Multi-source heterogeneous data integration method, electronic equipment, medium and product

Abstract

The invention relates to the technical field of data integration, in particular to a multi-source heterogeneous data integration method, electronic equipment, a medium and a product, and the method comprises the following steps: screening multi-source heterogeneous data based on a target index condition to obtain at least one piece of effective multi-source heterogeneous data; performing data preprocessing on the effective multi-source heterogeneous data to obtain effective processed multi-source heterogeneous data; determining at least one target to-be-filled directory from a preset initial data topic domain based on the target index condition; identifying data features contained in each piece of effectively processed multi-source heterogeneous data, determining a target to-be-filled catalogue corresponding to each piece of effectively processed multi-source heterogeneous data based on each data feature, and integrating the effectively processed multi-source heterogeneous data corresponding to each target to-be-filled catalogue, obtaining to-be-filled data corresponding to each target to-be-filled directory; and determining a target integrated document according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory. The accuracy of the data integration result can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data integration, and in particular to a multi-source heterogeneous data integration method, electronic equipment, medium and product. Background Art

[0002] With the development of medical information technology, the amount of data accumulated within hospitals is becoming increasingly large, and different data sources may be different. For example, the data source may be a hospital information system, a laboratory information system, etc. The data format, structure and type corresponding to different data sources are significantly different. By integrating and analyzing multi-source heterogeneous data, it is convenient to reflect the operating status of the hospital and provide strong support for medical quality control.

[0003] Related technologies generally organize multi-source heterogeneous data by comprehensively extracting data from various systems within the hospital and physically integrating the entire data content. However, with the continuous expansion and upgrading of hospital business, especially the massive emergence of multi-source heterogeneous data such as unstructured data and imaging materials, the use of traditional data integration methods may introduce a large amount of data that is irrelevant to the current quality control tasks, increasing the complexity and cost of data processing, and may also reduce the accuracy of data integration. Summary of the invention

[0004] In order to reduce the complexity of the data processing process and thus improve the accuracy of the data integration results, the present application provides a multi-source heterogeneous data integration method, electronic device, storage medium and product.

[0005] In the first aspect, the present application provides a method for integrating multi-source heterogeneous data, which adopts the following technical solution: A multi-source heterogeneous data integration method, comprising: Acquire multi-source heterogeneous data and target indicator conditions, and screen the multi-source heterogeneous data based on the target indicator conditions to obtain at least one valid multi-source heterogeneous data, where the valid multi-source heterogeneous data is the multi-source heterogeneous data that meets the target indicator conditions; Identify a target data volume corresponding to the at least one valid multi-source heterogeneous data, and when the target data volume is not higher than a preset data volume, perform data preprocessing on the at least one valid multi-source heterogeneous data to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data, wherein the data preprocessing includes but is not limited to data normalization processing, deduplication processing, and noise reduction processing; Determine at least one target to-be-filled directory from a preset initial data subject domain based on the target indicator condition, wherein the initial data subject domain includes a plurality of to-be-filled directories; Identify the data features contained in each effectively processed multi-source heterogeneous data, and determine the target to-be-filled directory corresponding to each effectively processed multi-source heterogeneous data based on each data feature, integrate the effectively processed multi-source heterogeneous data corresponding to each target to-be-filled directory, and obtain the to-be-filled data corresponding to each target to-be-filled directory; The target integration document corresponding to the target indicator condition is determined according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory, and the target integration document is fed back.

[0006] By adopting the above technical solution, multi-source heterogeneous data is screened by target indicator conditions, which is convenient for eliminating invalid data in multi-source heterogeneous data, and by reducing the number of data in the data processing process, it is convenient to improve the rate and accuracy of the data processing process. Since multi-source heterogeneous data has a wide range of sources and various types, and there are large differences in units or magnitudes between different data, by preprocessing effective multi-source heterogeneous data, the quality of effective multi-source heterogeneous data is improved, data noise and data redundancy are reduced, and it is also convenient to compare and analyze effective multi-source heterogeneous data on the same scale, so as to avoid data misunderstanding or misjudgment due to differences between data. According to the target indicator conditions, the target directory to be filled is determined from the preset initial data subject domain, and the effectively processed multi-source heterogeneous data is accurately allocated to the corresponding directory based on data characteristics, which not only simplifies the data integration process, but also facilitates improving the accuracy of determining the target integration document.

[0007] In one possible implementation, the method further includes: When the target data volume is higher than a preset data volume, determining a corresponding target buffer area based on the target data volume; The at least one valid multi-source heterogeneous data is written into the target buffer, and data preprocessing is performed on the at least one valid multi-source heterogeneous data written into the target buffer to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data.

[0008] By adopting the above technical solution, when the target data volume is large, all valid multi-source heterogeneous data are imported into the target buffer and then data preprocessing is performed on the valid multi-source heterogeneous data, rather than performing data preprocessing during the data acquisition process, so as to reduce the data transmission delay caused by data preprocessing. In addition, all valid multi-source heterogeneous data are determined before performing data preprocessing operations, that is, the valid multi-source heterogeneous data are processed centrally, which is convenient for effectively utilizing computing resources and improving the efficiency of the data processing process. In addition, the corresponding target buffer is determined based on the target data volume, so as to reduce the situation of data loss during data storage.

