Selection scheme generation method, device, equipment and medium based on big data technology

Abstract

The present application relates to a selection scheme generation method, device, computer equipment, storage medium and computer program product based on big data technology, which can be used in the field of big data technology. The method includes: displaying a query interface corresponding to the target selection object type according to the target selection object type selected by the user; obtaining the selection object parameters input by the user on the query interface; generating candidate selection object information matching the selection object parameters according to the selection object database; selecting the target selection object information from the candidate selection object information; and generating a corresponding selection scheme according to the target selection object information. The use of this method can improve the efficiency of generating selection schemes.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and in particular to a method, device, computer equipment, storage medium and computer program product for generating a selection plan based on big data technology. Background Art

[0002] With the development of information technology, by analyzing the information of different objects, the appropriate selection object can be selected. Therefore, how to efficiently generate selection plans has become an important research direction.

[0003] Traditional technology usually screens the selection objects through manual search and comparison to generate a selection plan; however, generating a selection plan in this way requires a lot of manual processing time, resulting in low efficiency in generating the selection plan. Summary of the invention

[0004] Based on this, it is necessary to provide a selection scheme generation method, device, computer equipment, computer-readable storage medium and computer program product based on big data technology that can improve the efficiency of generating selection schemes in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for generating a selection scheme based on big data technology. The method comprises:

[0006] According to the target selection object type selected by the user, a query interface corresponding to the target selection object type is displayed;

[0007] Acquire the selection object parameters input by the user on the query interface;

[0008] Generating candidate selection object information matching the selection object parameters according to the selection object database;

[0009] Selecting target selection object information from the candidate selection object information;

[0010] According to the target selection object information, a corresponding selection plan is generated.

[0011] In one embodiment, after generating a corresponding selection scheme according to the target selection object information, the method further includes:

[0012] Determining a connection relationship between target selection objects corresponding to the target selection object information;

[0013] Generate a basic drawing according to the connection relationship;

[0014] The basic drawing is used as the installation drawing corresponding to the selected solution.

[0015] In one of the embodiments, before generating candidate selection object information matching the selection object parameters according to the selection object database, the method further includes:

[0016] Construct the knowledge graph corresponding to the selection object database;

[0017] The step of generating candidate selection object information matching the selection object parameters according to the selection object database includes:

[0018] According to the knowledge graph corresponding to the selection object database, candidate selection object information matching the selection object parameters is generated.

[0019] In one of the embodiments, before generating candidate selection object information matching the selection object parameters according to the selection object database, the method further includes:

[0020] Using the selection object database, create training data for the selection object;

[0021] Using the training data, a model for generating information of a type selection object to be trained is trained to obtain a trained model for generating information of a type selection object;

[0022] The step of generating candidate selection object information matching the selection object parameters according to the selection object database further includes:

[0023] The selection object parameters are input into the trained selection object information generation model to obtain candidate selection object information matching the selection object parameters.

[0024] In one embodiment, selecting target selection object information from the candidate selection object information includes:

[0025] Identify the comprehensive indicator data corresponding to the candidate selection object information; the comprehensive indicator data includes performance indicator data and resource indicator data;

[0026] The target selection object information is selected from the candidate selection object information according to the comprehensive indicator data by using the selection object information selection model.

[0027] In one embodiment, selecting target selection object information from the candidate selection object information further includes:

[0028] According to the candidate selection object information, generating corresponding candidate selection object information options;

[0029] According to the candidate selection object information option selected by the user, target selection object information is selected from the candidate selection object information.

[0030] In one embodiment, the obtaining of the selection object parameters input by the user on the query interface includes:

[0031] Acquire the original selection object parameters input by the user on the query interface;

[0032] According to the preset parameter range conditions, the original selection object parameters are identified to obtain the identification results of the original selection object parameters;

[0033] When the recognition result indicates passing, the original selection object parameters are used as selection object parameters, or, when the recognition result indicates failing, prompt information is generated; the prompt information is used to prompt the user to re-enter new selection object parameters.

[0034] In a second aspect, the present application also provides a device for generating a selection scheme based on big data technology. The device comprises:

[0035] The interface display module is used to display the query interface corresponding to the target selection object type according to the target selection object type selected by the user;

[0036] A parameter acquisition module, used to acquire the selection object parameters input by the user on the query interface;

[0037] An information generation module, used to generate candidate selection object information matching the selection object parameters according to the selection object database;

[0038] An information selection module is used to select target selection object information from the candidate selection object information;

[0039] The solution generation module is used to generate a corresponding selection solution according to the target selection object information.

