Data processing method, device and electronic device

Abstract

The present application provides a data processing method, device and electronic device, the data processing method comprising: receiving a file to be processed sent by a terminal device, the file to be processed comprising: a plurality of first cells and first data in at least part of the first cells, the first data comprising: a first data type and a first data content; parsing the file to be processed to obtain parsed data corresponding to the first data, the parsed data comprising: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content; determining whether the parsed data type and any second data type of a standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least part of the second cells, the second data comprising: a second data type; if so, generating a target file according to the parsed data content and the second data type. The present application can improve the accuracy of correcting the file to be processed.

Description

Technical Field

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

[0002] In some application document review scenarios, the applicant submits the application documents to the review agency, and the review agency reviews the application documents. Among them, there may be situations where the applicant is not clear about the content and format of the documents required by the review agency, resulting in the problem that the content and format of the application documents do not meet the requirements of the review agency.

[0003] At present, the review agencies need to conduct a large amount of manual correction for the non-standard application documents of the applicant institutions. However, the efficiency of manual correction is low and there is a problem of low correction accuracy. Summary of the invention

[0004] Multiple aspects of the present application provide a data processing method, device and electronic device to improve the correction accuracy of application documents.

[0005] A first aspect of an embodiment of the present application provides a data processing method, which is applied to a server, comprising: receiving a file to be processed sent by a terminal device, the file to be processed comprising: a plurality of first cells and first data in at least some of the first cells, the first data comprising: a first data type and a first data content; parsing the file to be processed to obtain parsed data corresponding to the first data, the parsed data comprising: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content; determining whether the parsed data type and any second data type of a standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least some of the second cells, the second data comprising: a second data type; if so, generating a target file according to the parsed data content and the second data type, the target file comprising: a plurality of third cells and the second data type and parsed data content in the third cells, the layout of the third cells being the same as the layout of the second cells; sending the target file to the terminal device so that the terminal device displays the target file for user confirmation.

[0006] A second aspect of an embodiment of the present application provides a data processing method, which is applied to a terminal device, including: sending a file to be processed to a server, the file to be processed including: a plurality of first cells and first data in at least some of the first cells, the first data including: a first data type and a first data content, the server is used to parse the file to be processed, obtain parsed data corresponding to the first data, determine whether the parsed data type and any second data type of the standard file represent the same data type, and if so, generate a target file according to the data content and the second data type, the parsed data including: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content, the standard file including: a plurality of second cells and second data in at least some of the second cells, the second data including: a second data type, the target file including: a plurality of third cells and the second data type and parsed data content in the third cells, the layout of the third cells being the same as the layout of the second cells; receiving the target file sent by the server, and displaying the target file for the user to confirm the target file.

[0007] A third aspect of an embodiment of the present application provides a data processing device, applied to a server, including:

[0008] A receiving module, configured to receive a file to be processed sent by a terminal device, wherein the file to be processed includes: a plurality of first cells and first data in at least part of the first cells, wherein the first data includes: a first data type and first data content;

[0009] A parsing module, used for parsing the file to be processed to obtain parsed data corresponding to the first data, wherein the parsed data includes: a parsed data type corresponding to the first data type and parsed data content corresponding to the first data content;

[0010] a determination module, configured to determine whether the parsed data type and any second data type of the standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least part of the second cells, the second data comprising: a second data type;

[0011] a generating module, for generating a target file according to the parsed data content and the second data type, wherein the target file includes: a plurality of third cells and the second data type and the parsed data content in the third cells, wherein the layout of the third cells is the same as the layout of the second cells;

[0012] The sending module is used to send the target file to the terminal device so that the terminal device displays the target file for user confirmation.

[0013] A fourth aspect of an embodiment of the present application provides a data processing device, applied to a terminal device, including:

[0014] A sending module is used to send a to-be-processed file to a server, the to-be-processed file includes: a plurality of first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content, the server is used to parse the to-be-processed file, obtain parsed data corresponding to the first data, determine whether the parsed data type and any second data type of the standard file represent the same data type, and if so, generate a target file according to the data content and the second data type, the parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content, the standard file includes: a plurality of second cells and second data in at least part of the second cells, the second data includes: a second data type, the target file includes: a plurality of third cells and the second data type and parsed data content in the third cells, the layout of the third cells is the same as the layout of the second cells;

[0015] The processing module is used to receive the target file sent by the server and display the target file for the user to confirm the target file.

[0016] A fifth aspect of an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the data processing method of the first aspect or the second aspect when executing the computer program.

[0017] A sixth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the data processing method of the first aspect or the second aspect.