[0009] In a possible implementation, determining the target integration document corresponding to the target indicator condition according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory includes: Identify the docking mode, and determine the corresponding target docking technology based on a preset docking mapping relationship and the docking mode, wherein the preset docking mapping relationship is a correspondence relationship between the docking mode and the target docking technology; Perform semantic recognition on each effectively processed multi-source heterogeneous data, and determine whether the effectively processed multi-source heterogeneous data contains associated heterogeneous data based on the semantic recognition result. When associated heterogeneous data exists, establish an associated index between the corresponding effectively processed multi-source heterogeneous data, and the semantic recognition results corresponding to the associated heterogeneous data contain the same semantic entity segmentation; Based on the target docking technology and the associated index, each to-be-filled data is added to the corresponding to-be-filled directory to obtain a target integration document corresponding to the target indicator condition.

[0010] By adopting the above technical solution, it is convenient to accurately determine the docking technology corresponding to the docking method based on the preset docking mapping relationship, and to improve the accuracy of the docking process by improving the adaptability between the docking method and the docking technology. In addition, the associated heterogeneous data in the effective multi-source heterogeneous data is determined by semantic recognition, and the associated index between the associated heterogeneous data is established. Finally, the target integrated document is determined based on the associated index, which is convenient for relevant personnel to perform associated queries and comparisons during the access process of the target integrated document. Finally, the data to be filled is automatically added to the corresponding directory to be filled through the target docking technology, which improves the accuracy of the data filling process and also helps to reduce errors caused by human intervention.

[0011] In a possible implementation, after generating the target integration document, the method further includes: Identify whether there is a preset missing identifier in the target integrated document, and determine the field containing the preset missing identifier as a missing field; Determine whether the missing field contains a missing associated index; If so, determining replacement data from the corresponding associated heterogeneous data based on the missing associated index, and updating the missing field based on the replacement data to update the target integrated document; If not, a prompt message is generated based on the missing field, and the prompt message is superimposed on the target integrated document.

[0012] By adopting the above technical solution, after generating the target integrated document, whether the target integrated document contains missing information is detected, so that the missing fields can be discovered and located in time, and the replacement data can be determined from the associated heterogeneous data according to the missing associated index corresponding to the actual field, so as to improve the speed of completing the missing fields, and ensure that the data in the target integrated document is as complete as possible, so as to reduce the analysis and decision-making errors caused by missing data. For the missing fields that cannot be filled automatically, prompt information is generated and superimposed on the document, so as to prompt the relevant staff to check the missing content or complete it manually.

[0013] In one possible implementation, the method further includes: Identify whether the target integrated document contains a logical directory, where the logical directory is a directory to be filled that contains a preset logical identifier; If the logic directory is included, obtaining the logic formula corresponding to the preset logic identifier and determining the logic field corresponding to the preset logic identifier from the to-be-filled data corresponding to the logic directory; A logic value corresponding to the logic directory is determined based on the logic formula and the logic field, and the logic value is written into a corresponding position of the logic directory in the target integrated document.

[0014] By adopting the above technical solution, it is easy to automatically identify whether the target integrated document contains a logical directory, reduce manual intervention in the logical operation process, and improve the accuracy of the operation results. In addition, since the logical value is automatically calculated by using preset logical formulas and logical fields, it is easy to avoid errors or omissions caused by manual filling, thereby improving the accuracy of determining the logical value.

[0015] In one possible implementation, the method further includes: When a detail access instruction is detected, identifying the detail content corresponding to the detail access instruction; When the detailed content includes multiple items, a detailed display mode may be determined based on the detailed access instruction, and a target detailed content may be determined based on the detailed display mode; Identify the detail fields corresponding to the target detail content and the detail date corresponding to each detail field, sort all detail fields based on the detail date to obtain a detail list, and feed back the detail list; Identify whether the detail list contains a preset detail missing identifier. If so, generate detail prompt information based on the detail missing identifier and superimpose the detail prompt information into the detail list.

[0016] By adopting the above technical solution, by automatically identifying the detail access instruction and determining the corresponding detail content, it is convenient to obtain the required information more quickly. When there are multiple detail contents, by identifying the detail display method from the detail access instruction, it is convenient to quickly select the content that needs to be accessed or viewed from multiple detail contents. In addition, when it is necessary to further view the detail content, multiple detail fields can be sorted according to the detail date corresponding to each detail field, and feedback is provided in the form of a detail list, which is convenient for improving the standardization of the display of the detail fields. It is also possible to timely discover the preset detail missing marks that may exist in the detail list through defect identification, and promptly complete the missing content, which is convenient for improving data integrity.

[0017] In a second aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the multi-source heterogeneous data integration method.

[0018] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the multi-source heterogeneous data integration method.

[0019] In a fourth aspect, the present application provides a computer program product, which adopts the following technical solution: A computer program product includes a computer program, and when the computer program is executed by a processor, the multi-source heterogeneous data integration method is implemented.

