

Background Art

[0002] Currently, when using support capabilities to build business scenarios, it is necessary to select the required parameter configuration from the global parameter configuration of the support capability according to the business scenario to reduce redundancy and misoperation. Each support capability has more than a dozen or dozens of different parameter configurations. A business scenario will use multiple support capabilities, and business scenarios are diverse and changeable. This leads to complex and diverse parameter configurations of support capabilities corresponding to different business scenarios.

[0003] In the design of existing business scenarios and supporting capabilities, designers are required to be familiar with the parameter configurations of various business scenarios and supporting capabilities, which places high demands on the professional capabilities of designers. When designing business scenarios, it is necessary to manually trim parameters that are not related to the current business scenario from the global parameter configuration based on the supporting capabilities corresponding to different business scenarios. This is a large workload and is time-consuming and labor-intensive. In addition, there is a problem of trimming errors, which leads to errors in business scenario design.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The present disclosure provides a parameter configuration method and device, a storage medium and an electronic device, which at least to some extent overcome the time-consuming, labor-intensive and low-accuracy problems caused by manual parameter cutting in the related art.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of the present disclosure, a parameter configuration method is provided, including:

[0008] Acquire existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: support capabilities corresponding to the existing business scenario, and parameter configurations corresponding to the support capabilities;

[0009] Determine the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph based on the existing business scenario parameter configuration information;

[0010] According to the parameter requirement information of the target support capability under the target business scenario, graph convolution is performed on the business scenario heterogeneous graph and the support capability and parameter bipartite graph to determine the parameter configuration of the target support capability under the target business scenario.

[0011] In some embodiments, determining a heterogeneous graph of business scenarios according to existing business scenario parameter configuration information includes:

[0012] Parsing the supporting capability corresponding to the existing business scenario, determining the existing business scenario as a first node, determining the supporting capability corresponding to the business scenario as a second node, and determining the corresponding relationship between the business scenario and the supporting capability as an edge between the first node and the second node;

[0013] parsing the parameter configuration corresponding to the supporting capability, determining the parameter configuration corresponding to the supporting capability as a third node, and determining the corresponding relationship between the supporting capability and the parameter configuration as an edge between the second node and the third node;

[0014] A business scenario heterogeneous graph is determined based on the first node, the edge between the first node and the second node, the second node, the edge between the second node and the third node, and the third node.

[0015] In some embodiments, determining a bipartite graph of support capability and parameters based on existing business scenario parameter configuration information includes:

[0016] Constructing a first vertex set according to the supporting capability corresponding to the existing business scenario; the first vertex set includes a first vertex determined according to the supporting capability;

[0017] According to the parameter configuration corresponding to the supporting capability, a second vertex set is constructed; the second vertex set includes a second vertex determined according to the parameter configuration;

[0018] Determine an edge set between the first vertex set and the second vertex set according to the correspondence between the supporting capability and the parameter configuration; the edges included in the edge set respectively connect a first vertex in the first vertex set and a second vertex in the second vertex set;

[0019] A supporting capacity and parameter bipartite graph is determined according to the first vertex set, the second vertex set and the edge set.

[0020] In some embodiments, the parameter configuration includes: input parameter configuration and output parameter configuration;

[0021] According to the parameter configuration corresponding to the support capability, a second vertex set is constructed, including:

[0022] Determining a second input parameter vertex according to the input parameter configuration;

[0023] Determining a second output parameter vertex according to the output parameter configuration;

[0024] A second vertex set is constructed according to the second input parameter vertex and the second output parameter vertex.

[0025] In some embodiments, the edge set includes: a first edge connecting a first vertex in the first vertex set and a vertex of the second input parameter, and a second edge connecting a first vertex in the first vertex set and a vertex of the second output parameter;

[0026] Determining a bipartite graph of support capability and parameters according to the first vertex set, the second vertex set, and the edge set includes:

[0027] Connecting the first vertex in the first vertex set to the second input parameter vertex through the first edge to construct a bipartite graph of supporting capability and input parameter;

[0028] Connecting the first vertex in the first vertex set to the second output parameter vertex through the second edge to construct a bipartite graph of supporting capability and output parameter;

[0029] The supporting capability and input parameter bipartite graph and the supporting capability and output parameter bipartite graph are determined as supporting capability and parameter bipartite graph.

[0030] In some embodiments, according to the parameter requirement information of the target support capability in the target business scenario, graph convolution is performed on the business scenario heterogeneous graph and the support capability and parameter bipartite graph to determine the parameter configuration of the target support capability in the target business scenario, including:

[0031] Inputting parameter requirement information of target support capability under target business scenario into the business scenario heterogeneous graph, performing graph convolution, and determining business scenario characteristics;

[0032] Inputting parameter requirement information of target support capability under target business scenario into the support capability and parameter bipartite graph, performing graph convolution, and determining parameter features;

[0033] According to the business scenario characteristics and the parameter characteristics, parameter configuration of the target support capability under the target business scenario is determined.

[0034] In some embodiments, the bipartite graph of support capability and parameters includes: a bipartite graph of support capability and input parameters, and a bipartite graph of support capability and output parameters;

[0035] Inputting parameter requirement information of the target support capability under the target business scenario into the support capability and parameter bipartite graph, performing graph convolution, and determining parameter features, including:

[0036] Input the parameter requirement information of the target support capability under the target business scenario into the bipartite graph of support capability and input parameters, perform graph convolution, and determine the input parameter characteristics;

[0037] Input the parameter requirement information of the target support capability under the target business scenario into the bipartite graph of support capability and output parameter, perform graph convolution, and determine the output parameter characteristics;

[0038] The input parameter characteristic and the output parameter characteristic are determined as parameter characteristics.

[0039] In some embodiments, determining the parameter configuration of the target support capability in the target business scenario according to the business scenario characteristics and the parameter characteristics includes:

[0040] Performing graph feature fusion on the business scenario features and the input parameter features to determine the input parameter configuration;

[0041] Performing graph feature fusion on the business scenario features and the output parameter features to determine the output parameter configuration;

[0042] According to the input parameter configuration and the output parameter configuration, a parameter configuration of a target supporting capability in a target business scenario is determined.