[0018] The embodiment of the present application is applied to the review scenario of the application document, and the data processing method provided is applied to the server, including: receiving a file to be processed sent by a terminal device, the file to be processed includes: a plurality of first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content; parsing the file to be processed to obtain parsed data corresponding to the first data, the parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content; determining whether the parsed data type and any second data type of the standard file represent the same data type, the standard file includes: a plurality of second cells and second data in at least part of the second cells, the second data includes: a second data type; if so, generating a target file according to the parsed data content and the second data type, the target file includes: a plurality of third cells and the second data type and the parsed data content in the third cells, the layout of the third cells is the same as the layout of the second cells; sending the target file to the terminal device so that the terminal device displays the target file for the user to confirm. The embodiment of the present application generates the target file according to the parsed data content and the second data type when determining that the parsed data type and the second data type of the standard file represent the same data type, thereby being able to efficiently generate application documents that meet the requirements of the review agency. In addition, the accuracy of generating application documents can be improved by automatically parsing the files to be processed and generating target files. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0020] Figure 1 A schematic diagram of an application scenario provided for an exemplary embodiment of the present application;

[0021] Figure 2 A flowchart of a data processing method provided for an exemplary embodiment of the present application;

[0022] Figure 3 A flowchart of another data processing method provided for an exemplary embodiment of the present application;

[0023] Figure 4 A schematic diagram of optical character recognition provided for an exemplary embodiment of the present application;

[0024] Figure 5 A schematic diagram of a data processing method provided for an exemplary embodiment of the present application;

[0025] Figure 6A flowchart of another data processing method provided for an exemplary embodiment of the present application;

[0026] Figure 7 A structural block diagram of a data processing device provided for an exemplary embodiment of the present application;

[0027] Figure 8 A structural block diagram of another data processing device provided for an exemplary embodiment of the present application;

[0028] Fig. 9 A schematic structural diagram of an electronic device provided for an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only 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 making creative work are within the scope of protection of the present application.

[0030] In view of the problem of low accuracy and low efficiency in manually correcting application documents in the review scenario of existing application documents, the data processing method provided by the embodiment of the present application includes: receiving a file to be processed sent by a terminal device, the file to be processed includes: a plurality of first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content; parsing the file to be processed to obtain parsed data corresponding to the first data, the parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content; determining whether the parsed data type and any second data type of the standard file represent the same data type, the standard file includes: a plurality of second cells and second data in at least part of the second cells, the second data includes: a second data type; if so, generating a target file according to the parsed data content and the second data type, the target file includes: a plurality of third cells and the second data type and the parsed data content in the third cells, the layout of the third cells is the same as the layout of the second cells; sending the target file to the terminal device so that the terminal device displays the target file for user confirmation. The embodiment of the present application generates the target file according to the parsed data content and the second data type when determining that the parsed data type and any second data type of the standard file represent the same data type, thereby being able to efficiently generate application documents that meet the requirements of the review agency. In addition, the accuracy of generating application documents can be improved by automatically parsing the files to be processed and generating target files.

[0031] In this embodiment, the data processing method can be an overall data processing method implemented by a cloud computing system. In addition, the server executing the data processing method can be a cloud server, so as to run various neural network models by taking advantage of the resources on the cloud; relative to the cloud, the data processing method can also be applied to server-side devices such as conventional servers or server arrays, which are not limited here.

[0032] In addition, in any application document review scenario of the data processing method provided in the embodiment of the present application, for example, in import and export trade, the customs declaration unit (application agency) needs to prepare the relevant information of the customs declaration unit and the imported and exported goods into an application document and submit it to the customs (review agency) for review. Specifically, since the customs declaration unit is not clear about the application documents required by the customs, the content and file format of the application documents submitted by the customs declaration unit will not meet the requirements of the customs. The customs needs to correct the application documents to obtain a target file that meets the requirements. Among them, the application document is the pending document of this application.

[0033] For example, refer to Figure 1 , the pending document 11 is the application document that the customs declaration unit is going to or has submitted to the customs, and the standard document is the format of the application document required by the customs. The target file 13 is a document that meets the customs requirements generated based on the pending document 11 and the standard file 13. Figure 1 In standard file 12, the customs only requires the declaration unit to submit the trading country, destination country and gross weight, and does not require the number of pieces and net weight. In the pending file 11, the first data type "trading country (region)", "destination country (region)" and "gross weight (kg)" also do not meet the customs requirements. The second data type corresponding to the customs requirements is "trading country", "destination country" and "gross weight".

[0034] Furthermore, the data processing method of the embodiment of the present application is to generate a target file that meets the requirements of the review agency. The format and content of the target file need to meet the requirements of the review agency, and some data of the target file comes from the files to be processed provided by the applicant agency, thereby achieving fast and accurate generation of the target file.

[0035] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0036] Figure 2 A flowchart of a data processing method provided by an exemplary embodiment of the present application. Figure 2 The data processing method shown is applied to a server and specifically includes the following steps:

[0037] S201, receiving a file to be processed sent by a terminal device.

[0038] In the embodiment of the present application, if the original application document of the applicant organization is in image format, the terminal device can directly upload the original application document to the server as a file to be processed. If the original application document of the applicant organization is in PDF, word or Excel format, the terminal device can also use camera scanning technology to scan the original application document to obtain an image and upload it to the server as a file to be processed. In addition, when the original application document is in PDF, word or Excel format, it can also be directly uploaded to the server as a file to be processed.

