Data processing method and device, electronic equipment and readable storage medium

Abstract

The invention relates to the technical field of data processing, and provides a data processing method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring target object data; performing mapping processing on the target object data based on a preset processable object database to obtain at least one piece of sub-item data corresponding to the target object data; in response to the subitem data selection instruction, determining target subitem data corresponding to the target object data according to at least one subitem data corresponding to the target object data; determining a target value corresponding to the target subitem data and a real-time value corresponding to the target subitem data according to the target subitem data corresponding to the target object data; and performing matching processing on the target value corresponding to the target subitem data and the real-time value corresponding to the target subitem data based on a preset matching condition to obtain feedback result data corresponding to the target subitem data, thereby improving readability and manageability of the data, improving processing efficiency, and enhancing accuracy of data processing.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a data processing method, device, electronic device and readable storage medium. Background Art

[0002] Existing data entry and matching usually rely on manual judgment of the validity of the input data. For example, in a target management system, the achievement of the target is usually achieved by manually switching the status. The input targets and key results are manually entered into the system, and the input results are presented in natural language. The human involvement in the process leads to an increased error rate in result judgment. Under normal circumstances, the system corrects it in subsequent task plans. However, this method has a low degree of automation, it is difficult to unify the evaluation criteria, and the feedback link is long, resulting in low processing efficiency and poor accuracy.

[0003] It can be seen that the existing technology has problems such as low processing efficiency and poor accuracy due to low automation, difficulty in unifying evaluation standards, and long feedback links. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure provide a data processing method, device, electronic device and readable storage medium to solve the problems in the prior art of low processing efficiency and poor accuracy due to low degree of automation, difficulty in unifying evaluation standards and long feedback links.

[0005] In a first aspect of an embodiment of the present disclosure, a data processing method is provided, including: acquiring target object data; mapping the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data; in response to a sub-item data selection instruction, determining target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data; determining a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data according to the target sub-item data corresponding to the target object data; and matching the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data based on a preset matching condition to obtain feedback result data corresponding to the target sub-item data.

[0006] According to a second aspect of an embodiment of the present disclosure, a data processing device is provided, comprising: an acquisition module for acquiring target object data; a first processing module for performing confirmation processing on the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data; a first determination module for determining, in response to a sub-item data selection instruction, target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data; a second determination module for determining, based on the target sub-item data corresponding to the target object data, a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data; and a second processing module for performing matching processing on the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data based on a preset matching condition to obtain feedback result data corresponding to the target sub-item data.

[0007] According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0008] According to a fourth aspect of an embodiment of the present disclosure, a readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0009] Compared with the prior art, the embodiments of the present disclosure have the following beneficial effects: by obtaining target object data through user input or from a preset database, at least one sub-item data corresponding to the target object data can be mapped according to a mapping relationship between the target object data and a preset processable object database, and in response to a sub-item data selection instruction, the target sub-item data corresponding to the target object data can be determined and selected according to at least one sub-item data corresponding to the target object data, and then the target value corresponding to the target object data and the real-time value corresponding to the target object data can be obtained according to the sub-item data corresponding to the target object data, and according to preset matching conditions, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are rule-matched to obtain feedback result data corresponding to the target sub-item data, thereby improving the readability and manageability of the data, ensuring the accuracy of the processing steps, improving the processing efficiency, and enhancing the flexibility and scalability of the processing flow. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 is a schematic diagram of an application scenario of an embodiment of the present disclosure;

[0012] Figure 2 is a flowchart of a data processing method provided by an embodiment of the present disclosure;

[0013] Figure 3 is a structural schematic diagram of a data processing device provided by an embodiment of the present disclosure;

[0014] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0015] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0016] It should be noted that the user information (including but not limited to terminal device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0017] A data processing method and device according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0018] Figure 1 Schematic diagram of an application scenario of an embodiment of the present disclosure. The application scenario may include terminal devices 1, 2 and 3, a server 4 and a network 5.

[0019] Terminal devices 1, 2 and 3 can be hardware or software. When terminal devices 1, 2 and 3 are hardware, they can be various electronic devices with display screens and supporting communication with server 4, including but not limited to smart phones, tablet computers, laptop portable computers and desktop computers, etc.; when terminal devices 1, 2 and 3 are software, they can be installed in the above electronic devices. Terminal devices 1, 2 and 3 can be implemented as multiple software or software modules, or as a single software or software module, and the embodiments of the present disclosure are not limited to this. Furthermore, various applications can be installed on terminal devices 1, 2 and 3, such as data processing applications, instant messaging tools, social platform software, search applications, shopping applications, etc.

[0020] The server 4 may be a server that provides various services, for example, a background server that receives a request sent by a terminal device that establishes a communication connection with the server, and the background server may receive and analyze the request sent by the terminal device, and generate a processing result. The server 4 may be a single server, or a server cluster composed of several servers, or a cloud computing service center, which is not limited in the embodiments of the present disclosure.

[0021] It should be noted that the server 4 can be hardware or software. When the server 4 is hardware, it can be various electronic devices that provide various services for the terminal devices 1, 2, and 3. When the server 4 is software, it can be multiple software or software modules that provide various services for the terminal devices 1, 2, and 3, or it can be a single software or software module that provides various services for the terminal devices 1, 2, and 3, and the embodiments of the present disclosure are not limited to this.