[0020] In summary, the present application includes at least one of the following beneficial technical effects: By screening multi-source heterogeneous data through target indicator conditions, it is convenient to eliminate invalid data in multi-source heterogeneous data, and by reducing the number of data in the data processing process, it is convenient to improve the speed and accuracy of the data processing process. Since multi-source heterogeneous data has a wide range of sources, diverse types, and there are large differences in units or magnitudes between different data, by pre-processing effective multi-source heterogeneous data, the quality of effective multi-source heterogeneous data is improved, data noise and data redundancy are reduced, and it is also convenient to compare and analyze effective multi-source heterogeneous data on the same scale, so as to avoid data misunderstanding or misjudgment due to differences between data. According to the target indicator conditions, the target directory to be filled is determined from the preset initial data subject domain, and the effectively processed multi-source heterogeneous data is accurately allocated to the corresponding directory based on data characteristics, which not only simplifies the data integration process, but also facilitates improving the accuracy of determining the target integration document; By importing all valid multi-source heterogeneous data into the target buffer and then performing data preprocessing on the valid multi-source heterogeneous data when the target data volume is large, rather than performing data preprocessing during the data acquisition process, it is convenient to reduce the data transmission delay caused by data preprocessing. In addition, all valid multi-source heterogeneous data are determined before performing data preprocessing operations, that is, the valid multi-source heterogeneous data are processed centrally, which is convenient for effective use of computing resources and improving the efficiency of the data processing process. In addition, the corresponding target buffer is determined based on the target data volume, which is convenient to reduce data loss during data storage. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a flowchart of a multi-source heterogeneous data integration method in an embodiment of the present application; Figure 2 This is a schematic diagram showing a logic value in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0022] The following is combined with Figures 1 to 3 This application is described in further detail.

[0023] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained with the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information needs to obtain the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0026] Specifically, the embodiment of the present application provides a multi-source heterogeneous data integration method, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0027] refer to Figure 1 , Figure 1 : is a flow chart of a multi-source heterogeneous data integration method in an embodiment of the present application, the method includes steps S110-S150, wherein: Step S110: acquiring multi-source heterogeneous data and target indicator conditions, and screening the multi-source heterogeneous data based on the target indicator conditions to obtain at least one valid multi-source heterogeneous data, where the valid multi-source heterogeneous data is multi-source heterogeneous data that meets the target indicator conditions.

[0028] Specifically, multi-source heterogeneous data refers to data generated within the hospital, including but not limited to data from the HIS (Hospital Information System) hospital information system, LIS (Laboratory Information System) test information system, PACS (Picture Archiving and Communication Systems) image storage and transmission system, and HRP (Human Resource Planning) human resource planning system. The data stored in the HIS hospital information system is rich and complex, including but not limited to patient information, medical order information, drug information, test information, financial information, etc., which can collect, store, process, extract, transmit, summarize, and process the data generated in various stages of medical activities to generate various information, thereby providing comprehensive and automated management and various services for the overall operation of the hospital; the LIS test information system is an information management system that uses computer networks and information technology to realize the collection, storage, processing, transmission, query of clinical laboratory business information and management information, and provides analysis and diagnosis support; the PACS image storage and transmission system mainly stores data related to medical imaging, imaging examination information, image management and diagnosis data, etc.; the HRP human resource planning system generally stores basic employee information, organizational structure information, human resource status data, and recruitment and employment data, etc. Data from different systems may use completely different data structures, such as tables, key-value pairs, documents, images, etc. In addition, data from different systems may also use different storage formats, such as CSV, Excel, JSON, and XML. Therefore, data from different systems can be identified as multi-source heterogeneous data.

[0029] The target indicator conditions are the conditions corresponding to the indicators that need to be met when the hospital needs to be upgraded or optimized. The target indicators can be hospital quality inspection indicators, tertiary indicators, and hospital department management indicators, etc. Different indicators have different corresponding indicator conditions. The specific target indicators are not specifically limited in the embodiments of this application and can be determined according to the evaluation needs of the relevant hospitals. The target indicator conditions correspond to the target indicators and can be imported in advance by relevant staff.

[0030] After obtaining multi-source heterogeneous data, not all multi-source heterogeneous data need to participate in the target indicator evaluation, that is, the obtained multi-source heterogeneous data may contain non-essential data. The target indicator conditions can be used to eliminate the non-essential data contained in the multi-source heterogeneous data to obtain effective multi-source heterogeneous data. For example, the data that need to be evaluated by the target indicator conditions include data a, data b, data c, and data d. The obtained multi-source heterogeneous data may contain data a, data b, data c, data d, data e, and data f. The target indicator conditions can be used to eliminate data e and data f, and the effective multi-source heterogeneous data obtained are data a, data b, data c, and data d. That is, by evaluating and analyzing data a, data b, data c, and data d, it is convenient to judge whether the hospital meets the target indicators.

