Structured data generation method and device, storage medium and electronic equipment

Abstract

The present disclosure relates to the technical field of data processing, in particular to a structured data generation method and device, a storage medium and an electronic device. The method comprises: obtaining preliminary structured data to be processed; obtaining combination logic, and calculating and reorganizing the preliminary structured data to be processed according to the combination logic to obtain final structured data. The technical scheme of the present disclosure can automatically calculate and reorganize the preliminary structured data to be processed through the combination logic, avoids the process of statistically analyzing the preliminary structured data to be processed by manual operation, and further improves the efficiency of data processing and reduces the possibility of errors.

Description

[0001] This application is a divisional application of Chinese patent application filed on August 12, 2019, with application number 201910740189.0 and title "Structured Data Generation Method and Apparatus, Storage Medium and Electronic Equipment". Technical Field

[0002] This disclosure relates to the field of data processing technology, and more specifically, to a method and apparatus for generating structured data, a storage medium, and an electronic device. Background Technology

[0003] With the development of information technology in fields such as the Internet, the Internet of Things, and mobile computing, more and more different types of data are being produced in large quantities. However, this mass-produced data often needs further processing before it can be transformed into data that users can directly use.

[0004] Currently, in order to transform the large amounts of data produced into data that users can directly use, it is often necessary to manually perform statistical analysis on the structured information from various data sources extracted by the machine to obtain directly usable data. For example, in the medical field, after the machine extracts structured data from sources such as a patient's medical history, examination reports, and pathology reports, manual analysis and statistical analysis of the structured data are required to obtain the final examination results for the patient that are directly usable by medical personnel.

[0005] However, in the above methods, since the machine can only extract structured data from various sources, the process of converting the structured data into data that is directly usable by users still needs to be done manually, which leads to low data processing efficiency and is prone to errors.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this disclosure is to provide a method, apparatus, storage medium, and electronic device for generating structured data, thereby overcoming, to at least some extent, the problems of low data processing efficiency and susceptibility to errors caused by data conversion relying entirely on manual labor.

[0008] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0009] According to a first aspect of this disclosure, a method for generating structured data is provided, comprising:

[0010] Obtain preliminary structured data to be processed; obtain combinational logic, and perform calculations and recombination on the preliminary structured data to be processed according to the combinational logic to obtain final structured data.

[0011] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the preliminary structured data to be processed includes at least one pair of key-value pairs, wherein the key-value pairs include corresponding key data and value data;

[0012] The step of obtaining combinational logic and calculating and reorganizing the preliminary structured data to be processed according to the combinational logic to obtain the final structured data includes:

[0013] Group the data in the preliminary structured data to be processed according to the key data;

[0014] Obtain the combinational logic corresponding to each group, and calculate all the value data in the group according to the combinational logic to obtain the final value data;

[0015] The key data corresponding to each group and the corresponding final value data are combined to form the final key-value pair data to obtain the final structured data.

[0016] In an exemplary embodiment of this disclosure, based on the foregoing scheme, obtaining the combinational logic corresponding to each group includes:

[0017] Read the data type of the value data in each of the groups;

[0018] Invoke the corresponding preset combination logic according to the data type;

[0019] The preset combinational logic is set as the combinational logic corresponding to each group.

[0020] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the data types include Boolean, list, and date types.

[0021] In one exemplary embodiment of this disclosure, based on the foregoing scheme, before obtaining the combinational logic, the method further includes:

[0022] In response to user input logic data, combinational logic is configured based on the logic data.

[0023] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the method further includes:

[0024] Structure all text data corresponding to the target object to obtain preliminary structured data to be processed.

[0025] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the step of structuring all text data corresponding to the target object to obtain preliminary structured data to be processed includes:

[0026] Retrieve all text data corresponding to the target object;

[0027] The corresponding preset strategy is invoked based on the source of the text data;

[0028] The text data is structured according to a preset strategy to obtain preliminary structured data to be processed.

[0029] According to a second aspect of this disclosure, a structured data generation apparatus is provided, comprising:

[0030] The data acquisition module is used to acquire preliminary structured data to be processed; the calculation and recombination module is used to acquire combinational logic and perform calculation and recombination on the preliminary structured data to be processed according to the combinational logic to obtain final structured data.