[0040] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0041] According to the target selection object type selected by the user, a query interface corresponding to the target selection object type is displayed;

[0042] Acquire the selection object parameters input by the user on the query interface;

[0043] Generating candidate selection object information matching the selection object parameters according to the selection object database;

[0044] Selecting target selection object information from the candidate selection object information;

[0045] According to the target selection object information, a corresponding selection plan is generated.

[0046] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0047] According to the target selection object type selected by the user, a query interface corresponding to the target selection object type is displayed;

[0048] Acquire the selection object parameters input by the user on the query interface;

[0049] Generating candidate selection object information matching the selection object parameters according to the selection object database;

[0050] Selecting target selection object information from the candidate selection object information;

[0051] According to the target selection object information, a corresponding selection plan is generated.

[0052] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0053] According to the target selection object type selected by the user, a query interface corresponding to the target selection object type is displayed;

[0054] Acquire the selection object parameters input by the user on the query interface;

[0055] Generating candidate selection object information matching the selection object parameters according to the selection object database;

[0056] Selecting target selection object information from the candidate selection object information;

[0057] According to the target selection object information, a corresponding selection plan is generated.

[0058] The above-mentioned selection scheme generation method, device, computer equipment, storage medium and computer program product based on big data technology display a query interface corresponding to the target selection object type selected by the user; obtain the selection object parameters input by the user on the query interface; generate candidate selection object information matching the selection object parameters according to the selection object database; select the target selection object information from the candidate selection object information; and generate a corresponding selection scheme according to the target selection object information. The scheme displays a corresponding query interface according to the target selection object type selected by the user; obtains the selection object parameters input by the user on the query interface; generates candidate selection object information matching the selection object parameters according to the selection object database; selects the target selection object information from the candidate selection object information; and automatically generates a corresponding selection scheme according to the target selection object information; and realizes the automatic generation of a selection scheme that meets the requirements, thereby facilitating the improvement of the efficiency and accuracy of generating a selection scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 A schematic diagram of a flow chart of a method for generating a selection scheme based on big data technology in one embodiment;

[0061] Figure 2 A schematic flow chart of steps for generating drawings in one embodiment;

[0062] Figure 3 A schematic diagram of a flow chart of steps for selecting target selection object information in one embodiment;

[0063] Figure 4 It is a structural block diagram of a device for generating a selection scheme based on big data technology in one embodiment;

[0064] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0065] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0066] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0067] In an exemplary embodiment, Figure 1 As shown, a method for generating a selection scheme based on big data technology is provided. This embodiment uses the method applied to a terminal as an example. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be but is not limited to various personal computers, laptops, smart phones, tablet computers, etc.; the server can be implemented with an independent server or a server cluster composed of multiple servers. In this embodiment, the method includes the following steps:

[0068] Step S101, according to the target selection object type selected by the user, displaying a query interface corresponding to the target selection object type.

[0069] The selection object type may be the type of object that the user needs to select during the selection process, such as a device, a chip, an operating system, a communication solution, and the like.

[0070] The target selection object type may be one of the selection object types.

[0071] The query interface may be an interface displayed by the terminal to the user, for the user to input parameters of the selected object and perform query operations.

[0072] Optionally, the terminal determines the type of query interface to be displayed according to the target selection object type selected by the user, and displays the corresponding query interface according to the query interface type.

[0073] Step S102, obtaining the selection object parameters input by the user on the query interface.

[0074] The selection object parameters may be parameters input by the user on the query interface for screening the selection objects, such as performance parameters, attribute parameters, etc.

[0075] Optionally, the terminal monitors the user's operation on the query interface. When the user inputs the selection object parameters on the query interface, the terminal will obtain the selection object parameters input by the user in real time.

[0076] Step S103: generating candidate selection object information matching the selection object parameters according to the selection object database.

[0077] Among them, the selection object database can be a database built based on big data technology, which contains information of various selection objects, such as name, model, resource consumption, production information, etc.

[0078] Among them, the candidate selection object information can be the information of the selection object that matches the parameters obtained by matching in the selection object database based on the selection object parameters input by the user. For example, the candidate selection object information can be the information of the candidate selection object, wherein the information of the candidate selection object can be the name, model, resource consumption, production information, historical failure rate, reliability and other information of the candidate selection object.