[0039] Reference Figure 1 , the file to be processed 11 includes: a plurality of first cells and first data in at least part of the first cells, the first data including: a first data type and a first data content. Specifically, all data in each first cell in the file to be processed 11 are first data, and each first data includes: a first data type and a first data content. In an optional embodiment, there may be no data in the first cell, or the first data in the first cell may be only the first data type or the first data content.

[0040] For example, in Figure 1 In the figure, the file to be processed 11 includes multiple first data, namely “trading country (region), country A”, “destination country (region), country B”, “number of pieces, 1894”, “gross weight (kg), 24533.2”, and “net weight (kg), 22354.2”. Among them, for the first data “trading country (region), country A”, the first data type is “trading country (region)”, and the first data content is “country A”. For the first data “destination country (region), country B”, the first data type is “destination country (region)”, and the first data content is “country B”. For the first data “number of pieces, 1894”, the first data type is “number of pieces”, and the first data content is “1894”. For the first data “gross weight (kg), 24533.2”, the first data type is “gross weight (kg)”, and the first data content is “24533.2”. For the first data "net weight (kg), 22354.2", the first data type is "net weight (kg)", and the first data content is "22354.2".

[0041] In the embodiment of the present application, automatic correction of to-be-processed files of different formats can be achieved.

[0042] S202: Parse the file to be processed to obtain parsed data corresponding to the first data.

[0043] The parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content.

[0044] Exemplarily, referring to Table 1, the parsed data obtained after parsing the file to be processed 11 is shown in Table 1.

[0045] Table 1

[0046] Parsing data types Parsing data content Parsing data 1 Trading country (region) Country A Parsing data 2 Destination country (region) Country B Parsing data 3 Number of pieces 1894 Parsing data 4 Gross weight (kg) 24533.2 Parsing data 5 Net weight (kg) 22354.2

[0047] In the embodiment of the present application, the purpose of parsing the to-be-processed file is to completely and accurately parse out the data in each first cell of the to-be-processed file to obtain corresponding parsed data, wherein the parsed data can be completely the same as the first data or partially the same.

[0048] S203: Determine whether the parsed data type and any second data type in the standard file represent the same data type.

[0049] The standard file includes: a plurality of second cells and second data in at least part of the second cells, and the second data includes: a second data type. Figure 1 Specifically, all data in each second cell in the standard file 12 is second data, and each second data includes: a second data type. In an optional embodiment, the second cell may also include a second data type and a second data content, wherein the second data content is content to be replaced, specifically, replaced by the first data content of the same data type in the file to be processed.

[0050] In addition, the file format of the standard file may also be image, PDF, word or Excel, etc. The standard file may be parsed in the same parsing manner as the above-mentioned file to be processed to obtain parsed data corresponding to the second data.

[0051] For example, in Figure 1 In the example, the standard file 12 includes a plurality of second data, which are divided into "trading country", "destination country" and "gross weight". The corresponding second data types are also "trading country", "destination country" and "gross weight". In an optional embodiment, the second data may also include second data content. For example, if the second data is "trading country C", then when generating the target file, "C" may be replaced with "A".

[0052] Furthermore, determining whether the parsed data type and any second data type in the standard file represent the same data type refers to comparing each parsed data type and each second data type in pairs to determine the parsed data type and the second data type that represent the same data type. Figure 1, where the parsed data type "trading country (region)" and the second data type "trading country" represent the same data type. The parsed data type "shipping country (region)" and the second data type "shipping country" represent the same data type. "Gross weight (kg)" and the second data type "gross weight" represent the same data type.

[0053] S204: If yes, generate a target file according to the parsed data content and the second data type.

[0054] The target file includes: a plurality of third cells and the second data type and parsed data content in the third cells, and the layout of the third cells is the same as the layout of the second cells.

[0055] For example, refer to Figure 1 , the target file 13 includes a plurality of third cells, and the layout of the third cells is the same as the layout of the second cells of the standard file 12. And the distribution of each second data type in the third cells is also the same as the distribution of the second data type in the second cells. It can be understood that when it is determined that the parsed data type and any second data type of the standard file represent the same data type, the parsed content corresponding to the parsed data type is input into the second cell corresponding to the second data type in the standard file.

[0056] In an optional embodiment, if the parsed data type corresponding to the to-be-processed file 11 has no corresponding second data type in the standard file 12, the parsed data type and the parsed data content corresponding to the parsed data type are discarded when generating the target file 13.

[0057] S205: Send the target file to the terminal device, so that the terminal device displays the target file for user confirmation.

[0058] In addition, the terminal device can be a terminal device corresponding to an application agency (such as a customs declaration unit) or an audit agency (such as customs). That is, after the application agency uploads the pending documents, it obtains the target file generated by the server, and then can submit it to the audit agency for review after the application agency confirms the target file. If the application agency submits pending documents to the audit agency, the audit agency uploads the pending documents to the server, and the target file generated by the server can be used as a formal application document after the audit agency confirms it. Therefore, the user can be the corresponding staff of the application agency or the audit agency.