[0022] The network 5 can be a wired network connected by coaxial cable, twisted pair and optical fiber, or it can be a wireless network that can interconnect various communication devices without wiring, such as Bluetooth, Near Field Communication (NFC), infrared, etc., which is not limited in the embodiments of the present disclosure.

[0023] The user can establish a communication connection with the server 4 via the network 5 through the terminal devices 1, 2 and 3 to receive or send information, etc. Specifically, the server 4 can obtain the target object data via the terminal devices 1, 2 and 3, and can map and obtain at least one sub-item data corresponding to the target object data according to the mapping relationship between the target object data and the preset processable object database, and in response to the sub-item data selection instruction, can determine and select the target sub-item data corresponding to the target object data according to the at least one sub-item data corresponding to the target object data, and then can obtain the target value corresponding to the target object data and the real-time value corresponding to the target object data according to the sub-item data corresponding to the target object data, and according to the preset matching conditions, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are rule-matched to obtain the feedback result data corresponding to the target sub-item data.

[0024] It should be noted that the specific types, quantities and combinations of the terminal devices 1, 2 and 3, the server 4 and the network 5 can be adjusted according to the actual needs of the application scenario, and the embodiments of the present disclosure are not limited to this.

[0025] Figure 2 It is a flowchart of a data processing method provided by an embodiment of the present disclosure. Figure 2 The data processing method can be Figure 1 The server executes. Figure 2 As shown, the data processing method includes:

[0026] Step 201, obtaining target object data.

[0027] Specifically, data related to the target object can be automatically retrieved, extracted, or received from a data source through a preset data acquisition interface or data processing system, which is not limited here. The data source includes but is not limited to a database, a file, or a network application programming interface (Application Programming Interface, API), thereby enhancing the flexibility and real-time nature of data processing, improving the accuracy and efficiency of data processing, and providing a data basis for subsequent data mapping, analysis, comparison, and feedback by obtaining the target object data.

[0028] Among them, the target object data can be relevant data that users or data processing systems pay attention to, analyze, or process. The target object data includes but is not limited to project names, entity attributes, or task requirements, etc., and can be organized and stored through preset data structures, wherein the preset data structures include but are not limited to tables, JavaScript Object Notation (JSON), or Extensible Markup Language (XML), etc. The target object data can be obtained through various channels such as database query, file reading, or network request, which are not limited here.

[0029] For example, the target object data may be information about a product, including product name, price, inventory, and sales records. The data processing system may obtain the target object data of the product and may obtain and store real-time information about the product by calling the API interface of the e-commerce platform. In subsequent processing, the target object data may be used for analysis and processing, such as calculating the popularity of the product or predicting the user's purchasing intention.

[0030] Step 202: Mapping the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data.

[0031] Specifically, by querying the mapping rules or logic set in the preset processable object database, the acquired target object data can be matched and converted with the corresponding entries in the preset processable object database, and at least one sub-item data associated with the target object data can be matched and extracted, that is, the sub-item data corresponding to the target object data, thereby enhancing the intelligence and automation of data processing, improving the accuracy and efficiency of data processing, and improving the breadth and depth of data utilization. Through the mapping mechanism in the preset processable object database, the speed and efficiency of extracting key information are improved.

[0032] Among them, the preset processable object database can be a database that is pre-set and maintained. The preset processable object database can be used to store information such as data models, structures, attributes, and mapping relationships of processable objects, which is not limited here. The preset processable object database can also be used to guide the conversion of original data into a form that is recognizable and processable by the system; the sub-item data corresponding to the target object data can refer to specific information fragments decomposed, extracted, or derived from the target object data, and the content of the sub-item data corresponding to the target object data can be attribute values ​​of the target object data, calculation results, information of associated sub-items, etc., which is not limited here. The sub-item data corresponding to the target object data can be associated with the target object data through mapping rules in the preset processable object database.

[0033] For example, the target object data may be the patient's medical record information, including multiple fields such as name, age, medical history, and examination results. The preset processable object database may pre-set mapping rules for patient data to different medical systems or analysis models. Then, according to the mapping rules, the patient's medical record information may be mapped to obtain multiple sub-item data, such as the patient's basic information, disease diagnosis information, treatment plan information, etc. Among them, the patient's basic information may be name and age, etc., the disease diagnosis information may be the type of disease or stage, etc., and the treatment plan information may be drug information or surgical information, etc., which are not limited here.

[0034] Step 203 : In response to the sub-item data selection instruction, determine the target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data.

[0035] Specifically, a sub-item data selection instruction triggered by an interface or API can be received, and the sub-item data selection instruction specifies the specific criteria or conditions for the user to select from multiple sub-item data associated with the target object data. Then, according to the conditions or criteria determined by the sub-item data selection instruction, the target sub-item data corresponding to the target object data that meets the requirements can be retrieved and screened from at least one sub-item data corresponding to the target object data, thereby enhancing the flexibility of data processing and the convenience of user interaction, improving the accuracy and efficiency of data retrieval, and enhancing the user experience and system response speed. By allowing users to dynamically select target sub-item data, the user's personalized needs can be met more accurately, thereby promoting the effective use of data and decision support.

