Data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of Internet of Vehicles, and the method comprises the steps: obtaining business demand information input by a user, extracting candidate keywords in the business demand information, and responding to a target keyword determined by the user according to the candidate keywords, searching a business data model matched with the target keyword in a preset Internet of Vehicles index library, converting the business data model into a physical data model, capturing target physical data corresponding to the business demand information by adopting the physical data model, and performing unified processing on the target physical data to obtain a target physical data model; and visually displaying the processed target physical data to a user. According to the method, key information in user service analysis requirements is recognized and extracted, related service data models are automatically matched for data capture and processing, the requirements of users for quickly checking and analyzing multi-dimensional data are met, and the data analysis efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle networking, and in particular to a data processing method, device, electronic equipment and storage medium. Background Art

[0002] With the development of Internet of Vehicles technology and the expansion of its application scope, more and more vehicle business data need to be analyzed and processed in order to better support and serve related businesses. The analysis of Internet of Vehicles business data is to extract valuable information from massive data to provide support for business decision-making.

[0003] At present, the data required for Internet of Vehicles business analysis comes from a wide range of sources, involving R&D links such as data development, data analysis, and business. Extracting valuable information from massive data involves data analysis personnel, data development, and business personnel. Since professional technicians are required to participate and export data, it not only consumes a huge amount of human resources, but also when the business changes, the technicians need to export the data again, affecting the efficiency of data analysis. Summary of the invention

[0004] In view of this, the present invention aims to propose a data processing method, device, electronic device and storage medium to solve the problem that Internet of Vehicles business data analysis relies on manual data export by professional technicians, which affects the efficiency of data analysis, and to achieve automatic and efficient data processing.

[0005] According to a first aspect of the present invention, a data processing method is provided, the method comprising:

[0006] Obtaining business requirement information input by a user, and extracting candidate keywords from the business requirement information;

[0007] In response to a target keyword determined by a user according to the candidate keywords, a business data model matching the target keyword is retrieved from a preset Internet of Vehicles index library;

[0008] Converting the business data model into a physical data model;

[0009] The physical data model is used to capture target physical data corresponding to the business demand information, the target physical data is processed uniformly, and the processed target physical data is visualized and displayed to the user.

[0010] Optionally, the acquiring the business requirement information input by the user and extracting candidate keywords from the business requirement information includes:

[0011] Receiving business demand information input by a user; the business demand information includes voice information and text information;

[0012] Performing voice analysis on the voice information to extract a first keyword from the voice information, and performing semantic extraction on the text information to obtain a second keyword from the text information;

[0013] The first keyword and / or the second keyword is determined as a candidate keyword.

[0014] Optionally, in response to the target keyword determined by the user according to the candidate keyword, retrieving a business data model matching the target keyword in a preset Internet of Vehicles indicator library includes:

[0015] Displaying the candidate keywords to a user, and in response to a target keyword determined by the user based on the candidate keywords, calling a preset Internet of Vehicles indicator library;

[0016] The target keyword is searched through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword;

[0017] A target business data model in the at least one business data model is determined.

[0018] Optionally, converting the business data model into a physical data model includes:

[0019] Get the data type processed by the business data model;

[0020] The data types of the business data model are mapped to the data types of the physical data model using preset model conversion rules to obtain a physical data model.

[0021] Optionally, the adopting the physical data model to capture the target physical data corresponding to the business demand information, uniformly processing the target physical data, and visually displaying the processed target physical data to the user includes:

[0022] The physical data model is used to capture raw data to obtain target physical data corresponding to the business demand information;

[0023] Preprocessing the target physical data; wherein the preprocessing includes denoising, interpolation and smoothing;

[0024] The preprocessed target physical data is integrated into a preset standard format, and the target physical data in the preset standard format is visualized and displayed to the user.