[0059] In the embodiment of the present application, any format of the to-be-processed file can be parsed, and a target file that meets the requirements of the auditing agency can be generated in combination with the standard file. Specifically, when it is determined that the parsed data type and any second data type of the standard file represent the same data type, the target file is generated according to the parsed data content and the second data type, thereby enabling efficient generation of application documents that meet the requirements of the auditing agency. Moreover, the use of automation to parse the to-be-processed file and then generate the target file can improve the accuracy of generating the application document.

[0060] In the embodiment of the present application, another data processing method is provided, such as Figure 3 As shown, the data processing method specifically includes the following steps:

[0061] S301, receiving a file to be processed sent by a terminal device.

[0062] S302, using optical character recognition technology to determine multiple target data of the file to be processed.

[0063] Among them, if the file to be processed is in image format, optical character recognition technology (OCR) is used to identify the file to be processed. If the file to be processed is in PDF, word or Excel format, the terminal device can use a camera to capture the image corresponding to the file to be processed, and then use OCR technology to recognize it. In addition, for the file to be processed in PDF, word or Excel format directly uploaded to the server, other methods can also be used for recognition to obtain multiple target data, which is not limited.

[0064] The target data includes: the recognition text and the position information corresponding to the recognition text, the recognition text represents the recognition result corresponding to the first data type, or the recognition text represents the recognition result corresponding to the first data content.

[0065] For example, refer to Figure 4 , for Figure 1 Schematic diagram of the optical character recognition process of the to-be-processed file 11. Each dotted box is a bounding box for the recognized text. The text in the bounding box is the recognized file. The coordinate values ​​(in pixels) of the diagonal vertices of the bounding box are the position information corresponding to the recognized text. Figure 4 In the example, the recognized text in the boundary box 41 is "Trading Country (Region)", and the corresponding position information is the coordinate value of the diagonal point D and the coordinate value of the diagonal point F. Figure 4 In the figure, X represents the horizontal coordinate and Y represents the vertical coordinate.

[0066] Referring to Table 2, an example is shown Figure 4Corresponding to the identified multiple target data. In Table 2, Y1 represents the ordinate of the vertex in the upper left corner of the bounding box, and X1 represents the abscissa of the vertex in the upper left corner of the bounding box. Y2 represents the ordinate of the vertex in the lower right corner of the bounding box, and X2 represents the abscissa of the vertex in the lower right corner of the bounding box. For example, in the position information (85, 100, 100, 140) of target data 1 in Table 2, "85" represents Figure 4 The vertical coordinate of the vertex D of the bounding box 41, the first "100" indicates Figure 4 The horizontal coordinate of the vertex D of the bounding box 41 in the middle. The second "100" indicates Figure 4 The vertical coordinate of the vertex F of the middle bounding box 41, "140" indicates Figure 4 The horizontal coordinate of the vertex F of the bounding box 41.

[0067] Table 2

[0068] Recognize text Position information (Y1, X1, Y2, X2) Target data 1 Trading country (region) (85,100,100,140) Target data 2 Destination country (region) (85,270,95,310) Target data 3 Country A (85,210,95,240) Target data 4 Country B (85,350,95,380) Target data 5 Number of pieces (100,100,110,130) Target data 6 Gross weight (kg) (100,250,110,300) Target data 7 Net weight (kg) (100,320,110,370) Target data 8 1894 (120,100,135,135) Target data 9 24533.2 (120,240,135,285) Target data 10 22354.2 (120,320,135,355)

[0069] In the embodiment of the present application, the position information of the recognized text may also be represented by other methods, which are not limited here. The position information of the recognized text represents the relative position of the recognized text in the file to be processed.

[0070] S303: Input the two target data into the first matching model for matching processing to obtain a first matching result.

[0071] The first matching result is used to indicate whether the recognized texts of the two target data are the parsed data type and parsed data content in the same first cell.

[0072] In an embodiment of the present application, the first matching model is pre-trained and can perform matching processing on any two input target data to determine whether the recognized texts of the two input target data are the corresponding parsed data types and parsed data contents in the same first cell.

[0073] Exemplarily, the target data 1 and target data 2 in Table 2 are input into the first matching model, and the output matching result is 0, indicating that the recognition text "trading country (region)" and the recognition text "destination country (region)" are not the parsed data type and parsed data content corresponding to the same first cell. The target data 1 and target data 3 in Table 2 are input into the first matching model, and the output matching result is 1, indicating that the recognition text "trading country (region)" and the recognition text "country A" are the parsed data type and parsed data content corresponding to the same first cell.

[0074] In the embodiment of the present application, any two target data are input into the first matching model for matching processing, and the matching results of the any two target data can be obtained.

[0075] Specifically, the two target data are input into the first matching model for matching processing to obtain a first matching result, including: inputting the target data into the encoder of the first matching model for encoding processing to obtain a first feature vector corresponding to the target data; inputting the first feature vector corresponding to the two target data into the matching sub-model of the first matching model for matching processing to obtain a first matching result.