[0043] In some embodiments, the business scenario feature is fused with the input parameter feature to determine the input parameter configuration, including:

[0044] Determine the node characteristics of the business scenario characteristics and the node characteristics of the input parameter characteristics;

[0045] Splicing the node feature of the business scenario feature and the node feature of the input parameter feature to determine a first splicing feature;

[0046] The first concatenated features are expressed by a multi-layer perceptron to obtain fusion features and determine input parameter configuration.

[0047] In some embodiments, the business scenario feature and the output parameter feature are graph-feature fused to determine the output parameter configuration, including:

[0048] Determine the node characteristics of the business scenario characteristics and the node characteristics of the output parameter characteristics;

[0049] Splicing the node feature of the business scenario feature and the node feature of the output parameter feature to determine a second splicing feature;

[0050] The second concatenated features are expressed by a multi-layer perceptron to obtain fusion features and determine output parameter configuration.

[0051] According to another aspect of the present disclosure, a parameter configuration device is also provided, including:

[0052] An information acquisition module is used to acquire existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: support capabilities corresponding to the existing business scenarios, and parameter configurations corresponding to the support capabilities;

[0053] A heterogeneous graph and bipartite graph determination module is used to determine a business scenario heterogeneous graph and a supporting capability and parameter bipartite graph based on existing business scenario parameter configuration information;

[0054] The parameter configuration determination module is used to perform graph convolution on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph according to the parameter requirement information of the target supporting capability under the target business scenario, so as to determine the parameter configuration of the target supporting capability under the target business scenario.

[0055] According to another aspect of the present disclosure, an electronic device is also provided, which includes: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the parameter configuration methods described above by executing the executable instructions.

[0056] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the parameter configuration method described in any one of the above is implemented.

[0057] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the computer program implements any one of the above parameter configuration methods.

[0058] The parameter configuration method and device, storage medium and electronic device provided in the embodiments of the present disclosure include: obtaining existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: the supporting capabilities corresponding to the existing business scenarios, and the parameter configurations corresponding to the supporting capabilities; determining the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph based on the existing business scenario parameter configuration information; performing graph convolution on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph based on the parameter requirement information of the target supporting capability under the target business scenario, and determining the parameter configuration of the target supporting capability under the target business scenario. The disclosed embodiment utilizes existing business scenario parameter configuration information to construct a business scenario heterogeneous graph and a supporting capability and parameter bipartite graph, and performs graph convolution on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph based on the parameter requirement information of the target supporting capability under the target business scenario to obtain the parameter configuration of the target supporting capability under the target business scenario, thereby realizing the automatic generation of the parameter configuration of the supporting capability, thereby eliminating the need for designers to manually tailor the global parameter configuration, improving the accuracy of parameter configuration design, freeing up the labor of business scenario designers, saving the labor and time costs of manually designing business supporting scenarios and supporting capabilities, lowering the design threshold for business scenarios and supporting capabilities, and improving the efficiency of business scenario design.

[0059] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0061] Figure 1 A schematic diagram showing the system structure of a parameter configuration method in an embodiment of the present disclosure.

[0062] Figure 2 A schematic diagram of a business scenario for a new smart enterprise network is shown.

[0063] Figure 3 A schematic diagram of a parameter configuration method in an embodiment of the present disclosure is shown.

[0064] Figure 4 A schematic diagram of a process of determining a heterogeneous graph of business scenarios in a parameter configuration method according to an embodiment of the present disclosure is shown.

[0065] Figure 5A schematic diagram of a process of determining a supporting capability and a bipartite graph of parameters in a parameter configuration method in an embodiment of the present disclosure is shown.

[0066] Figure 6 A schematic diagram of the process of constructing a second vertex set in a parameter configuration method in an embodiment of the present disclosure is shown.

[0067] Figure 7 A schematic diagram of a specific process of determining a supporting capability and a bipartite graph of parameters in a parameter configuration method in an embodiment of the present disclosure is shown.

[0068] Figure 8 A schematic diagram of a parameter configuration process for determining a target support capability in a target business scenario in a parameter configuration method according to an embodiment of the present disclosure is shown.

[0069] Fig. 9 A schematic diagram of a parameter feature determination process of a parameter configuration method in an embodiment of the present disclosure is shown.

[0070] Fig.10 A schematic diagram showing a specific process of parameter configuration for determining a target support capability in a target business scenario in a parameter configuration method according to an embodiment of the present disclosure.

[0071] Fig.11 A schematic diagram of a process of determining input parameter configuration of a parameter configuration method in an embodiment of the present disclosure is shown.

[0072] Fig.12 A schematic diagram of a process of determining output parameter configuration of a parameter configuration method in an embodiment of the present disclosure is shown.

[0073] Fig.13 A flow chart showing graph convolution fusion of a heterogeneous graph of business scenarios, a bipartite graph of supporting capabilities and input parameters, and a bipartite graph of supporting capabilities and output parameters in a parameter configuration method in an embodiment of the present disclosure.

[0074] Fig.14 A schematic diagram of a business scenario involved in the installation of a mobile phone according to a parameter configuration method in an embodiment of the present disclosure is shown.

[0075] Fig.15 A schematic diagram of a parameter configuration device in an embodiment of the present disclosure is shown.

[0076] Fig.16 A structural block diagram of a computer device for a parameter configuration method in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0077] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0078] In addition, the accompanying drawings are only schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0079] For ease of understanding, before introducing the embodiments of the present disclosure, several terms involved in the embodiments of the present disclosure are first explained as follows:

[0080] Business scenarios: Also known as telecom business support scenarios, they refer to the scenarios involved when telecom operators conduct marketing to customers, including government and enterprise marketing scenarios, online / offline marketing scenarios, store retail scenarios, channel operation scenarios, intelligent customer service scenarios, risk management scenarios, etc.

[0081] Support capabilities, also known as telecommunications business support capabilities, refer to the marketing capabilities used by telecommunications operators in various business scenarios, including business opportunity management, customer management, product management, order management, channel management, customer service management, billing management, etc.

[0082] Parameter configuration refers to the parameters of supporting capabilities. When building business scenarios, supporting capabilities need to select and configure corresponding input parameters and output parameters.