[0025] According to a second aspect of the present invention, there is provided a data processing device, the device comprising:

[0026] An information acquisition module is used to acquire business demand information input by a user and extract candidate keywords from the business demand information;

[0027] A matching model module, configured to retrieve a business data model matching the target keyword from a preset Internet of Vehicles index library in response to a target keyword determined by a user based on the candidate keywords;

[0028] A model processing module, used for converting the business data model into a physical data model;

[0029] The data processing module is used to use the physical data model to capture the target physical data corresponding to the business demand information, perform unified processing on the target physical data, and visualize the processed target physical data to the user.

[0030] Optionally, the information acquisition module includes:

[0031] A receiving submodule, used to receive business demand information input by a user; the business demand information includes voice information and text information;

[0032] An extraction submodule, configured to perform voice analysis on the voice information to extract a first keyword from the voice information, and to perform semantic extraction on the text information to obtain a second keyword from the text information;

[0033] The first determining submodule is configured to determine the first keyword and / or the second keyword as candidate keywords.

[0034] Optionally, the matching model module includes:

[0035] A calling submodule, used for displaying the candidate keywords to the user, and calling a preset Internet of Vehicles indicator library in response to a target keyword determined by the user based on the candidate keywords;

[0036] A retrieval submodule, configured to search the target keyword through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword;

[0037] The second determining submodule is used to determine a target business data model in the at least one business data model.

[0038] Optionally, the model conversion module includes:

[0039] The acquisition submodule is used to obtain the data type processed by the business data model;

[0040] The mapping submodule is used to map the data type of the business data model to the data type of the physical data model using preset model conversion rules to obtain the physical data model.

[0041] Optionally, the data processing module includes:

[0042] A capture submodule, used to capture raw data using the physical data model to obtain target physical data corresponding to the business demand information;

[0043] A preprocessing submodule, used for preprocessing the target physical data; wherein the preprocessing includes denoising, interpolation and smoothing;

[0044] The display submodule is used to merge the preprocessed target physical data into a preset standard format and visually display the target physical data in the preset standard format to the user.

[0045] According to another aspect of the present invention, there is also provided an electronic device, comprising:

[0046] processor;

[0047] a memory for storing instructions executable by the processor;

[0048] The processor is configured to execute the instructions to implement the data processing method as described above.

[0049] According to another aspect of the present invention, a readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the data processing method described above are implemented.

[0050] The data processing method provided by the embodiment of the present invention obtains the business demand information input by the user, extracts the candidate keywords in the business demand information, responds to the target keywords determined by the user based on the candidate keywords, retrieves the business data model matching the target keywords in the preset Internet of Vehicles index library, converts the business data model into a physical data model, uses the physical data model to capture the target physical data corresponding to the business demand information, uniformly processes the target physical data, and visualizes the processed target physical data to the user. The embodiment of the present invention accurately identifies and extracts the key information in the user's business analysis needs, and the user can confirm the key information, ensuring that the extracted keywords accurately reflect the business needs, automatically matches the relevant business data model through the preset Internet of Vehicles index library, converts the business data model into a physical data model, ensures the compatibility of the physical data model with the underlying data storage and processing system, facilitates data capture and processing, and the captured data is highly matched with the business demand information, and finally integrates the data from different sources and displays it to the user in an intuitive and visual way, so as to meet the user's needs to quickly view and analyze data in multiple dimensions, improve the efficiency of data analysis and decision-making, and provide strong support for the analysis of Internet of Vehicles business data.

[0051] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0053] Figure 1 is a flow chart of steps of a data processing method provided by an embodiment of the present invention;

[0054] Figure 2 yes Figure 1 A flowchart of step 101 in the data processing method provided by an embodiment of the present invention;

[0055] Figure 3 yes Figure 1 A flowchart of step 102 in the data processing method provided in an embodiment of the present invention;

[0056] Figure 4 yes Figure 1 Flow chart of step 103 in the data processing method provided by the embodiment of the present invention;

[0057] Figure 5 yes Figure 1 A flowchart of step 104 in the data processing method provided in an embodiment of the present invention;

[0058] Figure 6 is a structural schematic diagram of a data processing device provided by an embodiment of the present invention;

[0059] Figure 7 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] To make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented. The division of the following embodiments is for the convenience of description, and should not constitute any limitation on the specific implementation of the present invention. The various embodiments can be combined and referenced with each other without contradiction.