[0076] Furthermore, the target data is input into the encoder of the first matching model for encoding processing to obtain a first feature vector corresponding to the target data, including: using the encoder to execute the following steps: semantically vectorizing the recognized text of the target data to obtain a first semantic vector; encoding the first semantic vector to obtain an encoding vector; normalizing the position information corresponding to the recognized text to a preset position range to obtain target position information; performing word vector processing on the target position information to obtain a first word vector; concatenating the encoding vector and the first word vector to obtain a first feature vector corresponding to the target data.

[0077] Reference Figure 5 , the two target data are target data A and target data B, Figure 5 Only the process of obtaining the first feature vector A according to the target data A is shown. The process of obtaining the first feature vector B according to the target data B is the same as the process of the target data A, and will not be repeated here. Specifically, the recognition text of the target data A is semantically vectorized to obtain the first semantic vector, and the semantic vectorization can be performed in the form of word embedding. Among them, the first semantic vector can be expressed as E1=[e1,e2,…,en], ei (i is 1 to n, n is an integer greater than 1) represents the vector corresponding to the i-th character in the recognition text. Furthermore, the first semantic vector E1 is encoded to obtain the encoded vector D1, and the encoding process can be encoded using a unidirectional LSTM (Long-Short Term Memory) network.

[0078] In addition, the normalized preset position range of the ordinate can be preset to 1 to y, and the normalized preset position range of the abscissa can be preset to 1 to x, where x and y can be set according to empirical values. For example, in Table 2, the minimum value of the ordinate is 85 and the maximum value is 135, then the minimum value 85 is normalized to 1, the maximum value 135 is normalized to 20, and other ordinate values ​​are normalized to between 1 and 20 in proportion. The abscissa is normalized in the same way, which will not be repeated here. It should be added that the normalization of the ordinate and abscissa constrains each other. It can be understood that the image corresponding to the file to be processed is proportionally reduced. Among them, the target position information is the result of normalizing the position information corresponding to the recognized text, recorded as (y1 x1y2 x2). Further, the target position information (y1 x1 y2 x2) is word vectorized to obtain the first word vector D2 = [f1, f2, f3, f4], where the word vector processing can also be done by word embedding. The obtained f1 is the word vector corresponding to y1, f2 is the word vector corresponding to x1, f3 is the word vector corresponding to y2, and f4 is the word vector corresponding to x2.

[0079] Finally, the encoding vector D1 and the first word vector D2 are concatenated to obtain the first feature vector A corresponding to the target data.

[0080] In an embodiment of the present application, the target data B is subjected to the same processing as above to obtain a first feature vector B. Then the first feature vector A (h1) and the first feature vector B (h2) are input into the matching sub-model to obtain a first matching result P. The matching sub-model may be a neural network model such as CNN (Convolutional Neural Networks) or RNN (Recurrent Neural Network). The model parameter W of the matching sub-model is pre-trained, and the first matching result P = h1·W·h2, wherein the first matching result P is a value from 0 to 1, and a first threshold value may be pre-set, such as 0.5. When P is greater than the first threshold value, it is determined that the first matching result indicates that the recognition text of the target data A and the recognition text of the target data B are the parsed data type and parsed data content corresponding to the same first cell.

[0081] An optional embodiment, if the recognized text is a number, semantic vectorization is performed on the recognized text of the target data to obtain a first semantic vector, including: normalizing the recognized text of the target data to a preset text; and semantic vectorization is performed on the preset text to obtain a first semantic vector.

[0082] For example, in Table 2, the recognized texts of target data 8, target data 9, and target data 10 are all numbers, so these numbers can be normalized into a preset text, such as "number". In the above semantic vectorization processing, the preset text "number" can be semantically vectorized.

[0083] In the embodiment of the present application, the first matching model is used to accurately parse various data types and data contents in the file to be processed, and group the data types and data contents of the same cell to obtain parsed data.

[0084] S304: Generate parsed data according to the first matching result and the target data.

[0085] Exemplarily, if the first matching result indicates that the recognition text of target data A and the recognition text of target data B are the parsed data type and parsed data content corresponding to the same first cell, a set of parsed data (recognition text of target data A, recognition text of target data B) is generated.

[0086] In the embodiment of the present application, by adopting the methods of S303 and S304 for any two target data, multiple groups of parsed data can be obtained, for example, refer to Table 1.

[0087] S305: Input the parsed data and the second data into a second matching model for matching processing to obtain a second matching result.

[0088] The second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

[0089] Specifically, the parsed data and the second data are input into the second matching model for matching processing to obtain a second matching result, including: performing semantic vectorization processing on the parsed data to obtain a second semantic vector; inputting the second semantic vector into the encoder of the second matching model for encoding processing to obtain a second feature vector; performing semantic vectorization processing on the second data to obtain a third semantic vector; inputting the third semantic vector into the encoder of the second matching model for encoding processing to obtain a third feature vector; inputting the second feature vector and the third feature vector into the operation layer of the second matching model for data processing to obtain the similarity between the parsed data type and the second data type; if the similarity is greater than the similarity threshold, it is determined that the parsed data type and the second data type represent the same data type.