[0036] Among them, the sub-item data selection instruction can be a request or command sent through a system interface or a programming interface. The sub-item data selection instruction can be used to obtain detailed dimensional information corresponding to the target object data. The sub-item data selection instruction can include specific conditions, rules, or parameters for filtering or locating the target sub-item data, which are not limited here; the target sub-item data corresponding to the target object data can be one or more sub-item data that meet the conditions filtered out from multiple sub-item data contained in the target object data. The target sub-item data corresponding to the target object data can be obtained from at least one sub-item data corresponding to the target object data through algorithms such as condition matching or filtering, which are not limited here.

[0037] For example, the target object data may be the patient's medical record information, and the multiple sub-item data mapped from the patient's medical record information may be the patient's basic information, disease diagnosis information, and treatment plan information. In response to a sub-item data selection instruction, the patient's basic information is selected from the patient's basic information, disease diagnosis information, and treatment plan information as the target sub-item data corresponding to the target object data.

[0038] Step 204: Determine the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data according to the target sub-item data corresponding to the target object data.

[0039] Specifically, the target value corresponding to the target sub-item data can be determined according to the target object data through a pre-set mapping relationship, and the real-time value of the target sub-item data at the current time point can be obtained by real-time collection or reception of real-time data from data sources such as monitoring equipment or sensors, that is, the real-time value corresponding to the target sub-item data. This enhances the sensitivity and accuracy to changes in the state of the target object, improves the real-time and effectiveness of data processing, improves the scientific nature and accuracy of decision support, and optimizes management processes and operational efficiency by comparing target values ​​with real-time values ​​in real time.

[0040] Among them, the target value corresponding to the target sub-item data can be a numerical standard that is expected to be achieved or maintained for the target sub-item data under pre-set conditions. The target value corresponding to the target sub-item data can be obtained based on experience, specifications, or scientific calculations. The target value corresponding to the target sub-item data can be used to evaluate whether the current status of the target sub-item data meets the standards. Among them, the target sub-item data can be temperature, output, project brand, project format, or project revenue, etc., which are not limited here. The pre-set conditions can be production standards, safety specifications, customer needs, expected project revenue, etc., which are not limited here; the real-time value corresponding to the target sub-item data can be the actual numerical value corresponding to the target sub-item data obtained in real time through real-time monitoring equipment or sensors and other technical means, which are not limited here. The real-time value corresponding to the target sub-item data can be used to characterize the real status of the target sub-item data in real time. The real-time value corresponding to the target sub-item data can be dynamically changing and can be used to compare with the target value corresponding to the target sub-item data to determine whether measures need to be taken for adjustment.

[0041] For example, the target object data may be equipment on a production line, and the target sub-item data of the equipment may be vibration frequency. The corresponding target value may be determined based on the target sub-item data, which is a vibration frequency not exceeding 50 Hz. Then, the real-time value of the vibration frequency may be collected in real time by a sensor set on the equipment, which may be 45 Hz.

[0042] Step 205 , based on the preset matching condition, matching processing is performed on the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data to obtain feedback result data corresponding to the target sub-item data.

[0043] Specifically, according to preset matching rules or conditions, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data currently collected in real time can be compared and analyzed, and then the degree of conformity or difference between the two can be determined, and the feedback result data corresponding to the target sub-item data can be stored and fed back, wherein the preset matching rules or conditions include but are not limited to numerical ranges, threshold comparisons, pattern matching, or progress matching, etc., thereby enhancing the monitorability of the data and improving the accuracy of data processing. Through the control of preset matching conditions, the subjectivity and error rate of human judgment are reduced, the degree of automation is improved, and the work efficiency and response speed are improved.

[0044] Among them, the preset matching conditions may be pre-set rules or standards that can be used to determine the relationship between the target value and the real-time value, including but not limited to numerical equality, size relationship, string matching pattern, completion, and / or time range matching, etc., wherein the size relationship may be greater than, less than, or equal to a set threshold, which is not limited here; the feedback result data corresponding to the target sub-item data may be result information that can be fed back to the front end by comparing the preset matching conditions, and the feedback result data corresponding to the target sub-item data may be obtained by comparing the target value with the real-time value and performing logical judgment according to the preset matching conditions, and the feedback result data corresponding to the target sub-item data may be used in a variety of scenarios such as monitoring the operating status of the system, evaluating performance indicators, triggering alarm notifications, or assisting decision making, which are not limited here.

[0045] For example, the target sub-item data may be the size of a part, and the target value corresponding to the target sub-item data may be the size of the part, which is 30 cm. Sensors may be deployed to collect the size of the current part in real time as the real-time value corresponding to the target sub-item data. According to preset matching conditions, for example, the maximum allowable deviation range of the part size may be 0.5 cm, and then the target value corresponding to the target sub-item data may be compared with the real-time value corresponding to the target sub-item data. When the absolute value of the difference between the real-time value and the target value is 0.6 cm, that is, it exceeds the allowable range, the feedback result data record corresponding to the target sub-item data may be mismatched. When the absolute value of the difference between the real-time value and the target value is 0.4 cm, that is, it is within the allowable range, the feedback result data record corresponding to the target sub-item data may be matched.