[0061] Reference Figure 1 , shows a flow chart of the steps of a data processing method provided by an embodiment of the present invention, the method may include:

[0062] Step 101: Obtain business requirement information input by a user, and extract candidate keywords from the business requirement information.

[0063] In an embodiment of the present invention, in order to solve the problem that the Internet of Vehicles business data analysis relies on professional technicians to manually export data, which affects the efficiency of data analysis, this embodiment extracts key information in the user's business analysis needs, automatically matches the business data model related to the key information, and captures and processes the underlying data according to the analysis algorithm in the model. The captured data is highly matched with the business demand information, and data from different sources are automatically integrated and displayed to the user in an intuitive and visual manner, meeting the user's needs for quickly viewing and analyzing data in multiple dimensions, and improving the efficiency of data analysis and decision-making. Specifically, the executor of the embodiment of the present invention is a data processing system, which can be a Internet of Vehicles data processing platform or processor.

[0064] In this embodiment, the system actively monitors or passively receives user input to obtain business demand information input by the user. The business demand information includes the business needs of business personnel for data analysis of the vehicle, which may be analysis needs such as vehicle driving conditions or vehicle health. The business demand information is obtained by the user through voice or text input. Specifically, the business demand information input by the user through voice or text is obtained, and voice parsing and text escape technology are used to extract characteristic keywords of the business analysis needs of the Internet of Vehicles business personnel as candidate keywords. The business demand information may contain analysis features and invalid information, and it is necessary to perform feature extraction on the business demand information to obtain keyword features in order to provide data support for further data analysis.

[0065] Step 102 , in response to a target keyword determined by the user based on the candidate keywords, a business data model matching the target keyword is retrieved from a preset Internet of Vehicles index library.

[0066] In an embodiment of the present invention, the system responds to a target keyword determined by a user based on candidate keywords, calls a preset Internet of Vehicles indicator library, uses the target keyword to search in the preset Internet of Vehicles indicator library, and retrieves a business data model that matches the target keyword, wherein the target keyword is at least one keyword confirmed by the user, and is used to match the data analysis model. The Internet of Vehicles indicator library is a database that centrally stores and manages various indicators, models, and algorithms required for Internet of Vehicles business data analysis, and includes various indicators and analysis algorithm models related to vehicles, driving behaviors, vehicle health status, driving data, etc.

[0067] Specifically, the business demand personnel confirm and extract the extracted feature keyword information, including parameter information such as time granularity, dimension, and feature attributes. For example: time granularity: by day; dimension: vehicle ID, time; feature attributes: fuel consumption, speed. If the candidate keywords are confirmed to be correct, enter the search, otherwise, re-enter the business demand information. The candidate keywords are displayed to the user, and in response to the target keywords determined by the user based on the candidate keywords, the preset Internet of Vehicles indicator library is called. The user selects or determines the target keywords based on the displayed candidate keywords. After user confirmation, it is ensured that the extracted keywords accurately reflect the user's needs. According to the target keywords determined by the user, the preset Internet of Vehicles indicator library is called, and the target keywords are used to search in the preset Internet of Vehicles indicator library, match at least one business data model, and select the most suitable target business data model from at least one matched business data model.

[0068] Step 103: Convert the business data model into a physical data model.

[0069] In an embodiment of the present invention, the business data model that business personnel retrieve to match when performing Internet of Vehicles data analysis is a high-level abstraction based on business needs and data needs, and describes the structure, relationship and business rules of the data. In order to meet the business analysis needs, it is necessary to capture the original data of the vehicle to obtain the original data required for business analysis. Therefore, after retrieving the business data model, the business data model is converted into a physical data model to realize the use of the physical data model to capture the original data of the vehicle.