[0090] Among them, the parsed data is as shown in Table 1, and the second matching model is pre-trained. Among them, the second eigenvector h3 is obtained, and the third eigenvector h4 is obtained. The operation layer of the second matching model performs a dot product calculation on the second eigenvector h3 and the third eigenvector h4. The obtained similarity T=h3·h4. Among them, the similarity is a value between 0 and 1. The similarity threshold can be set to 0.6. When the similarity is greater than 0.6, it is determined that the parsed data type and the second data type represent the same data type. It can be understood that the second matching result is the similarity.

[0091] For example, referring to Table 1 and Figure 1 , parsed data 1 to parsed data 4 are matched with the second data "trading country", the second data "destination country", and the second data "gross weight" respectively, and the second matching result obtained is that the parsed data type and the second data type corresponding to parsed data 1 and the second data "trading country" represent the same data type. The parsed data type and the second data type corresponding to parsed data 2 and the second data "destination country" represent the same data type. The parsed data type and the second data type corresponding to parsed data 4 and the second data "gross weight" represent the same data type.

[0092] In the embodiment of the present application, the use of a pre-trained second matching model can quickly and accurately match the parsed data and the second data, thereby improving the correction efficiency and correction accuracy of the file to be processed.

[0093] S306: If yes, generate a target file according to the parsed data content and the second data type.

[0094] S307, sending the target file to the terminal device so that the terminal device displays the target file for user confirmation.

[0095] In the embodiment of the present application, the text in the to-be-processed file and the location information of the text can be fully utilized, and the first matching model can be used to accurately parse the parsed data. The first matching model parses the to-be-processed file, is not limited by the field range of the text in the to-be-processed file, and has good generalization and robustness. Then the second matching model is used to match the parsed data with the second data of the standard file, which can reduce the manual input of the correction and achieve a higher data processing efficiency.

[0096] In the embodiments of this application, refer to Figure 6 , provides another data processing method, which is applied to terminal devices, such as Figure 6 As shown, the data processing method specifically includes the following steps:

[0097] S601, sending a file to be processed to a server.

[0098] Among them, the file to be processed includes: multiple first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content, the server is used to parse the file to be processed, obtain the parsed data corresponding to the first data, and determine whether the parsed data type and any second data type of the standard file represent the same data type. If so, generate a target file based on the data content and the second data type, the parsed data includes: the parsed data type corresponding to the first data type and the parsed data content corresponding to the first data content, the standard file includes: multiple second cells and second data in at least part of the second cells, the second data includes: a second data type, the target file includes: multiple third cells and the second data type and parsed data content in the third cells, and the layout of the third cells is the same as that of the second cells.

[0099] S602, receiving a target file sent by the server, and displaying the target file for the user to confirm the target file.

[0100] The specific implementation of S601 and S606 refers to the above embodiment and will not be described in detail here.

[0101] In the embodiments of this application, refer to Figure 7 In addition to providing a data processing method, a data processing device 70 is also provided, which is applied to a server. The data processing device 70 includes:

[0102] The receiving module 71 is used to receive a file to be processed sent by a terminal device, where the file to be processed includes: a plurality of first cells and first data in at least part of the first cells, where the first data includes: a first data type and first data content;

[0103] The parsing module 72 is used to parse the file to be processed to obtain parsed data corresponding to the first data, wherein the parsed data includes: a parsed data type corresponding to the first data type and parsed data content corresponding to the first data content;

[0104] A determination module 73 is used to determine whether the parsed data type and any second data type of the standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least part of the second cells, the second data comprising: a second data type;

[0105] A generating module 74, configured to generate a target file according to the parsed data content and the second data type, wherein the target file includes: a plurality of third cells and the second data type and the parsed data content in the third cells, wherein the layout of the third cells is the same as the layout of the second cells;

[0106] The sending module is used to send the target file to the terminal device so that the terminal device displays the target file for user confirmation.

[0107] In an optional embodiment, the parsing module 67 is specifically used to use optical character recognition technology to determine multiple target data of the file to be processed, the target data including: recognition text and position information corresponding to the recognition text, recognition result corresponding to the first data type represented by the recognition text, or recognition result corresponding to the first data content represented by the recognition text; inputting two target data into the first matching model for matching processing to obtain a first matching result, the first matching result is used to indicate whether the recognition texts of the two target data are the parsed data type and parsed data content in the same first cell; generating parsed data based on the first matching result and the target data.

[0108] In an optional embodiment, when the parsing module 72 inputs two target data into the first matching model for matching processing to obtain a first matching result, it is specifically used to: input the target data into the encoder of the first matching model for encoding processing to obtain a first feature vector corresponding to the target data; input the first feature vector corresponding to the two target data into the matching sub-model of the first matching model for matching processing to obtain a first matching result.

[0109] In an optional embodiment, when the parsing module 72 inputs the target data into the encoder of the first matching model for encoding processing to obtain the first feature vector corresponding to the target data, it is specifically used to: use the encoder to perform the following steps: semantically vectorize the recognized text of the target data to obtain a first semantic vector; encode the first semantic vector to obtain an encoding vector; normalize the position information corresponding to the recognized text to a preset position range to obtain target position information; perform word vector processing on the target position information to obtain a first word vector; concatenate the encoding vector and the first word vector to obtain the first feature vector corresponding to the target data.