[0031] In one exemplary embodiment of this disclosure, based on the foregoing solution, the apparatus further includes:

[0032] The logic configuration module is used to configure combinational logic based on user-input logic data in response to the logic data.

[0033] In one exemplary embodiment of this disclosure, based on the foregoing solution, the apparatus further includes:

[0034] The data processing module is used to structure all text data corresponding to the target object to obtain preliminary structured data to be processed.

[0035] According to a third aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the structured data generation method as described in the first aspect of the above embodiments.

[0036] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising:

[0037] Processor; and

[0038] A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the structured data generation method as described in the first aspect of the above embodiments.

[0039] The technical solutions provided in this disclosure may have the following beneficial effects:

[0040] One embodiment of this disclosure provides a structured data generation method that, by performing calculations and reorganizations on preliminary structured data to be processed according to combinational logic, can obtain the corresponding final structured data. In this process, combinational logic automatically performs calculations and reorganizations on the preliminary structured data to be processed, avoiding the need for manual statistical analysis of the preliminary structured data, thereby improving data processing efficiency and reducing the possibility of errors.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0042] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:

[0043] Figure 1 This schematically illustrates a flowchart of a structured data generation method according to an exemplary embodiment of the present disclosure;

[0044] Figure 2 The flowchart illustrates a method for obtaining combinational logic and recombining the preliminary structured data to be processed according to the combinational logic to obtain final structured data in an exemplary embodiment of the present disclosure.

[0045] Figure 3 A flowchart illustrating a method for obtaining combinational logic corresponding to each group in an exemplary embodiment of this disclosure is shown in the diagram.

[0046] Figure 4 The flowchart illustrates an exemplary embodiment of the present disclosure of a method for structuring all text data corresponding to a target object to obtain preliminary structured data to be processed.

[0047] Figure 5 This schematic diagram illustrates the composition of a structured data generation apparatus according to an exemplary embodiment of the present disclosure;

[0048] Figure 6 This schematic diagram illustrates the composition of another structured data generation apparatus in an exemplary embodiment of the present disclosure;

[0049] Figure 7 This schematic diagram illustrates the composition of another structured data generation apparatus in an exemplary embodiment of the present disclosure;

[0050] Figure 8This schematically illustrates a structural diagram of a computer system suitable for implementing exemplary embodiments of the present disclosure;

[0051] Figure 9 A schematic diagram of a computer-readable storage medium according to some embodiments of the present disclosure is shown. Detailed Implementation

[0052] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0053] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0054] In this exemplary embodiment, a structured data generation method is first provided, which can be applied to the data transformation process. The executing entity of this structured data generation method can be a terminal device capable of data processing, such as a mobile phone or computer. (Refer to...) Figure 1 As shown, the above-described structured data generation method may include the following steps:

[0055] S110, Obtain preliminary structured data to be processed;

[0056] S120, obtain combinational logic, and perform calculations and reorganization on the preliminary structured data to be processed according to the combinational logic to obtain the final structured data.

[0057] According to the structured data generation method provided in this exemplary embodiment, the corresponding final structured data can be obtained by calculating and reorganizing the preliminary structured data to be processed according to combinational logic. In this process, the combinational logic can automatically calculate and reorganize the preliminary structured data to be processed, avoiding the need for manual statistical analysis of the preliminary structured data to be processed, thereby improving the efficiency of data processing and reducing the possibility of errors.

[0058] The following will describe in more detail the various steps of the structured data generation method in this exemplary embodiment with reference to the accompanying drawings and embodiments.

[0059] Step S110: Obtain the preliminary structured data to be processed.

[0060] In one example embodiment of this disclosure, the preliminary structured data to be processed includes preliminary structured data corresponding to at least one text data, or it may include preliminary structured data corresponding to multiple text data. The preliminary structured data to be processed may be paired data or data in other forms, and this disclosure does not impose any special restrictions on this.

[0061] Step S120: Obtain combinational logic, and perform calculation and recombination on the preliminary structured data to be processed according to the combinational logic to obtain the final structured data.

[0062] In one example embodiment of this disclosure, prior to obtaining the combinational logic, the method further includes: configuring the combinational logic based on the logic data in response to user input logic data.