[0083] The specific implementation of the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0084] Figure 1 FIG. 1 shows an exemplary application system architecture diagram to which the parameter configuration method in the embodiment of the present disclosure can be applied. Figure 1 As shown, the system architecture may include a terminal device 101 , a network 102 and a server 103 .

[0085] The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103, and can be a wired network or a wireless network.

[0086] Optionally, the wireless network or wired network described above uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network). In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged through the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec) can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.

[0087] The terminal device 101 can be various electronic devices, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, wearable devices, augmented reality devices, virtual reality devices, etc.

[0088] Optionally, the client of the application installed in different terminal devices 101 is the same, or the client of the same type of application based on different operating systems. Based on the different terminal platforms, the specific form of the client of the application can also be different, for example, the application client can be a mobile client, a PC client, etc.

[0089] The server 103 may be a server that provides various services, such as a background management server that provides support for the device operated by the user using the terminal device 101. The background management server may analyze and process the received request and other data, and feed back the processing results to the terminal device.

[0090] Optionally, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. The terminal can be a smart phone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in this application.

[0091] Those skilled in the art will know that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration, and any number of terminal devices, networks and servers may be provided according to actual needs, and the embodiments of the present disclosure do not limit this.

[0092] Under the above system architecture, a parameter configuration method is provided in an embodiment of the present disclosure, and the method can be executed by any electronic device with computing and processing capabilities.

[0093] In some embodiments, the parameter configuration method provided in the embodiments of the present disclosure may be executed by a terminal device of the above-mentioned system architecture; in other embodiments, the parameter configuration method provided in the embodiments of the present disclosure may be executed by a server in the above-mentioned system architecture; in other embodiments, the parameter configuration method provided in the embodiments of the present disclosure may be implemented by a terminal device and a server in the above-mentioned system architecture through interaction.

[0094] When using supporting capabilities to build business scenarios, due to the diversity of business scenarios and the complexity of supporting capabilities, manually designing business scenarios requires designers to have high professional capabilities. Figure 2 A business scenario of a new smart enterprise network is shown. Figure 2 As shown, in the business scenario of new installation of smart enterprise network, at least one certificate and five cards, cloud network account verification, number query, number reservation, order payment, activation and completion and other supporting capabilities are used for construction and implementation.

[0095] When designing business scenarios, designers need to understand what supporting capabilities are needed for the target business scenarios and the parameter configurations required for the supporting capabilities. They need to manually cut out the supporting capabilities and corresponding parameter configurations required for the target business scenarios from the global parameter configurations to complete the parameter configuration cutting and the design of the target business scenarios. Designers need to be familiar with the business scenario and business supporting capability parameter cutting and configuration during the above process. Operators' business scenarios are often diverse, large and complex. If designers are required to manually configure the supporting capability parameter configurations for each business scenario, the workload will be large and time-consuming, and there will be design errors, resulting in a slow launch of business scenarios and possible missed business opportunities or marketing opportunities.

[0096] Figure 3 A schematic diagram of a parameter configuration method in an embodiment of the present disclosure is shown. Figure 3 As shown, the parameter configuration method provided in the embodiment of the present disclosure includes the following steps:

[0097] Step S302: Acquire existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: support capabilities corresponding to the existing business scenarios, and parameter configurations corresponding to the support capabilities;

[0098] Step S304: Determine a heterogeneous graph of business scenarios and a bipartite graph of supporting capabilities and parameters according to the existing business scenario parameter configuration information;

[0099] Step S306: According to the parameter requirement information of the target supporting capability in the target business scenario, graph convolution is performed on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph to determine the parameter configuration of the target supporting capability in the target business scenario.

[0100] This embodiment utilizes existing business scenario parameter configuration information to construct a business scenario heterogeneous graph and a bipartite graph of supporting capabilities and parameters, and performs graph convolution on the business scenario heterogeneous graph and the bipartite graph of supporting capabilities and parameters based on the parameter requirement information of the target supporting capabilities under the target business scenario to obtain the parameter configuration of the target supporting capabilities under the target business scenario, thereby realizing the automatic generation of the parameter configuration of the supporting capabilities, thereby eliminating the need for designers to manually tailor the global parameter configuration, improving the accuracy of parameter configuration design, freeing up the labor of business scenario designers, saving the labor and time costs of manually designing business supporting scenarios and supporting capabilities, lowering the design threshold for business scenarios and supporting capabilities, and improving the efficiency of business scenario design.

[0101] Figure 4 A schematic diagram of the process of determining a heterogeneous graph of business scenarios in an embodiment of the present disclosure is shown. Figure 4 As shown, in the embodiment, determining a heterogeneous graph of business scenarios according to existing business scenario parameter configuration information includes:

[0102] Step S402: parsing the supporting capability corresponding to the existing business scenario, determining the existing business scenario as the first node, determining the supporting capability corresponding to the business scenario as the second node, and determining the corresponding relationship between the business scenario and the supporting capability as the edge between the first node and the second node;

[0103] Step S404: parsing the parameter configuration corresponding to the supporting capability, determining the parameter configuration corresponding to the supporting capability as a third node, and determining the corresponding relationship between the supporting capability and the parameter configuration as an edge between the second node and the third node;

[0104] Step S406: Determine a business scenario heterogeneous graph according to the first node, the edge between the first node and the second node, the second node, the edge between the second node and the third node, and the third node.

[0105] The existing business scenario parameter configuration information contains the supporting capabilities corresponding to the existing business scenarios and the parameter configurations corresponding to the supporting capabilities. The existing business scenario parameter configuration information is the business scenario manually designed by the designer and completed online implementation. It is a business scenario that has been verified by actual use. Therefore, the supporting capabilities corresponding to the existing business scenarios in the existing business scenario parameter configuration information are correct, and the parameter configurations corresponding to the supporting capabilities are also correct. The existing business scenario parameter configuration information provides a data basis for constructing the heterogeneous graph of business scenarios and the bipartite graph of supporting capabilities and parameters.