[0031] Step S120: Identify a target data volume corresponding to at least one valid multi-source heterogeneous data. When the target data volume is not higher than a preset data volume, perform data preprocessing on at least one valid multi-source heterogeneous data to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data. The data preprocessing includes but is not limited to data normalization, deduplication and noise reduction.

[0032] Specifically, after determining at least one valid multi-source heterogeneous data, it is necessary to identify the target data volume of the at least one valid multi-source data. Different target data volumes may correspond to different processing methods. The processing method of at least one valid multi-source heterogeneous data can be distinguished based on the preset data volume.

[0033] When the target data volume is not higher than the preset data volume, at least one valid multi-source heterogeneous data can be directly preprocessed. After the data preprocessing operation, the complex and diverse multi-source heterogeneous data can be converted into unified, standardized, and high-quality data, so as to provide a data basis for the subsequent target indicator evaluation. Among them, since the effective multi-source heterogeneous data often have different dimensions and numerical ranges, if the effective multi-source heterogeneous data is directly evaluated, the weight of some effective multi-source data in the evaluation process may be too large or too small, which may affect the accuracy of the evaluation and analysis results.

[0034] The effective multi-source heterogeneous data can also be deduplicated, wherein the deduplication operation can remove the duplicate data content contained in the effective multi-source heterogeneous data to ensure the uniqueness and accuracy of the effective multi-source heterogeneous data. The effective multi-source heterogeneous data can be deduplicated by comparing the key fields in the effective multi-source heterogeneous data. The effective multi-source heterogeneous data can also be processed using a preset deduplication algorithm, wherein the preset deduplication algorithm can be a hash-based deduplication algorithm, a sorting-based deduplication algorithm, a bitmap-based deduplication algorithm, etc. The specific preset deduplication algorithm is not specifically limited in the embodiments of the present application, as long as it can deduplicate the effective multi-source heterogeneous data.

[0035] The effective multi-source heterogeneous data can also be subjected to noise reduction processing to reduce the noise and interference factors in the effective multi-source heterogeneous data. The noise and interference factors contained in the effective multi-source heterogeneous data may be sensor noise, transmission errors, human errors, etc. After the effective multi-source heterogeneous data is subjected to noise reduction processing, it is convenient to reduce the negative impact of noise interference factors on the evaluation of the effective multi-source heterogeneous data, that is, it is convenient to improve the accuracy of the evaluation of the effective multi-source heterogeneous data. In addition to normalization, deduplication and noise reduction processing, the preprocessing of multi-source heterogeneous data may also include steps such as data cleaning, data conversion, and data integration. The specific data preprocessing operations performed on the effective multi-source heterogeneous data are not specifically limited in the embodiments of the present application, as long as the quality and effectiveness of the effective processing of multi-source heterogeneous data can be improved.

[0036] Furthermore, when the target data volume is higher than the preset data volume, the corresponding target buffer is determined based on the target data volume; at least one valid multi-source heterogeneous data is written into the target buffer, and data preprocessing is performed on at least one valid multi-source heterogeneous data written into the target buffer to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data.

[0037] Specifically, when the target data volume is higher than the preset data volume, a target buffer can be allocated for all valid multi-source heterogeneous data according to the target data volume, that is, when the target data volume is higher than the preset data volume, all valid multi-source heterogeneous data can be stored in the target buffer first, and then all valid multi-source heterogeneous data are preprocessed, and the storage volume of the target buffer is not higher than the target data volume. When the target data volume is large, all valid multi-source heterogeneous data are imported into the target buffer and then preprocessed, rather than preprocessing during the data acquisition process, so as to reduce the data transmission delay caused by data preprocessing.

[0038] The target buffer can be a Hive data warehouse, or a TiDB database, an Oracle database, etc. The specific buffer is not specifically limited in the embodiments of this application, as long as it can temporarily store valid multi-source heterogeneous data. The method of preprocessing the valid multi-source heterogeneous data in the target buffer can refer to the method of preprocessing at least one valid multi-source heterogeneous data in the above embodiment, which will not be repeated here.

[0039] Step S130: determining at least one target to-be-filled directory from a preset initial data subject domain based on a target indicator condition, wherein the initial data subject domain includes a plurality of to-be-filled directories.

[0040] Specifically, the preset initial data subject domain includes multiple directories to be filled, including but not limited to patient basic database, clinical diagnosis and treatment, business operations, knowledge dictionary, etc. Different target indicator conditions correspond to different directories to be filled. There is a corresponding relationship between the target indicator conditions and the directories to be filled. Based on the corresponding relationship, the target directory to be filled corresponding to any target indicator condition can be determined. The specific content of the corresponding relationship is not specifically limited in the embodiment of the present application, and can be determined by relevant staff based on historical data and uploaded to the electronic device.

[0041] Step S140: Identify the data features contained in each effectively processed multi-source heterogeneous data, and determine the target to-be-filled directory corresponding to each effectively processed multi-source heterogeneous data based on each data feature, integrate the effectively processed multi-source heterogeneous data corresponding to each target to-be-filled directory, and obtain the to-be-filled data corresponding to each target to-be-filled directory.