[0079] Optionally, the terminal performs matching and query in a selection object database according to the selection object parameters input by the user, and generates candidate selection object information matching the selection object parameters.

[0080] Step S104: Select target selection object information from candidate selection object information.

[0081] The target selection object information may be information about a selection object in the candidate selection object information.

[0082] Optionally, the terminal selects target selection object information that is finally selected by the user or determined according to a recommendation algorithm from the candidate selection object information.

[0083] Step S105: Generate a corresponding selection plan according to the target selection object information.

[0084] Among them, the selection plan can be a corresponding plan generated according to the target selection object information selected by the user, including the configuration, connection method, etc. of the selection object. For example, the selection plan can be a selection plan for all objects in a complete set of equipment or system.

[0085] Optionally, after determining each target selection object information, the terminal generates a selection scheme corresponding to each target selection object information according to the determined each target selection object information.

[0086] In the above-mentioned selection scheme generation method based on big data technology, according to the target selection object type selected by the user, a query interface corresponding to the target selection object type is displayed; the selection object parameters input by the user on the query interface are obtained; according to the selection object database, candidate selection object information matching the selection object parameters is generated; from the candidate selection object information, the target selection object information is selected; according to the target selection object information, a corresponding selection scheme is generated. This scheme displays a corresponding query interface according to the target selection object type selected by the user; the selection object parameters input by the user on the query interface are obtained; according to the selection object database, candidate selection object information matching the selection object parameters is generated; the target selection object information is selected from the candidate selection object information; according to the target selection object information, a corresponding selection scheme is automatically generated; and selection schemes that meet the requirements are automatically generated, thereby facilitating the improvement of the efficiency and accuracy of generating selection schemes.

[0087] In an exemplary embodiment, Figure 2 As shown, the above step S105, after generating the corresponding selection scheme according to the target selection object information, also includes the step of generating drawings, which specifically includes the following contents:

[0088] Step S201, determining the connection relationship between target selection objects corresponding to the target selection object information;

[0089] Step S202, generating a basic drawing according to the connection relationship;

[0090] Step S203: Use the basic drawing as the installation drawing corresponding to the selected solution.

[0091] The connection relationship may be the correlation and dependency between the various selection objects in the selection scheme. These relationships may be physical connections, such as circuit connections between devices, or logical relationships, such as the dependency between an operating system and an application.

[0092] Among them, the basic drawing can be a technical drawing used to describe the connection method and layout between the various selection objects in the selection plan. The basic drawing can include circuit diagrams, wiring diagrams, etc., to guide the implementation and installation of the selection plan.

[0093] Among them, the installation drawings can be drawings that are further refined and improved based on the basic drawings, and are used to guide the actual installation and deployment of the selected plan. The installation drawings will contain more detailed information, such as specific dimensions, locations, connection methods, etc., to ensure that the selected plan can be implemented and implemented correctly.

[0094] Optionally, after generating a selection plan based on the target selection object information, the terminal will analyze the object properties, dependencies and other information of each selection object in the selection plan; automatically determine the connection relationship between the objects in the selection plan based on the object properties, dependencies and other information; automatically draw basic drawings based on standard drawing generation rules using these relationship information (connection relationship information); and on the basis of the basic drawings, add more details based on the needs of the actual installation environment to form installation drawings.

[0095] The technical solution provided in this embodiment is conducive to more efficient and accurate generation of corresponding installation drawings based on the connection relationship between target selection objects, thereby facilitating improving the efficiency and accuracy of generating installation drawings corresponding to the selection scheme.

[0096] In an exemplary embodiment, the above-mentioned step S103, before generating candidate selection object information matching the selection object parameters according to the selection object database, further includes the step of constructing a knowledge graph, which specifically includes the following contents: constructing a knowledge graph corresponding to the selection object database; In step S103, generating candidate selection object information matching the selection object parameters according to the selection object database, which specifically includes the following contents: generating candidate selection object information matching the selection object parameters according to the knowledge graph corresponding to the selection object database.

[0097] Among them, the knowledge graph can be a graphical structure for representing and storing knowledge, which contains various objects in the selection object database and their attributes, relationships and other information, and is used to help generate candidate selection object information that matches the selection object parameters.