[0046] According to the technical solution provided by the embodiment of the present disclosure, the target object data can be obtained through user input or from a preset database, and at least one sub-item data corresponding to the target object data can be mapped according to the mapping relationship between the target object data and the preset processable object database. In response to the sub-item data selection instruction, the target sub-item data corresponding to the target object data can be determined and selected according to the at least one sub-item data corresponding to the target object data. Then, according to the sub-item data corresponding to the target object data, the target value corresponding to the target object data and the real-time value corresponding to the target object data can be obtained, and according to the preset matching conditions, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are rule-matched to obtain feedback result data corresponding to the target sub-item data, thereby improving the readability and manageability of the data, ensuring the accuracy of the processing steps, improving the processing efficiency, and enhancing the flexibility and scalability of the processing flow.

[0047] In some embodiments, the feedback result data corresponding to the target sub-item data includes first feedback result data corresponding to the target sub-item data and second feedback result data corresponding to the target sub-item data; based on a preset matching condition, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are matched to obtain feedback result data corresponding to the target sub-item data, including: judging whether the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching condition; when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching condition, determining the first feedback result data corresponding to the sub-item data; when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data do not meet the preset matching condition, determining the second feedback result data corresponding to the sub-item data.

[0048] Specifically, according to the preset matching conditions, the target value corresponding to the target sub-item data can be compared with the real-time value corresponding to the target sub-item data obtained in real time to determine whether the two meet the preset matching criteria. If so, first feedback result data corresponding to the target sub-item data can be generated and determined, and the first feedback result data corresponding to the target sub-item data can be used to represent positive feedback such as normal, up to standard, or in line with expectations; if not, second feedback result data corresponding to the target sub-item data can be generated and determined, and the second feedback result data corresponding to the target sub-item data can be used to represent negative feedback such as abnormal, not up to standard, or needing attention.

[0049] Among them, the first feedback result data corresponding to the target sub-item data may be positive feedback data generated when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching conditions, and the first feedback result data corresponding to the target sub-item data may be used to characterize that the current state or performance of the target sub-item data is in line with expectations or meets the standards; the second feedback result data corresponding to the target sub-item data may refer to negative feedback data generated when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data do not meet the preset matching conditions, and the second feedback result data corresponding to the target sub-item data may be used to characterize that the current state or performance of the target sub-item data does not meet the expected standards or requirements.

[0050] For example, the target sub-item data may be temperature control in a production process, and the preset matching condition may be that the temperature must be within a preset range. The preset temperature range is the target value corresponding to the target sub-item data. Then, the real-time temperature data of each link can be collected in real time and compared with the preset temperature target value. If the real-time temperature value remains within the preset range, the first feedback result data "normal temperature" can be generated; if the real-time temperature value exceeds the preset range, the second feedback result data "too high / too low temperature" is generated.

[0051] According to the technical solution provided by the embodiments of the present disclosure, through preset matching conditions, the target value corresponding to the target sub-item data is compared with the real-time value corresponding to the target sub-item data obtained in real time to determine whether the two meet the preset matching criteria. If so, first feedback result data corresponding to the target sub-item data can be generated and determined. If not, second feedback result data corresponding to the target sub-item data can be generated and determined, thereby enhancing the degree of automation of data processing, improving the accuracy of monitoring and evaluation, and improving the timeliness of problem response. By automatically matching the target value corresponding to the target sub-item data with the real-time value corresponding to the target sub-item data and generating corresponding feedback result data, manual intervention is reduced and the timeliness and accuracy of feedback are ensured.

[0052] In some embodiments, the feedback result data corresponding to the target sub-item data includes second feedback result data corresponding to the target sub-item data; confirming the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data, including: performing data traversal processing on the preset processable object database to obtain at least one preset processable object database data; performing matching score calculation processing on the target object data and each preset processable object database data to obtain a matching value corresponding to each preset processable object database data; determining whether the matching value corresponding to each preset processable object database data meets a preset matching score threshold; when the matching value corresponding to at least one preset processable object database data meets the preset matching score threshold, determining at least one sub-item data corresponding to the target object data; the method also includes: when the matching value corresponding to each preset processable object database data does not meet the preset matching score threshold, determining the second feedback result data corresponding to the sub-item data.

[0053] Specifically, all data in the preset processable object database can be traversed, that is, the preset processable object database data can be traversed. The processable object database data can contain identifiable object features or attributes. The matching score between the target object data and each preset processable object database data can be calculated to obtain the matching value corresponding to the preset processable object database data. The matching value can be used to characterize the similarity or matching degree between the target object data and each preset processable object database data. It can be checked whether the matching value corresponding to the preset processable object database data reaches a preset matching score threshold. The preset matching score threshold can be pre-set based on a rule or data characteristic. The preset matching score threshold can be used to determine whether the matching result is valid. If at least one matching value corresponding to the preset processable object database data satisfies the preset matching score threshold condition, at least one sub-item data corresponding to the target object data is confirmed; if the matching values ​​corresponding to all preset processable object database data do not meet the preset matching score threshold, the second feedback result data corresponding to the sub-item data is determined and generated.