[0042] Specifically, after determining the directory to be filled, it is necessary to divide the effectively processed multi-source heterogeneous data into the corresponding target directory to be filled to complete the data filling, wherein each effectively processed multi-source heterogeneous data can be feature identified, and then based on the feature identification result, multiple effectively processed multi-source heterogeneous data can be divided into the corresponding target directory to be filled. Different target directories to be filled have different directory features. By comparing the data features with the directory features, the effectively processed multi-source heterogeneous data corresponding to each target directory to be filled can be determined, and the effectively processed multi-source heterogeneous data corresponding to each filled directory can be integrated to obtain the data to be filled corresponding to each filled directory. The directory features corresponding to the target directory to be filled are consistent with the data features of the corresponding data to be filled. The specific data features and directory features are not specifically limited in the embodiments of the present application, as long as the allocation of effectively processed multi-source heterogeneous data can be completed.

[0043] Step S150: determining a target integration document corresponding to the target indicator condition according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory, and feeding back the target integration document.

[0044] Specifically, the filling work of the directories to be filled can be completed by filling the data to be filled into the corresponding directories to be filled. After all the directories to be filled are filled, all the directories to be filled and the corresponding contents to be filled that have completed the filling work can be integrated to obtain the target integrated document.

[0045] For the embodiments of the present application, multi-source heterogeneous data are screened through target indicator conditions, which facilitates the elimination of invalid data in the multi-source heterogeneous data. By facilitating the reduction of the number in the data processing process, the rate and accuracy of the data processing process are improved. Since the sources of multi-source heterogeneous data are wide, the types are diverse, and there are large differences in the units or magnitudes between different data, by preprocessing the effective multi-source heterogeneous data, the quality of the effective multi-source heterogeneous data is improved, data noise and data redundancy are reduced, and it is also convenient to compare and analyze the effective multi-source heterogeneous data on the same scale, so as to avoid data misunderstanding or misjudgment due to differences between the data. According to the target indicator conditions, the target directory to be filled is determined from the preset initial data subject domain, and the effectively processed multi-source heterogeneous data is accurately allocated to the corresponding directory based on the data characteristics, which not only simplifies the data integration process, but also facilitates improving the accuracy when determining the target integration document.

[0046] Furthermore, in order to improve the accuracy of the data filling process, a target integration document corresponding to the target indicator condition is determined according to each directory to be filled and the data to be filled corresponding to each directory to be filled, including: The docking method is identified, and the corresponding target docking technology is determined based on a preset docking mapping relationship and the docking method, wherein the preset docking mapping relationship is a corresponding relationship between the docking method and the target docking technology.

[0047] Specifically, the docking method includes but is not limited to active reading and push reading, wherein active reading is to obtain multi-source heterogeneous data directly from the hospital data storage system through electronic devices by relevant staff after obtaining relevant authorization from the hospital, while push reading is for relevant hospital staff to push multi-source heterogeneous data to electronic devices. The specific docking method is not specifically limited in the embodiments of this application. Different docking methods are applicable to different target docking technologies. The preset docking mapping relationship contains target docking technologies corresponding to different docking methods. The specific content is not specifically limited in the embodiments of this application, and can be determined by relevant staff based on historical experimental data and uploaded to the electronic device. Because in the active reading docking method, the electronic device needs to actively read multi-source heterogeneous data from the hospital data storage system or other data sources, and the ODBC direct query technology can accurately complete the data reading task based on its cross-platform, flexibility and high efficiency. Therefore, when the docking method is active reading, the target docking technology is generally determined as the ODBC direct query technology. In the push-read docking mode, hospital-related staff need to actively push multi-source heterogeneous data in the hospital data storage system or other data sources to the electronic device, and the API interface query technology can receive the multi-source heterogeneous data pushed by the medical party in real time or periodically, and can ensure the timeliness and effectiveness of the multi-source heterogeneous data. Therefore, when the docking mode is push-read, the target docking technology is generally determined to be the API interface query technology.

[0048] Semantic recognition is performed on each effectively processed multi-source heterogeneous data, and based on the semantic recognition results, it is determined whether the effectively processed multi-source heterogeneous data contains associated heterogeneous data. When associated heterogeneous data exists, an associated index is established between the corresponding effective multi-source heterogeneous data, and the semantic recognition results corresponding to the associated heterogeneous data contain the same semantic entity segmentations.

[0049] Specifically, natural language processing technology can be used to identify the entities contained in each effectively processed multi-source heterogeneous data, to achieve semantic recognition of each effectively processed multi-source heterogeneous data, and then by comparing the entities between different effectively processed multi-source heterogeneous data, it is determined whether there are consistent entities between the effective multi-source heterogeneous data, wherein, if the entity similarity between the entities corresponding to two effectively processed multi-source heterogeneous data is not less than the preset similarity, then the corresponding effectively processed multi-source heterogeneous data can be determined to be associated heterogeneous data, wherein the preset similarity can be 85% or 95%, and the specific value is not specifically limited in the embodiment of this application, and can be set by relevant staff according to actual needs. In addition to using entity matching to determine whether there is associated heterogeneous data in the effectively processed multi-source heterogeneous data, cluster analysis, association rule mining and other methods can also be used for determination. The specific determination method is not specifically limited in the embodiment of this application, as long as it can determine whether multiple effectively processed multi-source heterogeneous data contain associated heterogeneous data.