[0106] When constructing a heterogeneous graph of business scenarios, the supporting capabilities corresponding to existing business scenarios are analyzed based on graph theory to obtain business entities and relationships, wherein the business entities are existing business scenarios and supporting capabilities, and the relationships are the corresponding relationships between business scenarios and supporting capabilities; the existing business scenarios of the business entities are determined as the first node, the supporting capabilities of the business entities are determined as the second node, and the corresponding relationships between the business scenarios and supporting capabilities are determined as the edges between the first node and the second node; further, the parameter configurations corresponding to the supporting capabilities are analyzed based on graph theory to obtain business entities and relationships, wherein the business entities are supporting capabilities and parameter configurations, and the relationships are the corresponding relationships between supporting capabilities and parameter configurations; the business entity parameter configurations are determined as the third node, and the corresponding relationships between the supporting capabilities and parameter configurations are determined as the edges between the second node and the third node; after the above two steps of analysis, three nodes and two edges are obtained, and a heterogeneous graph of business scenarios is constructed according to the first node, the edge between the first node and the second node, the second node, the edge between the second node and the third node, and the third node. Specifically, the first node, the second node and the third node are connected using the edge between the first node and the second node and the edge between the second node and the third node, and then the edge between the first node and the second node and the edge between the second node and the third node is used to establish the edge between the first node and the third node, and then the first node and the point node are connected using the edge between the first node and the third node to construct a heterogeneous graph for business scenarios.

[0107] The business scenario heterogeneous graph includes which supporting capabilities are used in each existing business scenario, and which configuration parameters each supporting capability selects and configures from the global parameters in its specific business scenario. The business scenario heterogeneous graph can provide auxiliary supporting information for multiple features of product structure. The information in the business scenario heterogeneous graph is rich and diverse. Combining it with the bipartite graph can make up for the disadvantage of insufficient information in the bipartite graph and realize the accurate generation of configuration parameters.

[0108] Figure 5 A schematic diagram of the process of determining the supporting capability and parameter bipartite graph in the embodiment of the present disclosure is shown. Figure 4 As shown, in the embodiment, according to the existing business scenario parameter configuration information, the supporting capability and parameter bipartite graph is determined, including:

[0109] Step S502: construct a first vertex set according to the supporting capability corresponding to the existing business scenario; the first vertex set includes a first vertex determined according to the supporting capability;

[0110] Step S504: constructing a second vertex set according to the parameter configuration corresponding to the support capability; the second vertex set includes a second vertex determined according to the parameter configuration;

[0111] Step S506: determining an edge set between the first vertex set and the second vertex set according to the corresponding relationship between the support capability and the parameter configuration; the edges included in the edge set respectively connect the first vertex in the first vertex set and the second vertex in the second vertex set;

[0112] Step S508: Determine a supporting capacity and parameter bipartite graph according to the first vertex set, the second vertex set, and the edge set.

[0113] When constructing a bipartite graph of support capabilities and parameters, the support capabilities corresponding to the existing business scenarios are analyzed based on graph theory to obtain the support capabilities of the business entities, the first vertex is determined based on the support capabilities, and the first vertex set is constructed. The parameter configuration corresponding to the support capabilities is analyzed based on graph theory to obtain the business entity parameter configuration, the second vertex is determined based on the parameter configuration, and the second vertex set is constructed. The corresponding relationship between the support capabilities and the parameter configuration is analyzed based on graph theory to obtain edges, which respectively connect the first vertex in the first vertex set and the second vertex in the second vertex set, and the edge set between the first vertex set and the second vertex set is constructed. Finally, the bipartite graph of support capabilities and parameters is determined based on the first vertex set, the second vertex set, and the edge set.

[0114] Figure 6 A schematic diagram of the process of constructing the second vertex set in the embodiment of the present disclosure is shown as follows: Figure 6 As shown, in the embodiment, parameter configuration includes: input parameter configuration and output parameter configuration;

[0115] According to the parameter configuration corresponding to the support capability, a second vertex set is constructed, including:

[0116] Step S602: Determine the second input parameter vertex according to the input parameter configuration;

[0117] Step S604: determining a second output parameter vertex according to the output parameter configuration;

[0118] Step S606: construct a second vertex set according to the second input parameter vertex and the second output parameter vertex.

[0119] Parameter configuration is divided into input parameter configuration and output parameter configuration. Taking the customer's newly created business scenario as an example, the required supporting capability "consistent customer query" has output parameters, including at least custName (customer name), isRealname (real name identification), certNum (certificate number), regionId (region identification), custNumber (customer code), contactsInfos (contact information), statusDate (status date), custSubType (customer type) and more than 40 other output parameter fields. Input parameters also include multiple input parameter fields, which are not listed one by one again. Since the configuration parameters are divided into input parameters and output parameters, the constructed second vertex set will also be divided into two categories. Specifically, the input parameter configuration is parsed based on graph theory to determine the second input parameter vertex, and the output parameter configuration is parsed based on graph theory to determine the second output parameter vertex; the second vertex set is constructed based on the second input parameter vertex and the second output parameter vertex.

[0120] Figure 7 A schematic diagram of a specific process of determining a bipartite graph of support capability and parameters in an embodiment of the present disclosure is shown. Figure 7 As shown, in the embodiment, the edge set includes: a first edge connecting a first vertex in the first vertex set and a second input parameter vertex, and a second edge connecting a first vertex in the first vertex set and a second output parameter vertex;

[0121] Determine a support capability and parameter bipartite graph according to the first vertex set, the second vertex set, and the edge set, including:

[0122] Step S702: Connect the first vertex in the first vertex set to the second input parameter vertex through the first edge to construct a bipartite graph of support capability and input parameter;

[0123] Step S704: Connect the first vertex in the first vertex set to the second output parameter vertex through the second edge to construct a bipartite graph of supporting capability and output parameter;

[0124] Step S706: Determine the supporting capability and input parameter bipartite graph and the supporting capability and output parameter bipartite graph as the supporting capability and parameter bipartite graph.

[0125] The edge set includes multiple edges, each edge connects the first vertex in the first vertex set with the second vertex in the second vertex set, and based on the second vertex set including the second input parameter vertex and the second output parameter vertex, the edges in the edge set are divided into two categories: first edges and second edges; the first edge connects the first vertex in the first vertex set with the second input parameter vertex, and the second edge connects the first vertex in the first vertex set with the second output parameter vertex. The process of constructing a bipartite graph of support capability and parameters includes: connecting the first vertex in the first vertex set to the second input parameter vertex through the first edge to construct a bipartite graph of support capability and input parameters, connecting the first vertex in the first vertex set to the second output parameter vertex through the second edge to construct a bipartite graph of support capability and output parameters, and determining the bipartite graphs corresponding to the input parameters and output parameters constructed above as the bipartite graphs of support capability and input parameters and the bipartite graphs of support capability and output parameters as bipartite graphs of support capability and parameters.