[0098] Optionally, the terminal constructs a corresponding knowledge graph based on the selection object database. In the process of constructing the knowledge graph, the terminal will analyze the selection object database, extract the basic information such as the name, attributes, parameters, etc. of the selection objects in the selection object database, and record various relationships between the selection objects, such as hierarchical relationships, attribute relationships, etc., to form a graphic structure with rich knowledge connotations, thereby constructing a knowledge graph corresponding to the selection object database; according to the selection object parameters input by the user, using the previously constructed knowledge graph, locate the relevant object information that matches the selection object parameters in the knowledge graph as the candidate selection object information that matches the selection object parameters.

[0099] The technical solution provided in this embodiment generates candidate selection object information that matches the selection object parameters based on the knowledge graph corresponding to the selection object database, which is conducive to more efficient and accurate generation of candidate selection object information that matches the selection object parameters, thereby facilitating improving the efficiency and accuracy of generating selection solutions.

[0100] In an exemplary embodiment, the above-mentioned step S103, before generating candidate selection object information matching the selection object parameters according to the selection object database, further includes the step of training the model, which specifically includes the following contents: using the selection object database to create training data for the selection object; using the training data to train the selection object information generation model to be trained to obtain the trained selection object information generation model; in step S103, generating candidate selection object information matching the selection object parameters according to the selection object database, which specifically includes the following contents: inputting the selection object parameters into the trained selection object information generation model to obtain candidate selection object information matching the selection object parameters.

[0101] Among them, the training data can be a data set used to train the selection object information generation model, which contains various attributes and parameter information of the selection object; by learning the training data, the model can learn the association rules between the selection object parameters and the candidate selection object information.

[0102] Among them, the selection object information generation model to be trained can be a machine learning model such as a neural network.

[0103] The trained selection object information generation model may be a model obtained through training data, and is used to generate candidate selection object information that matches the input selection object parameters.

[0104] Optionally, the terminal uses a selection object database to create training data for the selection object, wherein the training data includes various attributes and parameter information of the selection object, which is used to train a subsequent selection object information generation model; the created training data is used to train the selection object information generation model to be trained, wherein, through training, the model learns the association rules between the selection object parameters and the candidate selection object information, so that the trained model can generate candidate selection object information that matches the input selection object parameters; the terminal inputs the selection object parameters into the trained selection object information generation model, and the trained selection object information generation model generates and outputs candidate selection object information that matches the selection object parameters based on the input selection object parameters and the knowledge and rules obtained from previous training.

[0105] The technical solution provided in this embodiment generates candidate selection object information that matches the selection object parameters through a trained selection object information generation model, which is conducive to obtaining candidate selection object information that matches the selection object parameters more efficiently and accurately, thereby facilitating improving the efficiency and accuracy of generating selection solutions.

[0106] In an exemplary embodiment, Figure 3As shown, in step S104, target selection object information is selected from candidate selection object information, which specifically includes the following contents:

[0107] Step S301, identifying comprehensive indicator data corresponding to candidate selection object information; the comprehensive indicator data includes performance indicator data and resource indicator data;

[0108] Step S302 , using the selection object information selection model, and selecting target selection object information from candidate selection object information according to comprehensive indicator data.

[0109] Among them, the comprehensive indicator data can be data used to evaluate the comprehensive performance of candidate selection objects, including performance indicator data and resource indicator data.

[0110] Among them, performance indicator data can be used to reflect the performance of the selected object, such as speed, accuracy, etc.

[0111] Among them, resource indicator data can be used to reflect the performance of the selected object in resource utilization, such as power consumption, storage space, etc., and resource indicator data can also be used to represent data on resource consumption.

[0112] Among them, the selection object information selection model can be a model that evaluates and ranks candidate selection object information based on comprehensive indicator data. The selection object information selection model can comprehensively consider performance indicators and resource indicators based on preset evaluation algorithms and weights, and select the target selection object information that best meets the requirements from the candidate selection object information; for example, the selection object information selection model can be a model built based on a recommendation algorithm (such as a deep learning algorithm).

[0113] Optionally, the terminal identifies comprehensive indicator data corresponding to each candidate selection object from the candidate selection object information; inputs the comprehensive indicator data corresponding to the candidate selection object information into a selection object information selection model, so that the selection object information selection model selects target selection object information from the candidate selection object information, and obtains the target selection object information output by the selection object information selection model.

[0114] The technical solution provided in this embodiment selects target selection object information from candidate selection object information through a selection object information selection model, which is conducive to obtaining the target selection object information more efficiently and accurately, thereby facilitating improving the efficiency and accuracy of generating selection solutions.