[0063] In one example embodiment of this disclosure, a user can customize logical data according to the specific requirements of the preliminary structured data to be processed, and configure the logical data as combinational logic. This allows the preliminary structured data to be processed to be calculated and reorganized according to the user's requirements to obtain the final structured data needed by the user. By allowing the user to customize the combinational logic, the preliminary structured data to be processed can be calculated and reorganized according to the user's needs, thereby obtaining final structured data that is more suitable for the user's requirements.

[0064] In one example embodiment of this disclosure, the preliminary structured data to be processed may include at least one key-value pair. The key-value pair includes corresponding key data and value data. For example, the preliminary structured data to be processed in the medical field may include the text data corresponding to the text data of a bone scan report and a pathology report, specifically including "Bone Scan - Metastasis: Yes" and "Pathology - Metastasis: Yes", where "Bone Scan - Metastasis: Yes" and "Pathology - Metastasis: Yes" are key data, and "Yes" is value data; as another example, the preliminary structured data to be processed in the credit field may be "xx Bank - Timely Repayment: Yes", where "xx Bank - Timely Repayment: Yes" is key data, and "Yes" is value data.

[0065] In one example embodiment of this disclosure, when the preliminary structured data to be processed specifically includes at least one pair of key-value pairs, the step of obtaining combinational logic and calculating and reorganizing the preliminary structured data to be processed according to the combinational logic to obtain the final structured data is described below. Figure 2 As shown, the steps S210 to S230 may be included:

[0066] Step S210: Group the data according to the key values ​​in the preliminary structured data to be processed based on the key data.

[0067] In one example embodiment of this disclosure, key-value pairs can be grouped according to all key data in the preliminary structured data to be processed, grouping key-value pairs with the same structural field into the same group to facilitate further computational processing. For example, when the preliminary structured data to be processed includes key-value pairs "Bone Scan - Metastasis: Yes" from a bone scan report, and key-value pairs "Pathology - Metastasis: Yes" and "Pathology - Metastasis Site: Liver" from a pathology report, the two key-value pairs "Bone Scan - Metastasis: Yes" and "Pathology - Metastasis: Yes" can be grouped into one group based on the key data "Metastasis," while "Pathology - Metastasis Site: Liver" can be grouped into another group. By classifying key-value pairs according to key data, key-value pairs with the same structural field can be grouped into the same group, thereby facilitating the separate processing of key-value pairs in different groups.

[0068] Step S220: Obtain the combination logic corresponding to each group, and calculate all the value data in the group according to the combination logic to obtain the final value data.

[0069] In one example embodiment of this disclosure, the calculation basis for the median data in different groups may be different, therefore it is necessary to obtain the combinational logic corresponding to each group separately. The corresponding combinational logic can be obtained according to the data type of the key-value pair data in each group. Specifically, refer to... Figure 3 As shown, the steps S310 to S330 may be included:

[0070] Step S310: Read the data type of the value data in each group.

[0071] Step S320: Invoke the corresponding preset combination logic according to the data type;

[0072] Step S330: Set the preset combination logic to the combination logic corresponding to each group.

[0073] In one example embodiment of this disclosure, a corresponding preset combination logic can be invoked based on the data type of the value data in the key-value pairs within a group, and the preset combination logic can be set as the combination logic corresponding to that group. The data type can include Boolean, list, and date types, representing that the value data in the key-value pairs within the current group is Boolean, list, or date, respectively. By setting corresponding combination logic based on the data type of the value data in different groups, the selected combination logic can be more closely matched to the data type of the value data, resulting in more accurate and directly usable final value data, avoiding the mismatch problem caused by selecting the same combination logic for all key-value pairs.

[0074] In one example embodiment of this disclosure, the preset combination logic varies depending on the data type of the value data. For example, if the key-value pair data in the group is "bone scan - metastasis: yes" and "pathology - metastasis: yes", since "yes" is Boolean data, the preset combination logic can be set to "when any one of the multiple Boolean data is 'yes', the final value data is 'yes'". Similarly, when the value data is a list, the preset combination logic can be set to "take the union of multiple value data lists as the final value data". Furthermore, when the value data is a date, the preset combination logic can be set to "take the date closest to a specified date as the final value data". Because the types of value data and the requirements for the final value data differ, the preset combination logic typically includes some commonly used and general combination logic, which can be determined according to the type of value data and the requirements for the final value data. This disclosure does not impose any special restrictions on this.