[0126] In the supporting capacity and input parameter bipartite graph, the supporting capacity and input parameter are used as vertices in the bipartite graph, and in the supporting capacity and output parameter, the supporting capacity and output parameter are used as vertices in the bipartite graph.

[0127] Figure 8 A schematic diagram of the parameter configuration process for determining the target support capability in the target business scenario in the embodiment of the present disclosure is shown. Figure 8 As shown, in the embodiment, according to the parameter requirement information of the target support capability in the target business scenario, the heterogeneous graph of the business scenario and the bipartite graph of the support capability and the parameter are convolved to determine the parameter configuration of the target support capability in the target business scenario, including:

[0128] Step S802: input parameter requirement information of target support capability under target business scenario into the business scenario heterogeneous graph, perform graph convolution, and determine business scenario characteristics;

[0129] Step S804: input parameter requirement information of target support capability under target business scenario into the support capability and parameter bipartite graph, perform graph convolution, and determine parameter features;

[0130] Step S806: Determine parameter configuration of target support capability under target business scenario according to business scenario characteristics and parameter characteristics.

[0131] The target business scenario refers to the business scenario that needs to be designed and constructed. When designing the target business scenario, the required support capability is the target support capability. In order to realize the target business scenario, the corresponding parameter configuration of the target support capability is the parameter requirement information of the target support capability under the target business scenario. Input the parameter requirement information of the target support capability under the target business scenario into the business scenario heterogeneous graph, and perform graph convolution, so as to extract high-order semantic features from the business scenario heterogeneous graph, thereby determining the business scenario features; input the parameter requirement information of the target support capability under the target business scenario into the supporting capability and parameter bipartite graph, and perform graph convolution, so as to extract high-order semantic features from the supporting capability and parameter bipartite graph, thereby determining the parameter features; according to the business scenario features and parameter features obtained by the above graph convolution, determine the parameter configuration of the target support capability under the target business scenario. This embodiment realizes the automatic generation of the parameter configuration of the supporting capability, so that the designer does not need to manually cut the global parameter configuration, improves the accuracy of the parameter configuration design, can release the labor of the business scenario designer, save the labor and time cost of manually designing the business support scenario and supporting capability, reduce the threshold of business scenario and supporting capability design, and improve the efficiency of business scenario design.

[0132] Fig. 9 A schematic diagram of the process of determining parameter characteristics in an embodiment of the present disclosure is shown. Fig. 9 As shown, in the embodiment, the bipartite graph of support capability and parameters includes: a bipartite graph of support capability and input parameters, and a bipartite graph of support capability and output parameters;

[0133] Input the parameter requirement information of the target support capability under the target business scenario into the support capability and parameter bipartite graph, perform graph convolution, and determine the parameter features, including:

[0134] Step S902: Input parameter requirement information of target support capability under target business scenario into the bipartite graph of support capability and input parameter, perform graph convolution, and determine input parameter features;

[0135] Step S904: input parameter requirement information of target support capability under target business scenario into the bipartite graph of support capability and output parameter, perform graph convolution, and determine output parameter features;

[0136] Step S906: Determine the input parameter characteristics and the output parameter characteristics as parameter characteristics.

[0137] The supporting capability and parameter bipartite graph is divided into the supporting capability and input parameter bipartite graph and the supporting capability and output parameter bipartite graph according to the output parameters and the input parameters. When performing graph convolution on the supporting capability and parameter bipartite graph, it includes: inputting the parameter requirement information of the target supporting capability under the target business scenario into the supporting capability and input parameter bipartite graph, and performing graph convolution to extract high-order semantic features from the supporting capability and input parameter bipartite graph, thereby determining the input parameter features; inputting the parameter requirement information of the target supporting capability under the target business scenario into the supporting capability and output parameter bipartite graph, and performing graph convolution to extract high-order semantic features from the supporting capability and output parameter bipartite graph, thereby determining the output parameter features; and determining the input parameter features and the output parameter features as parameter features.

[0138] Fig.10 A schematic diagram of a specific process of parameter configuration for determining target support capabilities in a target business scenario in an embodiment of the present disclosure is shown. Fig.10 As shown, in the embodiment, according to the business scenario characteristics and parameter characteristics, the parameter configuration of the target support capability under the target business scenario is determined, including:

[0139] Step S1002: merging the business scenario features with the input parameter features to determine the input parameter configuration;

[0140] Step S1004: performing graph feature fusion on the business scenario features and the output parameter features to determine the output parameter configuration;

[0141] Step S1006: Determine parameter configuration of target support capability under target business scenario according to input parameter configuration and output parameter configuration.

[0142] Based on the aforementioned parameter features including input parameter features and output parameter features, the business scenario features are graph-feature fused with the input parameter features to strengthen the parameter requirements of the target support capability under the target business scenario and the feature information of the input parameters, thereby obtaining the input parameter configuration. The business scenario features are graph-feature fused with the output parameter features to strengthen the parameter requirements of the target support capability under the target business scenario and the feature information of the output parameters, thereby obtaining the output parameter configuration. According to the input parameter configuration and the output parameter configuration, the parameter configuration of the target support capability under the target business scenario is determined.

[0143] Fig.11 A schematic diagram of the process of determining input parameter configuration in an embodiment of the present disclosure is shown. Fig.11 As shown, in the embodiment, the business scenario features and the input parameter features are graph-feature fused to determine the input parameter configuration, including:

[0144] Step S1102: Determine node characteristics of business scenario characteristics and node characteristics of input parameter characteristics;

[0145] Step S1104: splicing the node features of the business scenario features and the node features of the input parameter features to determine a first splicing feature;

[0146] Step S1106: Use a multi-layer perceptron to obtain a fusion feature expression for the first concatenated feature and determine the input parameter configuration.