[0070] Step 104 , using the physical data model to capture the target physical data corresponding to the business demand information, uniformly processing the target physical data, and visually displaying the processed target physical data to the user.

[0071] In an embodiment of the present invention, a physical data model is used to capture the target physical data corresponding to the business demand information, and the target physical data is the original data of the vehicle, including driving data, status data, time and other physical data. Specifically, a physical data model is used to capture the original data from the lake warehouse (such as a data lake, a data warehouse), that is, the target physical data corresponding to the business demand information, and perform logical processing on the captured data, including data cleaning, conversion, aggregation and unified processing operations. Through a preset standard format, data from different sources are merged into a unified standard format to ensure the consistency of data in different sources and processing stages, improve data processing efficiency, reduce data conversion and integration time, and display the fused data to the user in the form of a chart, such as a relationship chart between fuel consumption and speed, a time series chart, etc., or integrate multiple visualization charts and indicators into a unified interface, so that users can quickly view and analyze data of multiple dimensions through the interface, and through visual display, users can intuitively understand the data and analysis results.

[0072] The data processing method provided by the embodiment of the present invention obtains the business demand information input by the user, extracts the candidate keywords in the business demand information, responds to the target keywords determined by the user based on the candidate keywords, retrieves the business data model matching the target keywords in the preset Internet of Vehicles index library, converts the business data model into a physical data model, uses the physical data model to capture the target physical data corresponding to the business demand information, uniformly processes the target physical data, and visualizes the processed target physical data to the user. The embodiment of the present invention accurately identifies and extracts the key information in the user's business analysis needs, and the user can confirm the key information, ensuring that the extracted keywords accurately reflect the business needs, automatically matches the relevant business data model through the preset Internet of Vehicles index library, converts the business data model into a physical data model, ensures the compatibility of the physical data model with the underlying data storage and processing system, facilitates data capture and processing, and the captured data is highly matched with the business demand information, and finally integrates the data from different sources and displays it to the user in an intuitive and visual way, so as to meet the user's needs to quickly view and analyze data in multiple dimensions, improve the efficiency of data analysis and decision-making, and provide strong support for the analysis of Internet of Vehicles business data.

[0073] Further, see Figure 2 , showing Figure 1 A flowchart of step 101 in a data processing method is provided. The method is substantially the same as the data processing method provided in the first embodiment of the present invention. Step 101 may include:

[0074] Step 201, receiving business demand information input by a user; the business demand information includes voice information and text information.

[0075] Step 202, performing voice analysis on the voice information to extract the first keyword in the voice information, and performing semantic extraction on the text information to obtain the second keyword in the text information.

[0076] Step 203: determine the first keyword and / or the second keyword as candidate keywords.

[0077] It should be noted that in the embodiment of the present invention, the data processing system receives the business demand information input by the user, and extracts effective feature information as keywords from the business demand information. Specifically, the user can input the business demand information by voice input or text input. This embodiment supports multiple input methods of voice and text to meet the usage habits of different users. Voice input can improve input efficiency, and text input can provide more accurate descriptions, which are suitable for complex or detailed needs.

[0078] Specifically, after the data processing system receives the voice information and text information input by the user, it uses speech recognition technology to convert the voice information into text, and extracts the keywords therein as the second keyword, uses natural language processing technology to perform semantic analysis on the text information, extracts the keywords therein as the second keyword, and determines the first keyword obtained from the speech analysis and the second keyword obtained from the semantic extraction as candidate keywords. The candidate keywords are used for users to screen and determine the target keywords of the retrieval model.