[0054] Among them, the preset processable object database data can be data pre-stored in a preset processable database, the preset processable object database data can be a data set of objects used for matching and comparing with the target object data, and the preset processable database data can include information such as the characteristics, attributes, or identifiers of the objects; the matching value corresponding to the preset processable object database data can be a quantitative value representing the similarity or degree of matching, and the matching value corresponding to the preset processable object database data can be calculated according to a preset algorithm by comparing the target object data with the preset processable object database data; the preset matching score threshold can be a preset numerical standard, and the preset matching score threshold can be used to judge the validity of the match between the target object data and the preset processable object database data, and the preset matching score threshold can be determined by business analysis, data testing, etc., and the preset matching score threshold can also be used to control the sensitivity and accuracy of data processing.

[0055] For example, the preset processable object database data can be the user's purchase history, browsing history, search keywords, etc., which are not limited here. The user's current browsing behavior of product details can be used as the target object data, matched with the historical data in the preset processable object database, and the matching value is calculated. If the matching value exceeds the preset matching score threshold, products similar to the user's interests are recommended as sub-item data; if the matching values ​​do not meet the threshold, the user can be prompted that the second feedback result data corresponding to the sub-item data is "No products that you may be interested in are found", or the user can be guided to conduct a more specific search.

[0056] According to the technical solution provided by the embodiments of the present disclosure, by traversing all data in a preset processable object database, that is, traversing the preset processable object database data, the matching score between the target object data and each preset processable object database data can be calculated to obtain the matching value corresponding to the preset processable object database data, and it can be checked whether the matching value corresponding to the preset processable object database data reaches the preset matching score threshold. If at least one matching value corresponding to the preset processable object database data satisfies the preset matching score threshold condition, at least one sub-item data corresponding to the target object data is confirmed; if all matching values ​​corresponding to the preset processable object database data do not meet the preset matching score threshold, the second feedback result data corresponding to the sub-item data is determined and generated, thereby enhancing the accuracy and efficiency of data processing, improving the accuracy of matching between the target object data and the sub-item data, and improving the user experience and system automation level.

[0057] In some embodiments, in response to a sub-item data selection instruction, target sub-item data corresponding to the target object data is determined based on at least one sub-item data corresponding to the target object data, including: parsing the sub-item data selection instruction to obtain a selection condition corresponding to the sub-item data selection instruction; retrieving at least one sub-item data corresponding to the target object data to obtain a sub-item data set; and determining the target sub-item data corresponding to the target object data based on the selection condition and the sub-item data set corresponding to the sub-item data selection instruction.

[0058] Specifically, by parsing the sub-item data selection instruction, the corresponding selection conditions can be extracted, including but not limited to the range of attribute values ​​or keyword matching, and then by traversing all the sub-item data corresponding to the target object data, the sub-item data that meets the basic association conditions can be obtained through database query, memory retrieval, or file scanning, etc., which are not limited here, that is, the sub-item data set. The sub-item data set can be screened according to the selection conditions corresponding to the sub-item data selection instruction obtained by the parsing to determine the target sub-item data corresponding to the target object data.

[0059] Among them, the selection condition corresponding to the sub-item data selection instruction can be clearly pointed out by the instruction, and can be used to determine the standard or rule of the sub-item data from multiple sub-item data; the sub-item data set can be a set of all sub-item data obtained from the sub-item data corresponding to the target object data through retrieval processing, and the sub-item data set can be obtained through database query, memory retrieval, or file scanning, etc., which is not limited here. The sub-item data set can include all sub-item data that meet the screening conditions.

[0060] For example, a user can use a sub-item data selection instruction, such as clicking the "Filter" button and selecting "Color: Black", "Material: Silicone" and other conditions to determine the selection conditions corresponding to the sub-item data selection instruction, and then retrieve all available accessories, that is, the sub-item data set, which can be filtered according to the user's selection conditions to obtain the target sub-item data corresponding to the target object data.

[0061] According to the technical solution provided by the embodiment of the present disclosure, by parsing the sub-item data selection instruction, the corresponding selection conditions are extracted, and then by traversing all the sub-item data corresponding to the target object data, the sub-item data that meets the basic association conditions, that is, the sub-item data set, can be obtained. According to the selection conditions corresponding to the parsed sub-item data selection instruction, the sub-item data set can be screened to determine the target sub-item data corresponding to the target object data, thereby enhancing the flexibility of data processing, being able to dynamically select target sub-item data, improving the efficiency of data retrieval, reducing the amount of data processing through precise matching and screening, and improving the user experience.

[0062] In some embodiments, based on the target sub-item data corresponding to the target object data, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are determined, including: mapping the target sub-item data corresponding to the target object data to obtain the target value corresponding to the target sub-item data; acquiring the object real-time data; querying the object real-time data based on the target sub-item data corresponding to the target object data to obtain the real-time value corresponding to the target sub-item data.