[0050] The associated index can be a one-to-one mapping relationship, or it can be a many-to-many mapping relationship, that is, the associated heterogeneous data may be two effectively processed multi-source heterogeneous data containing the same semantic entity segmentation, or it can be multiple effectively processed multi-source heterogeneous data containing the same semantic entity segmentation. The number of effectively processed multi-source heterogeneous data corresponding to the associated heterogeneous data is not specifically limited in the embodiments of this application, and can be set by relevant staff. In order to achieve fast retrieval, the associated index can be designed as an index table or a graph structure, where the index table uses the semantic entity segmentation as the key and the associated heterogeneous data containing the semantic entity segmentation as the value; the graph structure uses the associated heterogeneous data as the nodes and the semantic entity segmentations between them as the edges. The specific form of the associated index is not specifically limited in the embodiments of this application, as long as the association relationship between the associated heterogeneous data can be established.

[0051] Based on the target docking technology and the associated index, each data to be filled is added to the corresponding directory to be filled, and the target integration document corresponding to the target indicator condition is obtained.

[0052] Specifically, in the process of effectively processing multi-source heterogeneous data corresponding to the data to be filled into the corresponding directory to be filled, it is necessary to adopt the determined target docking technology. Based on the preset docking mapping relationship, it is convenient to accurately determine the docking technology corresponding to the docking method. By improving the adaptability between the docking method and the docking technology, it is convenient to improve the accuracy of the docking process. At the same time, it is necessary to establish the connection between the related heterogeneous data during the filling process, so that relevant personnel can perform related queries and comparisons when accessing the target integrated documents.

[0053] Furthermore, in order to ensure the integrity of the data in the target integrated document, after the target integrated document is generated, the following steps are also included: Identify whether there is a preset missing identifier in the target integrated document, and determine the field containing the preset missing identifier as a missing field; determine whether the missing field contains a missing associated index; if so, determine the substitute data from the corresponding associated heterogeneous data based on the missing associated index, and update the missing field based on the substitute data to update the target integrated document; if not, generate prompt information based on the missing field, and superimpose the prompt information on the target integrated document.

[0054] Specifically, feature recognition can be used to identify whether the target integrated document contains a preset missing identifier. When the target integrated document contains a preset missing identifier, it can indicate that there are missing fields or blank fields in the target integrated document. The preset missing identifier can be a special character or string, such as N / A, NULL, #MISSING#, etc., or a placeholder, code or enumeration value, etc. The preset missing identifier is not specifically limited in the embodiments of the present application.

[0055] The field containing a preset missing identifier in the target integrated document is determined as a missing field. The missing field may or may not contain a missing associated index. When the missing field does not contain a missing associated index, it indicates that there is no associated heterogeneous data corresponding to the effective processing of multi-source heterogeneous data corresponding to the missing field. At this time, prompt information can be directly generated according to the missing field, and the prompt information can be fed back to remind relevant staff to discover the missing field in time. When the prompt information is fed back, it can be directly fed back to the corresponding display interface of the electronic device, or the prompt information can be superimposed on the target integrated document.

[0056] When the missing field contains a missing associated index, it indicates that there is associated heterogeneous data corresponding to the missing field for effectively processing multi-source heterogeneous data. At this time, the associated heterogeneous data corresponding to the missing field can be determined from the target integrated document through the pre-established associated index, and the missing field can be completed based on the associated heterogeneous data. For example, the missing field is gender, and the associated heterogeneous data corresponding to the missing field is the ID card number. Since the 17th digit in the ID card number represents gender, odd numbers represent males, and even numbers represent females, the substitute data corresponding to the missing field can be determined through the associated heterogeneous data, and the missing field is updated based on the substitute data to achieve the update of the target integrated document.

[0057] By detecting whether the target integration document contains missing information after it is generated, it is convenient to timely discover and locate missing fields, and determine substitute data from associated heterogeneous data based on the missing associated index corresponding to the actual field, so as to improve the speed of completing missing fields and ensure that the data in the target integration document is as complete as possible, reducing analysis and decision-making errors caused by missing data. For missing fields that cannot be filled automatically, prompt information is generated and superimposed on the document to prompt relevant staff to check or manually complete the missing content.

[0058] In order to improve the accuracy of determining the logical value, the method provided in the embodiment of the present application further includes: Identify whether the target integrated document contains a logical directory, which is a directory to be filled that contains a preset logical identifier; if it contains a logical directory, obtain the logical formula corresponding to the preset logical identifier and determine the logical field corresponding to the preset logical identifier from the data to be filled corresponding to the logical directory; determine the logical value corresponding to the logical directory based on the logical formula and the logical field, and write the logical value into the corresponding position of the logical directory in the target integrated document.