[0079] For example, the user inputs "Analyze the vehicle driving data of the past month, focusing on the relationship between fuel consumption and speed" through voice, and the system extracts the first keywords "the past month", "vehicle driving data", "fuel consumption", and "speed". Alternatively, the user inputs "Analyze the vehicle driving data in September 2024, focusing on fuel consumption and speed" through text, and the second keywords "September 2024", "vehicle driving data", "fuel consumption", and "speed" are semantically extracted, and the candidate keywords are determined to be "the past month", "September 2024", "vehicle driving data", "fuel consumption", and "speed". It should be noted that the system receives the business demand information input by the user, identifies the business demand information, determines whether the business demand information includes valid feature information, and when it is determined that the business demand information is valid, performs voice analysis on the voice information to extract the first keyword in the voice information, and performs semantic extraction on the text information to obtain the second keyword in the text information.

[0080] The embodiments of the present invention can accurately identify and extract key information in user business needs through speech analysis and semantic extraction, ensure the accuracy and efficiency of subsequent analysis, reduce manual intervention, improve processing efficiency, and ensure that keywords extracted from different input methods are consistent and comparable.

[0081] Further, see Figure 3 , showing Figure 1 A flowchart of step 102 in a data processing method is provided. The method is substantially the same as the data processing method provided in the first embodiment of the present invention. Step 102 may include:

[0082] Step 301 : display candidate keywords to the user, and in response to the target keywords determined by the user based on the candidate keywords, call a preset Internet of Vehicles indicator library.

[0083] Step 302: Search the target keyword through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword.

[0084] Step 303: determine a target business data model in at least one business data model.

[0085] It should be noted that, in the embodiment of the present invention, the system first displays the candidate keywords to the user through the platform interface, and in response to the target keywords determined by the user based on the candidate keywords, calls the preset Internet of Vehicles indicator library, searches for the target keywords in the preset Internet of Vehicles indicator library, and obtains at least one business data model that matches the target keywords. The business data model is a model used to analyze data, including a regression analysis model, a clustering analysis model, and a time series analysis model.

[0086] Specifically, the user selects or determines the target keyword based on the displayed candidate keywords. The system calls the preset Internet of Vehicles index library based on the target keyword determined by the user. Through user confirmation, it ensures that the extracted keywords accurately reflect user needs, improves the interactivity of the system, and enables users to directly participate in the selection and confirmation of keywords. Use the target keyword to search in the preset Internet of Vehicles index library, match the business data model, match at least one business data model based on the target keyword, and automatically match related business data models through the preset Internet of Vehicles index library to reduce manual intervention, quickly find the business data model that matches the user's needs, and select the most suitable target business data model from at least one matched business data model. Specifically, the target business data model can be determined based on factors such as model scoring, user preferences, and historical data, which is not specifically limited in this embodiment.

[0087] For example, the user inputs "analyze the vehicle driving data of the past month, focusing on fuel consumption" through voice, and the candidate keywords are: "past month", "vehicle driving data", "fuel consumption", and "speed". The system displays the candidate keywords to the user, and the user confirms that the target keyword is "fuel consumption" by touching or entering commands. According to the target keyword, the Internet of Vehicles indicator library is called, and the target keyword is retrieved from the Internet of Vehicles indicator library, and the following business data models are matched: Model 1 is a regression analysis model of fuel consumption and speed, and Model 2 is a time series analysis model of fuel consumption and speed. According to the model score and user preference, the "regression analysis model of fuel consumption and speed" is selected as the target business data model.

[0088] By displaying candidate keywords to users and confirming target keywords, the embodiment of the present invention can ensure that the extracted keywords accurately reflect user needs, automatically match relevant business data models through a preset Internet of Vehicles indicator library, improve retrieval efficiency and accuracy, select the most appropriate business data model, and provide strong support for the analysis of Internet of Vehicles business data.

[0089] Further, see Figure 4 , showing Figure 1 A flowchart of step 103 in a data processing method is provided. The method is substantially the same as the data processing method provided in the first embodiment of the present invention. Step 103 may include:

[0090] Step 401: Obtain the data type processed by the business data model.

[0091] Step 402: Map the data types of the business data model to the data types of the physical data model using preset model conversion rules to obtain a physical data model.