[0075] Step S230: Combine the key data and the corresponding final value data of each group into final key-value pair data to obtain the final structured data.

[0076] In one example embodiment of this disclosure, the key data and final value data corresponding to each group are combined to obtain the final key-value pair data. The final key-value pair data corresponding to all groups constitutes the final structured data. For example, if the key data is "Transfer or not" and the final value data is "Yes", then the final key-value pair data is "Transfer or not: Yes". By calculating the final value data within the group, the process of integrating the value data corresponding to the same key data into a single final value data is realized. Furthermore, by combining the key data and the final value data into the final key-value pair data, the data needed by the user can be directly provided, avoiding the need for manual querying and analysis, thus improving data processing efficiency.

[0077] In one exemplary embodiment of this disclosure, to obtain preliminary structured data to be processed, the method further includes: structuring all text data corresponding to the target object to obtain preliminary structured data to be processed. For example, in the medical field, in order to understand the examination results of a target patient, a user can structure all text data corresponding to the target object to obtain preliminary structured data to be processed, and then further process it to obtain the final structured data.

[0078] In one example embodiment of this disclosure, the step of structuring all text data corresponding to the target object to obtain preliminary structured data to be processed is referred to... Figure 4 As shown, the steps S410 to S430 are as follows:

[0079] Step S410: Obtain all text data corresponding to the target object.

[0080] In one example embodiment of this disclosure, the target object can be set according to the user's needs. For example, in the medical field, in order to understand the medical information of patient A, a user needs to obtain all the text data corresponding to patient A, which may include examination reports corresponding to various medical examinations.

[0081] Step S420: Invoke the corresponding preset strategy according to the source of the text data.

[0082] In one example embodiment of this disclosure, since text data from different sources uses different natural language habits and text structures, the strategies used to extract structured data from different text data are also different. Correspondingly, in order to structure the text data according to the natural language habits and text structures used by each text data, it is necessary to pre-set a preset strategy, and then call the corresponding preset strategy according to the source of the text data.

[0083] Step S430: The text data is structured according to a preset strategy to obtain preliminary structured data to be processed.

[0084] In one example embodiment of this disclosure, text data is structured according to a preset strategy determined by the data source of the text data to obtain preliminary structured data to be processed. For example, the text data obtained from a bone scan report is "After esophagectomy, radioactive concentration was observed at the left sacral joint, suggesting metastasis." By structuring this data, preliminary structured data to be processed can be obtained as "Bone scan - metastasis: yes" and "Bone scan - metastasis site: bone".

[0085] The following uses the generation of structured data for patient A in the medical field as an example to illustrate the implementation details of the technical solution of this disclosure embodiment:

[0086] 1. Text data corresponding to all of Patient A's examination reports

[0087] The corresponding text data in the pathology report is: "Esophageal resection specimen, poorly differentiated squamous cell carcinoma of the esophagus with ulceration; additional liver tissue tested showed cancer cells, consistent with metastasis."

[0088] The text data corresponding to the bone scan report is: "Post-esophagectomy for esophageal cancer, radioactive concentration was observed at the left sacral joint, suggesting metastasis."

[0089] The corresponding text data in the head CT scan report is: "No signs of metastasis or recurrence were found after esophagectomy."

[0090] 2. Structure all text data corresponding to patient A to obtain preliminary structured data to be processed.

[0091] The structured data obtained by structuring the text data corresponding to the pathology report is as follows: Pathology - whether it has metastasized: Yes; Pathology - metastasis site: Liver.

[0092] The structured data obtained by structuring the text data corresponding to the bone scan report is as follows: Bone scan - whether metastasis occurs: Yes; Bone scan - metastasis site: Bone.

[0093] The structured data obtained by structuring the text data corresponding to the head CT examination report is as follows: Head CT - whether metastasis occurs: No; Head CT - metastasis site: NA.

[0094] 3. Group the data based on the key values ​​in all the preliminary structured data to be processed.

[0095] Key data includes key-value pairs indicating whether metastasis has occurred, such as: Pathology - Metastasis: Yes; Bone Scan - Metastasis: Yes; Head CT - Metastasis: No.