[0147] The process of fusing business scenario features with input parameter features through graph features includes: extracting node features from business scenario features to determine node features of business scenario features; extracting node features from input parameter features to determine node features of input parameter features; splicing node features of business scenario features and node features of input parameter features to obtain a first splicing feature, using a multi-layer perceptron to obtain a fusion feature expression of the first splicing feature, and determining the input parameter configuration. The node feature extraction algorithm used in the above-mentioned node feature extraction of business scenario features and the node feature extraction of input parameter features can extract information related to the input parameter configuration from the attributes, structural position, and neighboring nodes connected to the node; for example, a node feature extraction algorithm based on a deep learning algorithm can be used to extract node features from business scenario features, map nodes to a low-dimensional space, thereby capturing the structure and attribute information of the node, and obtaining the node features of the business scenario features. The above-mentioned node feature extraction algorithm based on a deep learning algorithm can include: DeepWalk, Node2Vec, and GraphSAGE, etc.

[0148] Fig.12 FIG. 1 is a schematic diagram showing a process of determining output parameter configuration in an embodiment of the present disclosure. Fig.12 As shown, in the embodiment, the business scenario features and the output parameter features are graph-feature fused to determine the output parameter configuration, including:

[0149] Step S1202: Determine node characteristics of business scenario characteristics and node characteristics of output parameter characteristics;

[0150] Step S1204: splicing the node features of the business scenario features and the node features of the output parameter features to determine a second splicing feature;

[0151] Step S1206: using a multi-layer perceptron to obtain a fusion feature expression for the second concatenated feature and determine the output parameter configuration.

[0152] The process of fusing the business scenario features with the output parameter features through graph features includes: extracting node features from the business scenario features and determining node features of the business scenario features;

[0153] Performing node feature extraction on the output parameter feature to determine the node feature of the output parameter feature;

[0154] The node features of the business scenario features and the node features of the output parameter features are spliced ​​to determine the second spliced ​​features, and the second spliced ​​features are expressed by obtaining fusion features using a multi-layer perceptron to determine the output parameter configuration.

[0155] The node feature extraction algorithm used in the above-mentioned node feature extraction of business scenario features and output parameter features can extract information related to input parameter configuration from the attributes, structural position and neighboring nodes connected to the node;

[0156] For example, a node feature extraction algorithm based on a deep learning algorithm can be used to extract node features from output parameter features, map nodes to a low-dimensional space, and thereby capture the structure and attribute information of the nodes to obtain node features of the output parameter features. The above-mentioned node feature extraction algorithms based on deep learning algorithms may include: DeepWalk, Node2Vec, and GraphSAGE, etc.

[0157] Fig.13 The flowchart of graph convolution fusion of heterogeneous graphs of business scenarios, bipartite graphs of supporting capabilities and input parameters, and bipartite graphs of supporting capabilities and output parameters is shown. Fig.13 As shown, including:

[0158] ① Input the parameter requirement information of the target support capability under the target business scenario into the heterogeneous graph of the business scenario, and obtain the business scenario features after graph convolution. It is then used to perform graph feature fusion with ②③.

[0159] ②The parameter requirement information of the target support capability under the target business scenario is input into the bipartite graph of support capability and input parameters. After graph convolution, the input parameter features are obtained, which are then fused with the business scenario features in ① to obtain the input parameter configuration and input it into the input and output parameter recommendation module.

[0160] ③ The parameter requirement information of the target support capability under the target business scenario is input into the bipartite graph of support capability and output parameter. After graph convolution, the output parameter features are obtained, which are then fused with the business scenario features in ① to obtain the output parameter configuration and input into the input and output parameter recommendation module.

[0161] ④ Generate the output parameter configuration and input parameter configuration of the target support capability under the target business scenario in the input and output parameter recommendation module, eliminating the complexity of manual design.

[0162] Fig.14 A schematic diagram of a business scenario involving a new mobile phone installation is shown, such as Fig.14As shown, the three corresponding business scenarios of "before business acceptance", "filling in business information" and "business confirmation" involved in the new installation of a mobile phone have multiple business activities in each business scenario. Each business activity is constructed through different supporting capabilities, and each supporting capability requires corresponding input parameter configuration and output parameter configuration. The parameter configuration method of the embodiment of the present disclosure is used to construct a business scenario heterogeneous graph and a bipartite graph of supporting capabilities and parameters based on the existing business scenario parameter configuration information, and the business scenario heterogeneous graph and the bipartite graph of supporting capabilities and parameters are convolved based on the parameter requirement information of the target supporting capabilities in the target business scenario to obtain the parameter configuration of the target supporting capabilities in the target business scenario, thereby realizing the automatic generation of the parameter configuration of the supporting capabilities, thereby eliminating the need for designers to manually tailor the global parameter configuration, improving the accuracy of the parameter configuration design, freeing up the labor of business scenario designers, saving the labor and time costs of manually designing business supporting scenarios and supporting capabilities, lowering the threshold for business scenario and supporting capability design, and improving the efficiency of business scenario design.

[0163] This embodiment constructs a heterogeneous graph of business scenarios and a bipartite graph of supporting capabilities and parameters. After the graph structure is passed through a graph convolutional neural network (GCN) to obtain high-order features, the output parameters and inputs of the supporting capabilities are configured. This can enhance the feature expression between the supporting capabilities and the required output parameter input parameters, and improve the accuracy of parameter recommendations. At the same time, it can release the labor of business scenario designers and improve configuration efficiency.

[0164] Build a heterogeneous graph of business scenarios and a bipartite graph group of supporting capabilities, output parameters, and input parameters to achieve parameter recommendation of supporting capabilities. The heterogeneous graph of business scenarios includes the parameter configuration information of existing business scenarios. According to the parameter requirement information of the target supporting capabilities under the target business scenario, the bipartite graph of supporting capabilities and output parameters and the bipartite graph of supporting capabilities and input parameters are fused with the heterogeneous graph of business scenarios through graph features to obtain the input parameters and output parameters required for the target supporting capabilities. Save the labor and time cost of manually designing business supporting scenarios and supporting capabilities.

[0165] This embodiment has a wide range of application scenarios and can be applied to the design of operator business support scenarios and support capabilities. Business scenarios include government and enterprise marketing scenarios, online / offline marketing scenarios, store retail scenarios, channel operation scenarios, intelligent customer service scenarios, risk management scenarios, etc. Support capabilities include business opportunity management, customer management, product management, order management, channel management, customer service management, billing management, etc.