[0092] It should be noted that, in the embodiments of the present invention, the business model is usually a high-level abstraction based on business needs and data needs, which describes the structure, relationship and business rules of the data. The system obtains the data type processed by the search-matched target business data model and extracts the data type processed by the business data model. The data type includes numeric type, character type, time type, Boolean type, etc. The physical data model is used to be compatible with the underlying data storage and processing system to capture and process the original data.

[0093] In this embodiment, the system uses a preset model conversion rule to map the data type of the business data model to the data type of the physical data model to obtain a physical data model, and uses the preset model conversion rule to map the data type of the business data model to the data type of the physical data model, and constructs the physical data model according to the mapped data type. For example, the business data model is a regression analysis model of fuel consumption and speed, and the preset conversion rule is used to map the numerical type (floating point number) in the regression analysis model to the numerical type (floating point number) of the physical data model, and the time type (date and time) is mapped to the time type (date and time) of the physical data model, ensuring that the physical data model meets the subsequent raw data capture and processing.

[0094] It should be noted that the preset model conversion rules in this embodiment are used to ensure the standardization of data types between the business data model and the physical data model. They are pre-formulated according to the actual raw data to be captured, and are not specifically limited here, to ensure the compatibility of the physical data model with the underlying data storage and processing system, and to facilitate subsequent data capture and processing. For example, the business data model is a regression analysis model of fuel consumption and speed. The preset conversion rules are used to map the numerical type (floating point number) in the regression analysis model to the numerical type (floating point number) of the physical data model, and the time type (date and time) is mapped to the time type (date and time) of the physical data model, to ensure that the physical data model meets the subsequent raw data capture and processing.

[0095] The embodiment of the present invention obtains the data type processed by the business data model and adopts preset model conversion rules to automatically map the data type of the business data model to the data type of the physical data model. This not only improves the efficiency of model conversion, but also ensures the compatibility of the physical data model with the underlying data storage and processing system, providing strong support for subsequent data capture and processing.

[0096] Further, see Figure 5 , showing Figure 1 A flowchart of step 104 in a data processing method is provided. The method is substantially the same as the data processing method provided in the first embodiment of the present invention. Step 104 may include:

[0097] Step 501: Use a physical data model to capture raw data to obtain target physical data corresponding to business demand information.

[0098] Step 502, preprocessing the target physical data; wherein the preprocessing includes denoising, interpolation and smoothing.

[0099] Step 503: merge the preprocessed target physical data into a preset standard format, and visualize the target physical data in the preset standard format to the user.

[0100] It should be noted that, in the embodiment of the present invention, a physical data model is used to capture the original data, and the corresponding target physical data is captured according to the business demand information to obtain the target physical data corresponding to the business demand information, thereby ensuring that the captured data is highly matched with the business demand information and avoiding interference from irrelevant data. Through the physical data model, the original physical data is automatically captured to improve data acquisition efficiency.

[0101] In this embodiment, the captured target physical data is preprocessed, and the preprocessing includes denoising, interpolation and smoothing. The denoising is used to remove noise data in the target physical data, such as outliers, outliers, etc. The interpolation is used to interpolate missing data and fill in data gaps. The smoothing is used to smooth continuous data to reduce data fluctuations and improve data stability. Through preprocessing, the data quality is improved to ensure the accuracy and reliability of the data. The preprocessed target physical data is merged into a preset standard format, and the target physical data in the preset standard format is visualized to the user. The preset standard format is used to ensure the consistency of data in different sources and processing stages. Through the visual display, the user can intuitively understand the data and analysis results.

[0102] The embodiment of the present invention captures raw data using a physical data model, thereby ensuring that the captured data is highly matched with business demand information, improving data acquisition efficiency and accuracy, denoising, interpolating and smoothing the captured target physical data, improving data quality, ensuring data consistency and robustness, merging the preprocessed data into a preset standard format, and displaying it visually so that users can intuitively understand the data and analysis results.