[0115] In an exemplary embodiment, in step S104, target selection object information is selected from the candidate selection object information, which specifically includes the following contents: generating corresponding candidate selection object information options based on the candidate selection object information; and selecting target selection object information from the candidate selection object information based on the candidate selection object information options selected by the user.

[0116] The candidate selection object information options may be options for each candidate object information presented (displayed) to the user for selection.

[0117] Optionally, the terminal generates corresponding candidate selection object information options based on the candidate selection object information; presents the generated candidate selection object information options to the user for selection, so that the user selects from the presented candidate selection object information options; and identifies corresponding object information from the candidate selection object information based on the candidate selection object information options selected by the user as the target selection object information.

[0118] The technical solution provided in this embodiment determines the target selection object information according to the candidate selection object information options selected by the user, which is conducive to obtaining the target selection object information more accurately, thereby facilitating improving the accuracy of generating selection solutions.

[0119] In an exemplary embodiment, in step S102, the selection object parameters input by the user on the query interface are obtained, specifically including the following contents: obtaining the original selection object parameters input by the user on the query interface; identifying the original selection object parameters according to preset parameter range conditions to obtain the identification results of the original selection object parameters; when the identification result indicates a pass, using the original selection object parameters as the selection object parameters, or, when the identification result indicates a fail, generating a prompt message; the prompt message is used to prompt the user to re-enter new selection object parameters.

[0120] The original selection object parameters may be selection object parameters input by the user on the query interface and have not yet been verified and identified.

[0121] The preset parameter range condition may be a pre-set reasonable range condition of the selection object parameter, which is used to verify whether the parameters input by the user meet the requirements.

[0122] The recognition result may be a result obtained after verifying the original selection object parameters according to a preset parameter range condition, and may be expressed as pass or fail.

[0123] The prompt information may be information automatically generated when the original selection object parameters input by the user do not meet the preset range conditions, and is used to prompt the user to re-enter new selection object parameters.

[0124] Optionally, the terminal obtains original selection object parameters entered by the user on the query interface; identifies the original selection object parameters according to preset parameter range conditions, for example, verifies the parameters entered by the user to determine whether they meet the preset range conditions; if the recognition result indicates pass, that is, the selection object parameters entered by the user meet the preset range conditions, the terminal uses the original selection object parameters as the selection object parameters; if the recognition result indicates fail, that is, the selection object parameters entered by the user do not meet the preset range conditions, the terminal generates a prompt message to prompt the user to re-enter new selection object parameters, and after the user re-enters the new selection object parameters, the terminal re-obtains the new selection object parameters re-entered by the user, and repeats the above-mentioned process of identifying according to the preset parameter range conditions until the recognition result of the latest selection object parameters re-entered by the user indicates pass, then the latest selection object parameters re-entered by the user are used as the selection object parameters.

[0125] The technical solution provided in this embodiment is conducive to obtaining accurate selection object parameters that meet preset conditions by identifying the original selection object parameters according to preset parameter range conditions, thereby facilitating improving the accuracy of generating selection solutions.

[0126] The following is an application example to illustrate the selection scheme generation method based on big data technology provided by this application. This application example uses the method applied to a terminal as an example, and the main steps include:

[0127] In the first step, the terminal determines the target selection object selected by the user among a variety of selection objects (such as devices, chips, operating systems, communication solutions, etc.); different selection objects correspond to different query interfaces.

[0128] In the second step, the terminal obtains the selection object parameters input by the user on the query interface of the target selection object; for example, performance parameters, attribute parameters, etc.; of course, when the selection object parameters input by the user do not meet the preset range, the user will be reminded to re-enter.

[0129] In the third step, the terminal generates adapted selection object information options according to the selection object parameters in combination with the database (i.e., a database built based on big data technology, such as a selection object library), including the selection object name, model, current resource consumption, date, production information, historical resource consumption, historical failure rate, cost performance, reliability, etc.; for example, in combination with the knowledge graph corresponding to the selection object library, generates selection object information options adapted to the selection object parameters; or, uses the database to create training data, and then uses the training data to train the neural network so that the trained neural network has the ability to select, and uses the trained neural network to output selection object information options adapted to the selection object parameters.