[0096] Key data includes key-value pairs for "metastatic sites": Pathology - Metastatic site: Liver; Bone scan - Metastatic site: Bone; Head CT - Metastatic site: None.

[0097] 4. Obtain the combinational logic and calculate the final value data based on the combinational logic.

[0098] The combined logic is invoked based on the data type of the value data in the key-value pairs within the group as follows:

[0099] The combinational logic corresponding to the key data grouping "whether to transfer" is as follows: for multiple Boolean data, if any one of them is "yes", then the final result is "yes".

[0100] The combinational logic corresponding to the grouping of key data including "transfer location" is as follows: for multiple list-type data, take the union of multiple lists as the final result.

[0101] The final value calculated using combinational logic is as follows:

[0102] The key data includes the grouping for "Whether to transfer", and the corresponding final value data is "Yes".

[0103] The key data includes the final value data corresponding to the grouping of "metastatic site": "liver, bone".

[0104] 5. Combine the key data and the corresponding final value data of each group into the final key-value pair data to obtain the final structured data.

[0105] The final key-value pair data is: "Transfer: Yes" and "Transfer site: Liver, bone".

[0106] The final structured data is as follows: whether it has metastasized: yes; metastasis sites: liver, bone.

[0107] After converting the text data corresponding to Patient A's examination report into preliminary structured data, the key-value pairs are grouped according to the key data in the preliminary structured data. The final value data is then calculated from the value data within each group. Finally, the key data corresponding to each group and the final value data are combined to obtain the final key-value pairs. This method of generating structured data avoids the process of manually performing statistical analysis on the retrieved text data to obtain the final key-value pairs, improving data processing efficiency and reducing the possibility of human error.

[0108] It should be noted that the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0109] Furthermore, in an exemplary embodiment of this disclosure, a structured data generation apparatus is also provided. (Refer to...) Figure 5 As shown, the structured data generation device 500 includes: a data acquisition module 510 and a calculation and reconstruction module 520.

[0110] The data acquisition module 510 can be used to acquire preliminary structured data to be processed.

[0111] The computational recombination module 520 can be used to obtain combinational logic and perform computational recombination on the preliminary structured data to be processed according to the combinational logic to obtain the final structured data.

[0112] In an exemplary embodiment of this disclosure, based on the foregoing scheme, the calculation and reorganization module 520 can be used to group the key-value pairs in the preliminary structured data to be processed according to the key data; obtain the combination logic corresponding to each group, and calculate all the value data in the group according to the combination logic to obtain the final value data; combine the key data corresponding to each group and the corresponding final value data into the final key-value pairs to obtain the final structured data.

[0113] In an exemplary embodiment of this disclosure, based on the foregoing scheme, the calculation and reorganization module 520 can be used to read the data type of the value data in each of the groups; and call the corresponding preset combination logic according to the data type to set the combination logic corresponding to each of the groups respectively.

[0114] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the data types include Boolean, list, and date types.

[0115] In one exemplary embodiment of this disclosure, based on the foregoing scheme, the calculation and reorganization module 520 can also be used to acquire logical data input by the user and set the logical data as combinational logic corresponding to the group.

[0116] In one exemplary embodiment of this disclosure, based on the foregoing scheme, referring to Figure 6 As shown, the structured data generation device 500 further includes a logic configuration module 530, which can be used to configure combinational logic based on the user input logic data in response to the user input logic data.

[0117] In one exemplary embodiment of this disclosure, based on the foregoing scheme, referring to Figure 7 As shown, the structured data generation device 500 further includes a data processing module 540, which can be used to structure all text data corresponding to the target object to obtain preliminary structured data to be processed.

[0118] In an exemplary embodiment of this disclosure, based on the foregoing scheme, the data processing module 540 can be used to acquire all text data corresponding to the target object; call the corresponding preset strategy according to the source of the text data; and perform structuring on the text data according to the preset strategy to obtain preliminary structured data to be processed.

[0119] Since the functional modules of the structured data generation apparatus in the example embodiments of this disclosure correspond to the steps of the example embodiments of the structured data generation method described above, for details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the structured data generation method described above.

[0120] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0121] Furthermore, in an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described structured data generation method is also provided.