[0103] Reference Figure 6 , shows a schematic diagram of the structure of a data processing device 600 provided in an embodiment of the present invention, the device comprising:

[0104] The information acquisition module 601 is used to acquire the business demand information input by the user and extract candidate keywords from the business demand information;

[0105] A matching model module 602 is used to retrieve a business data model matching the target keyword in a preset Internet of Vehicles indicator library in response to a target keyword determined by a user according to the candidate keywords;

[0106] A model processing module 603, used to convert the business data model into a physical data model;

[0107] The data processing module 604 is used to use the physical data model to capture the target physical data corresponding to the business demand information, perform unified processing on the target physical data, and visualize the processed target physical data to the user.

[0108] Optionally, the information acquisition module 601 includes:

[0109] A receiving submodule, used to receive business demand information input by a user; the business demand information includes voice information and text information;

[0110] An extraction submodule, configured to perform voice analysis on the voice information to extract a first keyword from the voice information, and to perform semantic extraction on the text information to obtain a second keyword from the text information;

[0111] The first determining submodule is configured to determine the first keyword and / or the second keyword as candidate keywords.

[0112] Optionally, the matching model module 602 includes:

[0113] A calling submodule, used for displaying the candidate keywords to the user, and calling a preset Internet of Vehicles indicator library in response to a target keyword determined by the user based on the candidate keywords;

[0114] A retrieval submodule, configured to search the target keyword through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword;

[0115] The second determining submodule is used to determine a target business data model in the at least one business data model.

[0116] Optionally, the model conversion module 603 includes:

[0117] The acquisition submodule is used to obtain the data type processed by the business data model;

[0118] The mapping submodule is used to map the data type of the business data model to the data type of the physical data model using preset model conversion rules to obtain the physical data model.

[0119] Optionally, the data processing module 604 includes:

[0120] A capture submodule, used to capture raw data using the physical data model to obtain target physical data corresponding to the business demand information;

[0121] A preprocessing submodule, used for preprocessing the target physical data; wherein the preprocessing includes denoising, interpolation and smoothing;

[0122] The display submodule is used to merge the preprocessed target physical data into a preset standard format and visually display the target physical data in the preset standard format to the user.

[0123] The data processing device provided by the embodiment of the present invention obtains the business demand information input by the user, extracts the candidate keywords in the business demand information, responds to the target keywords determined by the user according to the candidate keywords, retrieves the business data model matching the target keywords in the preset Internet of Vehicles index library, converts the business data model into a physical data model, uses the physical data model to capture the target physical data corresponding to the business demand information, uniformly processes the target physical data, and visualizes the processed target physical data to the user. The embodiment of the present invention accurately identifies and extracts the key information in the user's business analysis needs, and the user can confirm the key information, ensures that the extracted keywords accurately reflect the business needs, automatically matches the relevant business data model through the preset Internet of Vehicles index library, converts the business data model into a physical data model, ensures the compatibility of the physical data model with the underlying data storage and processing system, facilitates data capture and processing, and the captured data is highly matched with the business demand information, and finally integrates the data from different sources and displays it to the user in an intuitive and visual way, so as to meet the user's needs to quickly view and analyze data in multiple dimensions, improve the efficiency of data analysis and decision-making, and provide strong support for the analysis of Internet of Vehicles business data.

[0124] Reference Figure 7 , an embodiment of the present invention further provides an electronic device, such as Figure 7 As shown, it includes a processor 701, a communication interface 702, a memory 703 and a communication bus 704, wherein the processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704.

[0125] A processor 701, a memory 703 for storing processor executable instructions;

[0126] The processor 701 is configured to execute the instructions to implement the data processing method as described above:

[0127] Obtaining business requirement information input by a user, and extracting candidate keywords from the business requirement information;

[0128] In response to a target keyword determined by a user according to the candidate keywords, a business data model matching the target keyword is retrieved from a preset Internet of Vehicles index library;

[0129] Converting the business data model into a physical data model;

[0130] The physical data model is used to capture target physical data corresponding to the business demand information, the target physical data is processed uniformly, and the processed target physical data is visualized and displayed to the user.