[0166] Taking the above-mentioned customer newly created business scenario as an example, the output parameters of the supporting capability "consistent customer query" include at least more than 40 output parameter fields such as custName (customer name), isRealname (real name identification), certNum (certificate number), regionId (region identification), custNumber (customer code), contactsInfos (contact information), statusDate (status date), custSubType (customer type). There are customers in the system whose customer ID numbers are correct but no real-name authentication is performed. When the marketing personnel query these customers, they do not need all the more than 40 output parameters of the supporting capability of "consistent customer query". They only need to cut out the three output parameter fields of custName (customer name), isRealname (real name identification), and certNum (certificate number). When the customer's certificate number is correct, but the real-name flag is 0 (i.e., no real-name authentication is performed), the real-name authentication operation is allowed for this customer. After using this embodiment, it is no longer necessary to manually cut out the required three output parameters from more than 40 output parameters, but the parameter configuration of the target supporting capability under the target business scenario is automatically generated by this embodiment. When the business scenario becomes customer information query, the output parameters of the supporting capability "consistent customer query" are automatically generated into custName (customer name) and contactsInfos (contact information) by the parameter configuration method of this embodiment.

[0167] The disclosed embodiments do not require designers to manually design each business scenario and supporting capability, including clipping the input parameters required for the target business scenario from the global input parameters of the supporting capability, and clipping the output parameters required for the target business scenario from the global output parameters of the supporting capability. By constructing two types of graphs, bipartite graphs and heterogeneous graphs, the input parameters and output parameters required for the target supporting capability under the target business scenario can be automatically recommended through the fusion of graph features of the two types of graphs, eliminating the labor and time of designers to manually design ever-changing business scenarios and thousands of supporting capabilities. Lower the threshold for operators' business support scenario design, save designers' labor and time costs, improve the efficiency of operators' marketing business scenario design, and obtain business opportunities and marketing opportunities.

[0168] It should be noted that the acquisition, storage, use, and processing of data in the technical solution disclosed in this disclosure are in compliance with the relevant provisions of national laws and regulations, and various types of data such as personal identity data, operation data, behavioral data, etc. related to individuals, customers, and groups obtained in the embodiments of this disclosure have all been authorized.

[0169] Based on the same inventive concept, the present disclosure also provides a parameter configuration device, as described in the following embodiments. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.

[0170] Fig.15 A schematic diagram of a parameter configuration device in an embodiment of the present disclosure is shown. Fig.15 As shown, the device comprises:

[0171] The information acquisition module 1501 is used to acquire the existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: the supporting capability corresponding to the existing business scenario, and the parameter configuration corresponding to the supporting capability;

[0172] A heterogeneous graph and bipartite graph determination module 1502 is used to determine a business scenario heterogeneous graph and a supporting capability and parameter bipartite graph according to existing business scenario parameter configuration information;

[0173] The parameter configuration determination module 1503 is used to perform graph convolution on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph according to the parameter requirement information of the target supporting capability in the target business scenario, and determine the parameter configuration of the target supporting capability in the target business scenario.

[0174] It should be noted that the above information acquisition module 1501, heterogeneous graph and bipartite graph determination module 1502 and parameter configuration determination module 1503 correspond to S302 to S304 in the method embodiment, and the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above method embodiment. It should be noted that the above modules as part of the device can be executed in a computer system such as a set of computer executable instructions.

[0175] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".

[0176] Refer to the following Fig.16 1600 according to this embodiment of the present disclosure is described. Fig.16 The electronic device 1600 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0177] like Fig.16As shown, the electronic device 1600 is in the form of a general computing device. The components of the electronic device 1600 may include but are not limited to: at least one processing unit 1610, at least one storage unit 1620, and a bus 1630 connecting different system components (including the storage unit 1620 and the processing unit 1610).

[0178] Among them, the storage unit stores a program code, and the program code can be executed by the processing unit 1610, so that the processing unit 1610 executes the steps described in the above "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 1610 can execute the following steps of the above method embodiment: obtaining existing business scenario parameter configuration information; the existing business scenario parameter configuration information includes: support capabilities corresponding to existing business scenarios, and parameter configurations corresponding to the support capabilities; determining a business scenario heterogeneous graph and a bipartite graph of support capabilities and parameters based on the existing business scenario parameter configuration information; performing graph convolution on the business scenario heterogeneous graph and the bipartite graph of support capabilities and parameters based on the parameter requirement information of the target support capabilities under the target business scenario, and determining the parameter configuration of the target support capabilities under the target business scenario.

[0179] The storage unit 1620 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 16201 and / or a cache storage unit 16202 , and may further include a read-only storage unit (ROM) 16203 .

[0180] The storage unit 1620 may also include a program / utility 16204 having a set (at least one) of program modules 16205, such program modules 16205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0181] Bus 1630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0182] The electronic device 1600 may also communicate with one or more external devices 1640 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 1600, and / or communicate with any device that enables the electronic device 1600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 1650. Furthermore, the electronic device 1600 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 1660. As shown, the network adapter 1660 communicates with other modules of the electronic device 1600 via a bus 1630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0183] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0184] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart may be implemented as a computer program product, which includes: a computer program, which implements the above parameter configuration method when executed by a processor.

[0185] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, which may be a readable signal medium or a readable storage medium. A program product capable of implementing the above method of the present disclosure is stored thereon. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary implementations of the present disclosure described in the above “Exemplary Method” section of this specification.

[0186] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0187] In the present disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0188] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0189] In a specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0190] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0191] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0192] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0193] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.

Claims

1. A parameter configuration method, characterized in that: include: Obtain existing business scenario parameter configuration information; The existing business scenario parameter configuration information includes: support capabilities corresponding to the existing business scenarios, and parameter configurations corresponding to the support capabilities; Determine the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph based on the existing business scenario parameter configuration information; According to the parameter requirement information of the target support capability under the target business scenario, graph convolution is performed on the business scenario heterogeneous graph and the support capability and parameter bipartite graph to determine the parameter configuration of the target support capability under the target business scenario.