[0059] Specifically, the logical directory is a directory that needs to be logically operated. For example, the logical directory can be the approved number of beds. The corresponding filling data under this logical directory can be the bed configuration data and bed adjustment file data of each department in the hospital. After these filling data are filled into the logical directory, logical operations need to be performed according to the filling content to determine the approved number of beds. The logical directory can also be the actual number of open beds, bed utilization rate, etc. Different target indicator conditions correspond to different logical directories. The logical directory contained in the target integration document can be determined by feature recognition.

[0060] Different preset logical identifiers correspond to different logical formulas. For example, the preset logical identifier corresponding to the approved number of beds is identifier a, and the logical formula corresponding to identifier a is used to calculate the approved number of beds according to the logical field in the corresponding fill-in data; the preset logical identifier corresponding to the bed occupancy rate is identifier b, and the logical formula corresponding to identifier b is used to calculate the bed occupancy rate according to the logical field in the corresponding fill-in data. Among them, the logical field is a field that needs to participate in the logical operation. After determining the corresponding logical field according to the corresponding logical identifier, the logical field is brought into the corresponding logical formula to realize the calculation of the logical value. The logical formula and logical field corresponding to the logical identifier can be determined by relevant staff based on historical experimental data and uploaded to the electronic device. The specific content is not specifically limited in the embodiment of the present application. The determined logical value can be directly filled into the corresponding position in the target integrated document. When the logical directory is the approved number of beds and the calculated logical value is 700, 700 can be directly filled into the approved number of beds in the target integrated document, such as Figure 2 shown.

[0061] Furthermore, the method provided in the embodiment of the present application also includes: When a detail access instruction is detected, the detail content corresponding to the detail access instruction is identified; when the detail content contains multiple items, the detail display method can be determined based on the detail access instruction, and the target detail content can be determined based on the detail display method; the detail fields corresponding to the target detail content and the detail date corresponding to each detail field are identified, all detail fields are sorted based on the detail date to obtain a detail list, and the detail list is fed back; it is identified whether the detail list contains a preset detail missing indicator, and if so, detail prompt information is generated based on the detail missing indicator, and the detail prompt information is superimposed on the detail list.

[0062] Specifically, when it is detected that the relevant staff member clicks or triggers the access area corresponding to the logical value, it can be determined that there is a detailed access instruction. At this time, the logical field corresponding to the logical value and the fill-in data corresponding to the logical field can be directly fed back. The logical field and the fill-in data corresponding to the logical field constitute the detailed content. By only displaying the logical value in the target integrated document, the detailed content corresponding to the logical value is displayed only when the detailed access instruction is detected, that is, when the detailed access instruction is not detected, the detailed content corresponding to the logical value is folded. In this way, the readability and clarity of the target integrated document can be improved, so that the relevant visitors can quickly complete the browsing and grab the key content. In the scenario where there is no need to view the detailed detailed content, hiding the detailed content corresponding to the logical value or folding the detailed content can reduce the space occupied by the target integrated document. At the same time, the relevant visitors do not need to spend time reading or browsing irrelevant detailed information, thereby facilitating improving the access efficiency of the relevant visitors.

[0063] Since the logical values ​​corresponding to different logical operation dates may be different, for example, the logical value corresponding to the number of approved beds when performing logical operations in June is 700, and the logical value corresponding to the number of approved beds when performing logical operations in July is 600. Therefore, there may be multiple logical values ​​corresponding to the logical directory, and there may also be multiple detailed contents corresponding to the corresponding logical directory. At this time, the detailed display method can be determined according to the detailed access instruction, and the target detailed content can be determined based on the detailed display method, wherein the detailed display method can include taking the maximum value, taking the minimum value, summing, etc. The specific detailed display method is not specifically limited in the embodiment of the present application, and the relevant staff can determine the detailed display method corresponding to each logical directory based on historical experimental data and upload it to the electronic device.

[0064] After determining the detailed display method, the target detailed content can be determined from multiple detailed contents based on the detailed display method. At this time, all the target detailed contents can be directly fed back, and the target detailed contents can also be further analyzed and sorted before feedback. Among them, the detailed fields contained in the target detailed content and the detailed date corresponding to each detailed field can be identified according to the feature recognition algorithm. Each detailed field in the target detailed content is sorted based on the detailed date to obtain a detailed list, and finally the detailed list is fed back. The detailed date of each detailed field in the detailed list can be arranged in sequence or in reverse order. The specific arrangement order is not specifically limited in the embodiment of this application. After determining the detailed list, it is also possible to analyze whether the detailed list contains missing content. The specific method can refer to the above-mentioned content of analyzing whether the target integration document contains missing fields. The specific process is not repeated here.

[0065] By automatically identifying detail access instructions and determining the corresponding detail content, it is convenient to obtain the required information more quickly. When there are multiple detail contents, by identifying the detail display method from the detail access instruction, it is convenient to quickly select the content that needs to be accessed or viewed from multiple detail contents. In addition, when it is necessary to further view the detail content, multiple detail fields can be sorted according to the detail date corresponding to each detail field, and feedback can be provided in the form of a detail list, so as to improve the standardization of the display of the detail fields. It is also possible to promptly discover the preset detail missing marks that may exist in the detail list through defect identification, and promptly complete the missing content, so as to improve data integrity.