[0063] Specifically, each target sub-item data in the target object data can be processed according to a preset mapping relationship to obtain a target value corresponding to the target sub-item data. The target value corresponding to the target sub-item data can be used to characterize the expected or standard state of the target sub-item data. The object real-time data can be obtained through a real-time data source. The real-time data source includes but is not limited to a database or a sensor cluster, etc. The object real-time data can be used to characterize the current actual state of the target object data. Then, the identifier or keyword of the target sub-item data corresponding to the target object data can be used to query in the object real-time data to extract the real-time value corresponding to the target sub-item data.

[0064] Among them, the real-time data of the object can be dynamic data related to the current state of the target object data. The real-time data of the object can be obtained through a real-time data acquisition system or a real-time database and other structures, which are not limited here. The real-time data acquisition system includes but is not limited to Internet of Things devices or sensors, etc. The real-time data acquisition system can reflect the various attributes, states, or behaviors of the target object data in real time. The real-time data of the object can be used for real-time warning, performance evaluation, or decision support and other aspects, which are not limited here.

[0065] For example, the target object data may be a machine device on a production line, and the target sub-item data corresponding to the target object data may be the temperature of the device. The target value of the device temperature can be set to no more than 60°C through a preset mapping rule. The temperature data of the device can then be acquired in real time through the sensor network on the production line. Based on the temperature identifier corresponding to the device, a query is performed in the real-time data to obtain the actual temperature of the device as a real-time value.

[0066] According to the technical solution provided by the embodiment of the present disclosure, each target sub-item data in the target object data is processed through a preset mapping relationship to obtain the target value corresponding to the target sub-item data, and the object real-time data can be obtained through a real-time data source, and then the identifier or keyword of the target sub-item data corresponding to the target object data can be used to query in the object real-time data to extract the real-time value corresponding to the target sub-item data, thereby enhancing the degree of automation of data processing, improving the accuracy and efficiency of data processing, ensuring the consistency between the target value and the real-time value through direct mapping and precise query, and improving the real-time and response speed of target object data status monitoring.

[0067] In some embodiments, the above-mentioned data processing method also includes: encapsulating the feedback result data corresponding to the target sub-item data to obtain a data packet corresponding to the feedback result data; serializing the data packet corresponding to the feedback result data to obtain serialized data corresponding to the data packet; and determining the display data corresponding to the feedback result data based on the serialized data corresponding to the data packet.

[0068] Specifically, the feedback result data corresponding to the target sub-item data can be encapsulated and packaged according to preset formats and rules to obtain a data packet. Then, the data packet corresponding to the feedback result data can be serialized and converted into a format suitable for storage or transmission, including but not limited to JSON or XML, to obtain serialized data corresponding to the data packet. The serialized data corresponding to the data packet can be parsed according to the structure and content of the serialized data corresponding to the data packet to determine the display form of the feedback result data for display to the user or the system, that is, the display data corresponding to the feedback result data. The display data corresponding to the feedback result data includes but is not limited to warning information, charts, or reports.

[0069] Among them, the data packet corresponding to the feedback result data can be a data set that encapsulates the feedback result data according to a preset structure and format, and the data packet corresponding to the feedback result data can contain all relevant information of the feedback result data and can be identified by a specific identifier or keyword; the serialized data corresponding to the data packet can be the information in the data packet converted into a standardized data representation form; the display data corresponding to the feedback result data can be data parsed by the serialized data corresponding to the data packet, and the display data corresponding to the feedback result data can be used to display to a user or a system, and the display data corresponding to the feedback result data includes but is not limited to text, numbers, charts, or reports and other forms.

[0070] For example, in an environmental monitoring system, the target object data is the regional air quality, and the target sub-item data may be the ozone concentration. The real-time value of the ozone concentration can be obtained through real-time monitoring equipment and compared with the preset target value to obtain feedback result data. If the ozone concentration does not exceed the standard, the feedback result data can be encapsulated into a data packet and serialized. Based on the analysis results of the serialized data, the display data corresponding to the feedback result data can be obtained, such as a chart or warning information of the air quality index, and displayed on the front-end device.

[0071] According to the technical solution provided by the embodiment of the present disclosure, by encapsulating the feedback result data corresponding to the target sub-item data, the feedback result data corresponding to the target sub-item data is packaged according to a preset format and rules to obtain a data packet, and then the data packet corresponding to the feedback result data can be serialized, and the data packet corresponding to the feedback result data is converted into a format suitable for storage or transmission to obtain serialized data corresponding to the data packet. According to the structure and content of the serialized data corresponding to the data packet, the serialized data corresponding to the data packet can be parsed and the display form of the feedback result data for display to the user or the system, that is, the display data corresponding to the feedback result data, can be determined. In this way, through encapsulation and serialization processing, the feedback result data can be transmitted and shared between different systems or platforms, thereby enhancing the portability and reusability of the data. The serialization process can include mechanisms such as encryption and verification, thereby improving the security and integrity of data processing, and enhancing the user experience and system responsiveness.

[0072] In some embodiments, display data corresponding to the feedback result data is determined based on the serialized data corresponding to the data packet, including: deserializing the serialized data corresponding to the data packet to obtain a feedback result data object; rendering the feedback result data object to obtain display data corresponding to the feedback result data.