[0131] The communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0132] The communication interface is used for communication between the above terminal and other devices.

[0133] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0134] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0135] In another embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the data processing method described in any one of the above embodiments is implemented.

[0136] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk (SSD)), etc.

[0137] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0138] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A data processing method, characterized in that: The method comprises: Obtaining business requirement information input by a user, and extracting candidate keywords from the business requirement information; In response to a target keyword determined by the user according to the candidate keywords, a business data model matching the target keyword is retrieved from a preset Internet of Vehicles index library; Converting the business data model into a physical data model; The physical data model is used to capture target physical data corresponding to the business demand information, the target physical data is processed uniformly, and the processed target physical data is visualized and displayed to the user.

2. According to the method of claim 1, the step of obtaining the business requirement information input by the user and extracting candidate keywords from the business requirement information comprises: Receive business requirement information input by users; The business demand information includes voice information and text information; Performing voice analysis on the voice information to extract a first keyword from the voice information, and performing semantic extraction on the text information to obtain a second keyword from the text information; The first keyword and / or the second keyword is determined as a candidate keyword.

3. The method according to claim 1, characterized in that In response to the target keyword determined by the user according to the candidate keyword, searching for a business data model matching the target keyword in a preset Internet of Vehicles indicator library includes: Displaying the candidate keywords to a user, and in response to a target keyword determined by the user based on the candidate keywords, calling a preset Internet of Vehicles indicator library; Retrieving the target keyword through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword; A target business data model in the at least one business data model is determined.

4. The method according to claim 1, characterized in that: The converting the business data model into a physical data model comprises: Get the data type processed by the business data model; The data types of the business data model are mapped to the data types of the physical data model using preset model conversion rules to obtain a physical data model.

5. The method according to claim 1, characterized in that: The adopting the physical data model to capture the target physical data corresponding to the business demand information, uniformly processing the target physical data, and visually displaying the processed target physical data to the user includes: The physical data model is used to capture raw data to obtain target physical data corresponding to the business demand information; Preprocessing the target physical data; wherein the preprocessing includes denoising, interpolation and smoothing; The preprocessed target physical data is integrated into a preset standard format, and the target physical data in the preset standard format is visualized and displayed to the user.

6. A data processing device, characterized in that: The device comprises: An information acquisition module is used to acquire business demand information input by a user and extract candidate keywords from the business demand information; A matching model module, configured to retrieve a business data model matching the target keyword from a preset Internet of Vehicles index library in response to a target keyword determined by a user based on the candidate keywords; A model conversion module, used to convert the business data model into a physical data model; The data processing module is used to use the physical data model to capture the target physical data corresponding to the business demand information, perform unified processing on the target physical data, and visualize the processed target physical data to the user.

7. The device according to claim 6, characterized in that The information acquisition module includes: A receiving submodule, used to receive business demand information input by a user; the business demand information includes voice information and text information; An extraction submodule, configured to perform voice analysis on the voice information to extract a first keyword from the voice information, and to perform semantic extraction on the text information to obtain a second keyword from the text information; The first determining submodule is configured to determine the first keyword and / or the second keyword as candidate keywords.

8. The device according to claim 6, characterized in that The matching model module comprises: A calling submodule, used for displaying the candidate keywords to the user, and calling a preset Internet of Vehicles indicator library in response to a target keyword determined by the user based on the candidate keywords; A retrieval submodule, configured to search the target keyword through a preset Internet of Vehicles index library to obtain at least one business data model matching the target keyword; The second determining submodule is used to determine a target business data model in the at least one business data model.

9. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute the instructions to implement the data processing method according to any one of claims 1 to 5.

10. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the data processing method according to any one of claims 1 to 5 is implemented.

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