[0110] In an optional embodiment, when the parsing module 72 performs semantic vectorization processing on the recognized text of the target data to obtain the first semantic vector, it is specifically used to: normalize the recognized text of the target data to a preset text; and perform semantic vectorization processing on the preset text to obtain the first semantic vector.

[0111] In an optional embodiment, the determination module 73 is specifically used to: input the parsed data and the second data into a second matching model for matching processing to obtain a second matching result, and the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

[0112] In an optional embodiment, when the determination module 73 inputs the parsed data and the second data into the second matching model for matching processing to obtain a second matching result, it is specifically used to: perform semantic vectorization processing on the parsed data to obtain a second semantic vector; input the second semantic vector into the encoder of the second matching model for encoding processing to obtain a second feature vector; perform semantic vectorization processing on the second data to obtain a third semantic vector; input the third semantic vector into the encoder of the second matching model for encoding processing to obtain a third feature vector; input the second feature vector and the third feature vector into the operation layer of the second matching model for data processing to obtain the similarity between the parsed data type and the second data type; if the similarity is greater than the similarity threshold, it is determined that the parsed data type and the second data type represent the same data type.

[0113] In the embodiments of this application, refer to Figure 8 , another data processing device 80 is also provided, which is applied to a terminal device, and the data processing device 80 includes:

[0114] The sending module 81 is used to send a to-be-processed file to a server, the to-be-processed file includes: a plurality of first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content, the server is used to parse the to-be-processed file, obtain parsed data corresponding to the first data, determine whether the parsed data type and any second data type of the standard file represent the same data type, and if so, generate a target file according to the data content and the second data type, the parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content, the standard file includes: a plurality of second cells and second data in at least part of the second cells, the second data includes: a second data type, the target file includes: a plurality of third cells and the second data type and parsed data content in the third cells, the layout of the third cells is the same as the layout of the second cells;

[0115] The processing module 82 is used to receive the target file sent by the server and display the target file for the user to confirm the target file.

[0116] The data processing device provided by the embodiment of the present application can make full use of the text in the file to be processed and the location information of the text, and use the first matching model to accurately parse the parsed data. The first matching model parses the file to be processed, which is not limited by the field range of the text in the file to be processed and has good generalization and robustness. Then, the second matching model is used to match the parsed data with the second data of the standard file, which can reduce the manual input of the correction and achieve a higher data processing efficiency.

[0117] In addition, in some of the processes described in the above embodiments and the accompanying drawings, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel, and are only used to distinguish between different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to different types.

[0118] Fig. 9 The following is a schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present application. The electronic device is used to run the above data processing method. Fig. 9 As shown, the electronic device includes: a memory 94 and a processor 95.

[0119] The memory 94 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. The memory 94 can be an object storage service (OSS).

[0120] The memory 94 may be implemented by any type of volatile or nonvolatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0121] The processor 95 is coupled to the memory 94 and is used to execute the computer program in the memory 94, so as to: receive a file to be processed sent by a terminal device, the file to be processed includes: a plurality of first cells and first data in at least part of the first cells, the first data includes: a first data type and a first data content; parse the file to be processed to obtain parsed data corresponding to the first data, the parsed data includes: a parsed data type corresponding to the first data type and a parsed data content corresponding to the first data content; determine whether the parsed data type and any second data type of a standard file represent the same data type, the standard file includes: a plurality of second cells and second data in at least part of the second cells, the second data includes: a second data type; if so, generate a target file according to the parsed data content and the second data type, the target file includes: a plurality of third cells and the second data type and parsed data content in the third cells, the layout of the third cells is the same as the layout of the second cells; send the target file to the terminal device so that the terminal device displays the target file for user confirmation.

[0122] Further optionally, when the processor 95 parses the file to be processed and obtains the parsed data corresponding to the first data, it is specifically used to: use optical character recognition technology to determine multiple target data of the file to be processed, the target data including: recognition text and position information corresponding to the recognition text, the recognition text represents the recognition result corresponding to the first data type, or the recognition text represents the recognition result corresponding to the first data content; input the two target data into the first matching model for matching processing to obtain a first matching result, the first matching result is used to indicate whether the recognition texts of the two target data are the parsed data type and parsed data content in the same first cell; generate parsed data according to the first matching result and the target data.

[0123] Further optionally, when the processor 95 inputs the two target data into the first matching model for matching processing to obtain the first matching result, it is specifically used to: input the target data into the encoder of the first matching model for encoding processing to obtain the first feature vector corresponding to the target data; input the first feature vector corresponding to the two target data into the matching sub-model of the first matching model for matching processing to obtain the first matching result.

[0124] Further optionally, when the processor 95 inputs the target data into the encoder of the first matching model for encoding processing to obtain the first feature vector corresponding to the target data, it is specifically used to: use the encoder to perform the following steps: semantically vectorize the recognized text of the target data to obtain a first semantic vector; encode the first semantic vector to obtain an encoding vector; normalize the position information corresponding to the recognized text to a preset position range to obtain target position information; perform word vector processing on the target position information to obtain a first word vector; concatenate the encoding vector and the first word vector to obtain the first feature vector corresponding to the target data.