[0122] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be embodied in the following forms: a completely hardware embodiment, a completely software embodiment (including firmware, microcode, etc.), or an embodiment combining hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0123] The following reference Figure 8 To describe an electronic device 800 according to such an embodiment of the present disclosure. Figure 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0124] like Figure 8 As shown, the electronic device 800 is presented in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, a bus 830 connecting different system components (including storage unit 820 and processing unit 810), and a display unit 840.

[0125] The storage unit stores program code that can be executed by the processing unit 810, causing the processing unit 810 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 810 can perform actions such as... Figure 1 The steps shown are: S110: Obtain preliminary structured data to be processed; S120: Obtain combinational logic, and calculate and reorganize the preliminary structured data to be processed according to the combinational logic to obtain final structured data.

[0126] For example, the aforementioned electronic device can achieve the following: Figures 2 to 4 The steps shown.

[0127] Storage unit 820 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 821 and / or cache memory 822, and may further include a read-only memory (ROM) 823.

[0128] The storage unit 820 may also include a program / utility 824 having a set (at least one) of program modules 825, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0129] Bus 830 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0130] Electronic device 800 can also communicate with one or more external devices 870 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 800, and / or with any device that enables electronic device 800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 850. Furthermore, electronic device 800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0131] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0132] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of this disclosure may also be implemented as a program product including program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0133] Reference Figure 9 This document describes a program product 900 for implementing the methods described above according to embodiments of the present disclosure. This product may be a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of this disclosure is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0134] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0135] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0136] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0137] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0138] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0139] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0140] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for generating structured data, characterized in that, include: Obtain preliminary structured data to be processed; The preliminary structured data to be processed includes at least one key-value pair; the key-value pair includes corresponding key data and value data. Grouping key-value pairs in the preliminary structured data to be processed according to the key data includes: grouping key-value pairs with similar structured fields into the same group; In response to user input logic data, combinational logic is configured based on the logic data, wherein the user customizes the logic data according to the specific requirements of the preliminary structured data to be processed, and the logic data is configured as combinational logic; Obtain the combinational logic corresponding to each group, and calculate all the value data in the group according to the combinational logic to obtain the final value data; The key data corresponding to each group and the corresponding final value data are combined into final key-value pair data to obtain the final structured data; The step of obtaining the combination logic corresponding to each group includes: reading the data type of the value data in each group; calling the corresponding preset combination logic according to the data type; and setting the preset combination logic as the combination logic corresponding to each group.

2. The method according to claim 1, characterized in that, The data types include Boolean, list, and date.

3. The method according to claim 1, characterized in that, The method further includes: All text data corresponding to the target object is structured to obtain preliminary structured data to be processed. The text data includes examination reports corresponding to various medical examinations.

4. The method according to claim 3, characterized in that, The step of structuring all text data corresponding to the target object to obtain preliminary structured data to be processed includes: Retrieve all text data corresponding to the target object; The corresponding preset strategy is invoked based on the source of the text data; The text data is structured according to a preset strategy to obtain preliminary structured data to be processed.

5. A structured data generation device, characterized in that, include: The data acquisition module is used to acquire the preliminary structured data to be processed. The preliminary structured data to be processed includes at least one key-value pair; the key-value pair includes corresponding key data and value data. The grouping module is used to group the key-value pairs in the preliminary structured data to be processed according to the key data, including: grouping key-value pairs with the same structure field into the same group; The logic configuration module is used to respond to user input logic data and configure combinational logic based on the logic data. The user customizes the logic data according to the specific requirements of the preliminary structured data to be processed and configures the logic data into combinational logic. The calculation module is used to obtain the combinational logic corresponding to each group, and to calculate all the value data in the group according to the combinational logic to obtain the final value data; The combination module is used to combine the key data corresponding to each group and the corresponding final value data into final key-value pair data to obtain the final structured data; The step of obtaining the combination logic corresponding to each group includes: reading the data type of the value data in each group; calling the corresponding preset combination logic according to the data type; and setting the preset combination logic as the combination logic corresponding to each group.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the structured data generation method as described in any one of claims 1 to 4.

7. An electronic device, characterized in that, include: processor; as well as A memory for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the structured data generation method as described in any one of claims 1 to 4.

Images