[0130] In the fourth step, the terminal generates a complete set of selection schemes and basic drawings based on the selection object information selected by the user for the selection object information option (such as the selected model, production information, etc.). Of course, the user can modify the selection object information, and the corresponding selection scheme and basic drawings will be updated accordingly, that is, after the user modifies the selection object information, the selection scheme and basic drawings are automatically updated; the basic drawings provide references for various objects in the installation selection scheme, such as which two objects are connected together.

[0131] In the fifth step, after obtaining the selection object information options, the terminal can also automatically recommend the corresponding selection plan based on comprehensive indicators (maximizing performance, minimizing resource consumption, etc.) and combined with recommendation algorithms (such as deep learning algorithms).

[0132] The technical solution provided by this application example can automatically generate a selection plan that meets the requirements, thereby helping to improve the efficiency and accuracy of generating the selection plan.

[0133] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0134] Based on the same inventive concept, the embodiment of the present application also provides a selection solution generation device based on big data technology for implementing the selection solution generation method based on big data technology involved above. The implementation solution for solving the problem provided by the device is similar to the implementation solution recorded in the above method, so the specific limitations in one or more embodiments of the selection solution generation device based on big data technology provided below can refer to the limitations of the selection solution generation method based on big data technology above, and will not be repeated here.

[0135] In an exemplary embodiment, Figure 4 As shown, a device for generating a selection scheme based on big data technology is provided, and the device 400 may include:

[0136] The interface display module 401 is used to display a query interface corresponding to the target selection object type according to the target selection object type selected by the user;

[0137] The parameter acquisition module 402 is used to acquire the selection object parameters input by the user on the query interface;

[0138] The information generation module 403 is used to generate candidate selection object information matching the selection object parameters according to the selection object database;

[0139] The information selection module 404 is used to select target selection object information from candidate selection object information;

[0140] The solution generation module 405 is used to generate a corresponding selection solution according to the target selection object information.

[0141] In an exemplary embodiment, the device 400 also includes: a drawing generation module, which is used to determine the connection relationship between the target selection objects corresponding to the target selection object information; generate a basic drawing according to the connection relationship; and use the basic drawing as an installation drawing corresponding to the selection scheme.

[0142] In an exemplary embodiment, the device 400 also includes: a graph construction module, which is used to construct a knowledge graph corresponding to the selection object database; an information generation module 403, which is also used to generate candidate selection object information matching the selection object parameters based on the knowledge graph corresponding to the selection object database.

[0143] In an exemplary embodiment, the device 400 also includes: a model training module, which is used to create training data for selection objects using a selection object database; using the training data to train a selection object information generation model to be trained to obtain a trained selection object information generation model; an information generation module 403, which is also used to input selection object parameters into the trained selection object information generation model to obtain candidate selection object information that matches the selection object parameters.

[0144] In an exemplary embodiment, the information selection module 404 is also used to identify comprehensive indicator data corresponding to the candidate selection object information; the comprehensive indicator data includes performance indicator data and resource indicator data; and the selection object information selection model is used to select the target selection object information from the candidate selection object information according to the comprehensive indicator data.

[0145] In an exemplary embodiment, the information selection module 404 is further used to generate corresponding candidate selection object information options according to the candidate selection object information; and select target selection object information from the candidate selection object information according to the candidate selection object information options selected by the user.

[0146] In an exemplary embodiment, the parameter acquisition module 402 is also used to obtain the original selection object parameters input by the user on the query interface; the original selection object parameters are identified according to the preset parameter range conditions to obtain the identification results of the original selection object parameters; when the identification result indicates a pass, the original selection object parameters are used as the selection object parameters, or, when the identification result indicates a fail, a prompt message is generated; the prompt message is used to prompt the user to re-enter new selection object parameters.