[0073] Specifically, the serialized data corresponding to the received data packet can be decoded and parsed, and the serialized data corresponding to the data packet can be converted into a data structure that can be directly operated, namely, a feedback result data object. The deserialization process includes restoring the data in binary stream or text format into structured data, wherein the structured data includes but is not limited to JSON, XML, or custom objects, etc. The feedback result data object can be formatted according to preset rendering logic or template, including but not limited to adding styles or adjusting layouts, etc., to obtain display data corresponding to the feedback result data that can be directly displayed on the user interface.

[0074] Among them, the feedback result data object can be a structured data representation, and the feedback result data object can be obtained by deserializing the serialized data corresponding to the data packet. The feedback result data object can contain business data, including but not limited to query results, operation status, or error information, etc. The feedback result data object structure can be designed according to requirements, including but not limited to a key-value pair set, a nested object, or an array, etc. The feedback result data object can also be used for rendering the front-end page.

[0075] For example, the serialized data corresponding to the data packet may be serialized data containing order information. The front end receives the serialized data containing order information and may perform deserialization processing to obtain a feedback result data object containing order details, such as order number, product list, or payment status. The front end may render the order list page through the template engine based on the content of the feedback result data object and display it to the user.

[0076] According to the technical solution provided by the embodiment of the present disclosure, by decoding and parsing the serialized data corresponding to the received data packet, the serialized data corresponding to the data packet is converted into a directly operable data structure, namely, a feedback result data object. The feedback result data object can be formatted according to a preset rendering logic or template to obtain display data corresponding to the feedback result data that can be directly displayed on the user interface, thereby enhancing the readability and ease of use of the data, improving the response speed and interactive experience of the user interface, improving the efficiency and accuracy of the system in processing feedback results, and accelerating the transmission and display of information from the back end to the front end.

[0077] All the above optional technical solutions can be arbitrarily combined to form optional embodiments of the present disclosure, and will not be described in detail here.

[0078] The following are embodiments of the device disclosed herein, which can be used to execute the method embodiments disclosed herein. For details not disclosed in the device embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0079] Figure 3Schematic diagram of a data processing device provided by an embodiment of the present disclosure. Figure 3 As shown, the data processing device includes:

[0080] An acquisition module 301 is used to acquire target object data;

[0081] The first processing module 302 is used to confirm the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data;

[0082] A first determination module 303, configured to determine, in response to a sub-item data selection instruction, target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data;

[0083] A second determination module 304 is used to determine a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data according to the target sub-item data corresponding to the target object data;

[0084] The second processing module 305 is used to perform matching processing on the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data based on a preset matching condition, so as to obtain feedback result data corresponding to the target sub-item data.

[0085] According to the technical solution provided by the embodiment of the present disclosure, the target object data can be obtained through user input or from a preset database, and at least one sub-item data corresponding to the target object data can be mapped according to the mapping relationship between the target object data and the preset processable object database. In response to the sub-item data selection instruction, the target sub-item data corresponding to the target object data can be determined and selected according to the at least one sub-item data corresponding to the target object data. Then, according to the sub-item data corresponding to the target object data, the target value corresponding to the target object data and the real-time value corresponding to the target object data can be obtained, and according to the preset matching conditions, the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data are rule-matched to obtain feedback result data corresponding to the target sub-item data, thereby improving the readability and manageability of the data, ensuring the accuracy of the processing steps, improving the processing efficiency, and enhancing the flexibility and scalability of the processing flow.

[0086] In some embodiments, the second processing module 305 is specifically used to determine whether the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching conditions; when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching conditions, determine the first feedback result data corresponding to the sub-item data; when the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data do not meet the preset matching conditions, determine the second feedback result data corresponding to the sub-item data.

[0087] In some embodiments, the first processing module 302 is specifically used to perform data traversal processing on a preset processable object database to obtain at least one preset processable object database data; perform matching score calculation processing on the target object data and each preset processable object database data to obtain a matching value corresponding to each preset processable object database data; determine whether the matching value corresponding to each preset processable object database data satisfies a preset matching score threshold; when the matching value corresponding to at least one preset processable object database data satisfies the preset matching score threshold, determine at least one sub-item data corresponding to the target object data; the method also includes: when the matching value corresponding to each preset processable object database data does not satisfy the preset matching score threshold, determine second feedback result data corresponding to the sub-item data.

[0088] In some embodiments, the first determination module 303 is specifically used to parse and process the sub-item data selection instruction to obtain the selection conditions corresponding to the sub-item data selection instruction; retrieve and process at least one sub-item data corresponding to the target object data to obtain a sub-item data set; and determine the target sub-item data corresponding to the target object data based on the selection conditions and the sub-item data set corresponding to the sub-item data selection instruction.

[0089] In some embodiments, the second determination module 304 is specifically used to map the target sub-item data corresponding to the target object data to obtain the target value corresponding to the target sub-item data; obtain the real-time data of the object; and query the real-time data of the object based on the target sub-item data corresponding to the target object data to obtain the real-time value corresponding to the target sub-item data.

[0090] In some embodiments, the above-mentioned data processing device is also used to encapsulate the feedback result data corresponding to the target sub-item data to obtain a data packet corresponding to the feedback result data; serialize the data packet corresponding to the feedback result data to obtain serialized data corresponding to the data packet; and determine the display data corresponding to the feedback result data based on the serialized data corresponding to the data packet.