[0066] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 300 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 300 does not constitute a limitation on the embodiments of the present application.

[0067] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0068] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The fact that only one line is used in the diagram does not mean that there is only one bus or only one type of bus.

[0069] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0070] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0071] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0072] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0073] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method in any of the above embodiments is implemented.

[0074] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0075] The above is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A multi-source heterogeneous data integration method, characterized in that: include: Acquire multi-source heterogeneous data and target indicator conditions, and screen the multi-source heterogeneous data based on the target indicator conditions to obtain at least one valid multi-source heterogeneous data, where the valid multi-source heterogeneous data is the multi-source heterogeneous data that meets the target indicator conditions; Identify a target data volume corresponding to the at least one valid multi-source heterogeneous data, and when the target data volume is not higher than a preset data volume, perform data preprocessing on the at least one valid multi-source heterogeneous data to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data, wherein the data preprocessing includes but is not limited to data normalization processing, deduplication processing, and noise reduction processing; Determine at least one target to-be-filled directory from a preset initial data subject domain based on the target indicator condition, wherein the initial data subject domain includes a plurality of to-be-filled directories; Identify the data features contained in each effectively processed multi-source heterogeneous data, and determine the target to-be-filled directory corresponding to each effectively processed multi-source heterogeneous data based on each data feature, integrate the effectively processed multi-source heterogeneous data corresponding to each target to-be-filled directory, and obtain the to-be-filled data corresponding to each target to-be-filled directory; The target integration document corresponding to the target indicator condition is determined according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory, and the target integration document is fed back.

2. A multi-source heterogeneous data integration method according to claim 1, characterized in that: Also includes: When the target data volume is higher than a preset data volume, determining a corresponding target buffer area based on the target data volume; The at least one valid multi-source heterogeneous data is written into the target buffer, and data preprocessing is performed on the at least one valid multi-source heterogeneous data written into the target buffer to obtain valid processed multi-source heterogeneous data corresponding to each valid multi-source heterogeneous data.

3. A multi-source heterogeneous data integration method according to claim 1, characterized in that: The step of determining the target integration document corresponding to the target indicator condition according to each to-be-filled directory and the to-be-filled data corresponding to each to-be-filled directory includes: Identify the docking mode, and determine the corresponding target docking technology based on a preset docking mapping relationship and the docking mode, wherein the preset docking mapping relationship is a correspondence relationship between the docking mode and the target docking technology; Perform semantic recognition on each effectively processed multi-source heterogeneous data, and determine whether the effectively processed multi-source heterogeneous data contains associated heterogeneous data based on the semantic recognition result. When associated heterogeneous data exists, establish an associated index between the corresponding effectively processed multi-source heterogeneous data, and the semantic recognition results corresponding to the associated heterogeneous data contain the same semantic entity segmentation; Based on the target docking technology and the associated index, each to-be-filled data is added to the corresponding to-be-filled directory to obtain a target integration document corresponding to the target indicator condition.

4. A multi-source heterogeneous data integration method according to claim 3, characterized in that: After generating the target integration document, it also includes: Identify whether there is a preset missing identifier in the target integrated document, and determine the field containing the preset missing identifier as a missing field; Determine whether the missing field contains a missing associated index; If so, determining replacement data from the corresponding associated heterogeneous data based on the missing associated index, and updating the missing field based on the replacement data to update the target integrated document; If not, a prompt message is generated based on the missing field, and the prompt message is superimposed on the target integrated document.

5. A multi-source heterogeneous data integration method according to claim 1, characterized in that: Also includes: Identify whether the target integrated document contains a logical directory, where the logical directory is a directory to be filled that contains a preset logical identifier; If the logic directory is included, obtaining the logic formula corresponding to the preset logic identifier and determining the logic field corresponding to the preset logic identifier from the to-be-filled data corresponding to the logic directory; A logic value corresponding to the logic directory is determined based on the logic formula and the logic field, and the logic value is written into a corresponding position of the logic directory in the target integrated document.

6. A multi-source heterogeneous data integration method according to claim 5, characterized in that: Also includes: When a detail access instruction is detected, identifying the detail content corresponding to the detail access instruction; When the detailed content includes multiple items, a detailed display mode may be determined based on the detailed access instruction, and a target detailed content may be determined based on the detailed display mode; Identify the detail fields corresponding to the target detail content and the detail date corresponding to each detail field, sort all detail fields based on the detail date to obtain a detail list, and feed back the detail list; Identify whether the detail list contains a preset detail missing identifier. If so, generate detail prompt information based on the detail missing identifier and superimpose the detail prompt information into the detail list.

7. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute a multi-source heterogeneous data integration method according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that: include: A computer program is stored which can be loaded by a processor and execute a multi-source heterogeneous data integration method as described in any one of claims 1 to 6.

9. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of a multi-source heterogeneous data integration method according to any one of claims 1 to 6.

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