[0147] Each module in the above-mentioned selection scheme generation device based on big data technology can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0148] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a selection scheme generation method based on big data technology is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0149] Those skilled in the art will understand that Figure 5The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0150] In an exemplary embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0151] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0152] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0154] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for generating a selection scheme based on big data technology, characterized in that: The method comprises: Determine the type of query interface to be displayed according to the target selection object type selected by the user, and display the query interface corresponding to the target selection object type according to the query interface type; the target selection object type is one of the selection object types; the selection object types include devices, chips, operating systems and communication solutions; Acquire the selection object parameters input by the user on the query interface; Generate candidate selection object information matching the selection object parameters according to the selection object database; the selection object database is a database built based on big data technology; the candidate selection object information includes the name, model, resource consumption, production information, historical failure rate and reliability of the candidate selection object; Selecting target selection object information from the candidate selection object information; According to each of the target selection object information, a selection scheme corresponding to each of the target selection object information is generated; the selection scheme is a selection scheme for all objects in a complete set of equipment or system; Analyze the object attributes and dependency relationships of each selection object in the selection scheme; Automatically determine the connection relationship between the various selection objects in the selection scheme according to the object attributes and dependency relationships of the various selection objects in the selection scheme; the connection relationship includes the circuit connection between the devices and the dependency relationship between the operating system and the application program; According to standard drawing generation rules, basic drawings are automatically drawn using the connection relationship between the various selection objects in the selection scheme; the basic drawings are used to describe the connection mode and layout between the various selection objects in the selection scheme, and the basic drawings include wiring diagrams; On the basis of the basic drawings, more details are added according to the requirements of the actual installation environment to form installation drawings corresponding to the selected solution.

2. The method according to claim 1, characterized in that The selection object parameters include performance parameters and attribute parameters.

3. The method according to claim 1, characterized in that Before generating candidate selection object information matching the selection object parameters according to the selection object database, the method further includes: Construct the knowledge graph corresponding to the selection object database; The step of generating candidate selection object information matching the selection object parameters according to the selection object database includes: According to the knowledge graph corresponding to the selection object database, candidate selection object information matching the selection object parameters is generated.

4. The method according to claim 1, characterized in that Before generating candidate selection object information matching the selection object parameters according to the selection object database, the method further includes: Using the selection object database, create training data for the selection object; Using the training data, a model for generating information of a type selection object to be trained is trained to obtain a trained model for generating information of a type selection object; The step of generating candidate selection object information matching the selection object parameters according to the selection object database further includes: The selection object parameters are input into the trained selection object information generation model to obtain candidate selection object information matching the selection object parameters.

5. The method according to claim 1, characterized in that The step of selecting target selection object information from the candidate selection object information includes: Identify the comprehensive indicator data corresponding to the candidate selection object information; the comprehensive indicator data includes performance indicator data and resource indicator data; The target selection object information is selected from the candidate selection object information according to the comprehensive indicator data by using the selection object information selection model.

6. The method according to claim 1, characterized in that The step of selecting target selection object information from the candidate selection object information further includes: According to the candidate selection object information, generating corresponding candidate selection object information options; According to the candidate selection object information option selected by the user, target selection object information is selected from the candidate selection object information.

7. The method according to any one of claims 1 to 6, characterized in that: The obtaining of the selection object parameters input by the user on the query interface includes: Acquire the original selection object parameters input by the user on the query interface; According to the preset parameter range conditions, the original selection object parameters are identified to obtain the identification results of the original selection object parameters; When the recognition result indicates passing, the original selection object parameters are used as selection object parameters, or, when the recognition result indicates failing, prompt information is generated; the prompt information is used to prompt the user to re-enter new selection object parameters.

8. A selection scheme generation device based on big data technology, characterized in that: The device comprises: The interface display module is used to determine the query interface type to be displayed according to the target selection object type selected by the user, and display the query interface corresponding to the target selection object type according to the query interface type; the target selection object type is one of the selection object types; the selection object types include devices, chips, operating systems and communication solutions; A parameter acquisition module, used to acquire the selection object parameters input by the user on the query interface; An information generation module is used to generate candidate selection object information matching the selection object parameters according to a selection object database; the selection object database is a database constructed based on big data technology; the candidate selection object information includes the name, model, resource consumption, production information, historical failure rate and reliability of the candidate selection object; An information selection module is used to select target selection object information from the candidate selection object information; A scheme generating module is used to generate a selection scheme corresponding to each target selection object information according to each target selection object information; the selection scheme is a selection scheme for all objects in a complete set of equipment or system; A drawing generation module is used to analyze the object properties and dependency relationships of each selection object in the selection scheme; according to the object properties and dependency relationships of each selection object in the selection scheme, automatically determine the connection relationship between each selection object in the selection scheme; the connection relationship includes the circuit connection between the devices and the dependency relationship between the operating system and the application program; according to standard drawing generation rules, basic drawings are automatically drawn using the connection relationship between each selection object in the selection scheme; the basic drawings are used to describe the connection mode and layout between each selection object in the selection scheme, and the basic drawings include wiring diagrams; on the basis of the basic drawings, more details are added according to the requirements of the actual installation environment to form installation drawings corresponding to the selection scheme.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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