2. The parameter configuration method according to claim 1, characterized in that: According to the existing business scenario parameter configuration information, determine the business scenario heterogeneous graph, including: Parsing the supporting capability corresponding to the existing business scenario, determining the existing business scenario as a first node, determining the supporting capability corresponding to the business scenario as a second node, and determining the corresponding relationship between the business scenario and the supporting capability as an edge between the first node and the second node; parsing the parameter configuration corresponding to the supporting capability, determining the parameter configuration corresponding to the supporting capability as a third node, and determining the corresponding relationship between the supporting capability and the parameter configuration as an edge between the second node and the third node; A business scenario heterogeneous graph is determined based on the first node, the edge between the first node and the second node, the second node, the edge between the second node and the third node, and the third node.

3. The parameter configuration method according to claim 1, characterized in that: Based on the existing business scenario parameter configuration information, determine the supporting capability and parameter bipartite graph, including: Constructing a first vertex set according to the supporting capability corresponding to the existing business scenario; the first vertex set includes a first vertex determined according to the supporting capability; According to the parameter configuration corresponding to the supporting capability, a second vertex set is constructed; the second vertex set includes a second vertex determined according to the parameter configuration; Determine an edge set between the first vertex set and the second vertex set according to the correspondence between the supporting capability and the parameter configuration; the edges included in the edge set respectively connect a first vertex in the first vertex set and a second vertex in the second vertex set; A supporting capacity and parameter bipartite graph is determined according to the first vertex set, the second vertex set and the edge set.

4. The parameter configuration method according to claim 3, characterized in that: The parameter configuration includes: input parameter configuration and output parameter configuration; According to the parameter configuration corresponding to the support capability, a second vertex set is constructed, including: Determining a second input parameter vertex according to the input parameter configuration; Determining a second output parameter vertex according to the output parameter configuration; A second vertex set is constructed according to the second input parameter vertex and the second output parameter vertex.

5. The parameter configuration method according to claim 4, characterized in that: The edge set includes: a first edge connecting a first vertex in the first vertex set and a vertex of the second input parameter, and a second edge connecting a first vertex in the first vertex set and a vertex of the second output parameter; Determining a bipartite graph of support capability and parameters according to the first vertex set, the second vertex set, and the edge set includes: Connecting the first vertex in the first vertex set to the second input parameter vertex through the first edge to construct a bipartite graph of supporting capability and input parameter; Connecting the first vertex in the first vertex set to the second output parameter vertex through the second edge to construct a bipartite graph of supporting capability and output parameter; The supporting capability and input parameter bipartite graph and the supporting capability and output parameter bipartite graph are determined as supporting capability and parameter bipartite graph.

6. The parameter configuration method according to claim 1, characterized in that: According to the parameter requirement information of the target support capability in the target business scenario, graph convolution is performed on the business scenario heterogeneous graph and the support capability and parameter bipartite graph to determine the parameter configuration of the target support capability in the target business scenario, including: Inputting parameter requirement information of target support capability under target business scenario into the business scenario heterogeneous graph, performing graph convolution, and determining business scenario characteristics; Inputting parameter requirement information of target support capability under target business scenario into the support capability and parameter bipartite graph, performing graph convolution, and determining parameter features; According to the business scenario characteristics and the parameter characteristics, parameter configuration of the target support capability under the target business scenario is determined.

7. The parameter configuration method according to claim 6, characterized in that: The supporting capability and parameter bipartite graph includes: supporting capability and input parameter bipartite graph, supporting capability and output parameter bipartite graph; Inputting parameter requirement information of the target support capability under the target business scenario into the support capability and parameter bipartite graph, performing graph convolution, and determining parameter features, including: Input the parameter requirement information of the target support capability under the target business scenario into the bipartite graph of support capability and input parameters, perform graph convolution, and determine the input parameter characteristics; Input the parameter requirement information of the target support capability under the target business scenario into the bipartite graph of support capability and output parameter, perform graph convolution, and determine the output parameter characteristics; The input parameter characteristic and the output parameter characteristic are determined as parameter characteristics.

8. The parameter configuration method according to claim 7, characterized in that: Determining parameter configuration of target support capability under target business scenario according to the business scenario characteristics and the parameter characteristics includes: Performing graph feature fusion on the business scenario features and the input parameter features to determine the input parameter configuration; Performing graph feature fusion on the business scenario features and the output parameter features to determine the output parameter configuration; According to the input parameter configuration and the output parameter configuration, a parameter configuration of a target supporting capability in a target business scenario is determined.

9. The parameter configuration method according to claim 8, characterized in that: The business scenario feature and the input parameter feature are subjected to graph feature fusion to determine the input parameter configuration, including: Determine the node characteristics of the business scenario characteristics and the node characteristics of the input parameter characteristics; Splicing the node feature of the business scenario feature and the node feature of the input parameter feature to determine a first splicing feature; The first concatenated features are expressed by a multi-layer perceptron to obtain fusion features and determine input parameter configuration.

10. The parameter configuration method according to claim 8, characterized in that: The business scenario feature and the output parameter feature are subjected to graph feature fusion to determine the output parameter configuration, including: Determine the node characteristics of the business scenario characteristics and the node characteristics of the output parameter characteristics; Splicing the node feature of the business scenario feature and the node feature of the output parameter feature to determine a second splicing feature; The second concatenated features are expressed by a multi-layer perceptron to obtain fusion features and determine output parameter configuration.

11. A parameter configuration device, characterized in that: include: Information acquisition module, used to obtain existing business scenario parameter configuration information; The existing business scenario parameter configuration information includes: support capabilities corresponding to the existing business scenarios, and parameter configurations corresponding to the support capabilities; A heterogeneous graph and bipartite graph determination module is used to determine a business scenario heterogeneous graph and a supporting capability and parameter bipartite graph based on existing business scenario parameter configuration information; The parameter configuration determination module is used to perform graph convolution on the business scenario heterogeneous graph and the supporting capability and parameter bipartite graph according to the parameter requirement information of the target supporting capability under the target business scenario, so as to determine the parameter configuration of the target supporting capability under the target business scenario.

12. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to execute the parameter configuration method according to any one of claims 1 to 10 by executing the executable instructions.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the parameter configuration method according to any one of claims 1 to 10 is implemented.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the parameter configuration method according to any one of claims 1 to 10 is implemented.

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