[0091] In some embodiments, based on the serialized data corresponding to the data packet, the display data corresponding to the feedback result data is determined to be specifically used for deserializing the serialized data corresponding to the data packet to obtain a feedback result data object; and rendering the feedback result data object to obtain display data corresponding to the feedback result data.

[0092] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0093] Figure 4Schematic diagram of an electronic device 4 provided in an embodiment of the present disclosure. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, the steps in the above-mentioned method embodiments are implemented. Alternatively, when the processor 401 executes the computer program 403, the functions of the modules / units in the above-mentioned device embodiments are implemented.

[0094] The electronic device 4 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that Figure 4 The electronic device 4 is merely an example and does not limit the electronic device 4 , and may include more or less components than those shown in the figure, or different components.

[0095] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0096] The memory 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. The memory 402 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0097] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units.

[0098] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium (e.g., a computer-readable storage medium). Based on this understanding, the present disclosure implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0099] The above embodiments are only used to illustrate the technical solutions of the present disclosure, rather than to limit them. Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should all be included in the protection scope of the present disclosure.

Claims

1. A data processing method, characterized in that: include: Get target object data; Mapping the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data; In response to a sub-item data selection instruction, determining target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data; Determine, according to the target sub-item data corresponding to the target object data, a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data; Based on a preset matching condition, a matching process is performed on the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data to obtain feedback result data corresponding to the target sub-item data.

2. The data processing method according to claim 1, characterized in that: The feedback result data corresponding to the target sub-item data includes first feedback result data corresponding to the target sub-item data and second feedback result data corresponding to the target sub-item data; The matching process is performed on the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data based on the preset matching condition to obtain feedback result data corresponding to the target sub-item data, including: Determine whether the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching condition; When the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data meet the preset matching condition, determining first feedback result data corresponding to the sub-item data; When the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data do not satisfy the preset matching condition, second feedback result data corresponding to the sub-item data is determined.

3. The data processing method according to claim 1, characterized in that: The feedback result data corresponding to the target sub-item data includes second feedback result data corresponding to the target sub-item data; The confirming and processing the target object data based on the preset processable object database to obtain at least one sub-item data corresponding to the target object data includes: Performing data traversal processing on the preset processable object database to obtain at least one preset processable object database data; Performing matching score calculation processing on the target object data and each of the preset processable object database data to obtain a matching value corresponding to each of the preset processable object database data; Determining whether the matching value corresponding to each of the preset processable object database data meets a preset matching score threshold; When a matching value corresponding to at least one of the preset processable object database data satisfies a preset matching score threshold, determining at least one sub-item data corresponding to the target object data; The method further includes: when the matching value corresponding to each of the preset processable object database data does not meet a preset matching score threshold, determining second feedback result data corresponding to the sub-item data.

4. The data processing method according to claim 1, characterized in that: The step of determining, in response to the sub-item data selection instruction, target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data comprises: The sub-item data selection instruction is parsed to obtain a selection condition corresponding to the sub-item data selection instruction; Performing a search process on at least one sub-item data corresponding to the target object data to obtain a sub-item data set; The target sub-item data corresponding to the target object data is determined according to the selection condition corresponding to the sub-item data selection instruction and the sub-item data set.

5. The data processing method according to claim 1, characterized in that: The determining, according to the target sub-item data corresponding to the target object data, a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data comprises: Mapping the target sub-item data corresponding to the target object data to obtain a target value corresponding to the target sub-item data; Get real-time data of the object; The real-time data of the object is queried based on the target sub-item data corresponding to the target object data to obtain the real-time value corresponding to the target sub-item data.

6. The data processing method according to claim 1, characterized in that: The method further comprises: Encapsulating the feedback result data corresponding to the target sub-item data to obtain a data packet corresponding to the feedback result data; Serializing the data packet corresponding to the feedback result data to obtain serialized data corresponding to the data packet; The display data corresponding to the feedback result data is determined according to the serialized data corresponding to the data packet.

7. The data processing method according to claim 6, characterized in that: The determining, according to the serialized data corresponding to the data packet, display data corresponding to the feedback result data comprises: Deserialize the serialized data corresponding to the data packet to obtain a feedback result data object; The feedback result data object is rendered to obtain display data corresponding to the feedback result data.

8. A data processing device, characterized in that: include: An acquisition module is used to acquire target object data; A first processing module, configured to perform confirmation processing on the target object data based on a preset processable object database to obtain at least one sub-item data corresponding to the target object data; A first determination module, configured to determine, in response to a sub-item data selection instruction, target sub-item data corresponding to the target object data according to at least one sub-item data corresponding to the target object data; A second determination module, configured to determine, according to the target sub-item data corresponding to the target object data, a target value corresponding to the target sub-item data and a real-time value corresponding to the target sub-item data; The second processing module is used to match the target value corresponding to the target sub-item data and the real-time value corresponding to the target sub-item data based on a preset matching condition to obtain feedback result data corresponding to the target sub-item data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: 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 readable storage medium storing a computer program, 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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