[0125] In an optional embodiment, when the processor 95 performs semantic vectorization processing on the recognized text of the target data to obtain the first semantic vector, it is specifically used to: normalize the recognized text of the target data to a preset text; and perform semantic vectorization processing on the preset text to obtain the first semantic vector.

[0126] In an optional embodiment, when determining whether the parsed data type and any second data type of the standard file represent the same data type, the processor 95 is specifically used to input the parsed data and the second data into a second matching model for matching processing to obtain a second matching result, and the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

[0127] In an optional embodiment, when the processor 95 inputs the parsed data and the second data into the second matching model for matching processing to obtain a second matching result, it is specifically used to: perform semantic vectorization processing on the parsed data to obtain a second semantic vector; input the second semantic vector into the encoder of the second matching model for encoding processing to obtain a second feature vector; perform semantic vectorization processing on the second data to obtain a third semantic vector; input the third semantic vector into the encoder of the second matching model for encoding processing to obtain a third feature vector; input the second feature vector and the third feature vector into the operation layer of the second matching model for data processing to obtain the similarity between the parsed data type and the second data type; if the similarity is greater than the similarity threshold, it is determined that the parsed data type and the second data type represent the same data type.

[0128] In an optional embodiment, the processor 95 is also used to send a file to be processed to the server, the file to be processed includes: multiple first cells and first data in at least some of the first cells, the first data includes: a first data type and a first data content, the server is used to parse the file to be processed, obtain parsed data corresponding to the first data, determine whether the parsed data type and any second data type of the standard file represent the same data type, and if so, generate a target file based on the parsed data content and the second data type, the parsed data includes: the parsed data type corresponding to the first data type and the parsed data content corresponding to the first data content, the standard file includes: multiple second cells and second data in at least some of the second cells, the second data includes: the second data type, the target file includes: multiple third cells and the second data type and parsed data content in the third cells, and the layout of the third cells is the same as the layout of the second cells; receive the target file sent by the server, and display the target file for the user to confirm the target file.

[0129] Furthermore, if Fig. 9 The electronic device also includes: a firewall 91, a load balancer 92, a communication component 96, a power supply component 98 and other components. Fig. 9 Only some components are shown schematically, which does not mean that the electronic device only includes Fig. 9 Components shown.

[0130] The electronic device provided by the embodiment of the present application can make full use of the text in the file to be processed and the location information of the text, and use the first matching model to accurately parse the parsed data. The first matching model parses the file to be processed, which is not limited by the field range of the text in the file to be processed and has good generalization and robustness. Then, the second matching model is used to match the parsed data with the second data of the standard file, which can reduce the manual input of the correction and achieve a higher data processing efficiency.

[0131] Accordingly, the embodiment of the present application also provides a computer-readable storage medium storing a computer program, which, when the computer program / instruction is executed by a processor, causes the processor to implement Figure 2 or Figure 3 Steps in the method shown.

[0132] Accordingly, the embodiment of the present application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, causes the processor to implement Figure 2 or Figure 3 Steps in the method shown.

[0133] Above Fig. 9 The communication component is configured to facilitate wired or wireless communication between the device where the communication component is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G / LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast-related text from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0134] Above Fig. 9 The power supply component provides power to various components of the device where the power supply component is located. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device where the power supply component is located.

[0135] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0136] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0137] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0138] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0139] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0140] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0141] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store text. The text can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store text that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0143] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A data processing method, characterized in that: Applied to a server, the data processing method includes: Receiving a file to be processed sent by a terminal device, the file to be processed comprising: a plurality of first cells and first data in at least part of the first cells, the first data comprising: a first data type and first data content; Parsing the to-be-processed file to obtain parsed data corresponding to the first data, the parsed data including: a parsed data type corresponding to the first data type and parsed data content corresponding to the first data content; determining whether the parsed data type and any second data type of a standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least a portion of the second cells, the second data comprising: the second data type; If yes, then generating a target file according to the parsed data content and the second data type, the target file comprising: a plurality of third cells and the second data type and the parsed data content in the third cells, the layout of the third cells being the same as the layout of the second cells; Sending the target file to the terminal device so that the terminal device displays the target file for user confirmation; The determining whether the parsed data type and any second data type of the standard file represent the same data type includes: inputting the parsed data and the second data into a second matching model for matching processing to obtain a second matching result, wherein the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

2. The data processing method according to claim 1, characterized in that: The file to be processed is in an image format, and the step of parsing the file to be processed to obtain parsed data corresponding to the first data includes: Using optical character recognition technology, determine multiple target data of the file to be processed, the target data including: recognition text and position information corresponding to the recognition text, the recognition text represents the recognition result corresponding to the first data type, or the recognition text represents the recognition result corresponding to the first data content; Inputting two target data into a first matching model for matching processing to obtain a first matching result, wherein the first matching result is used to indicate whether the recognized texts of the two target data are the same parsed data type and parsed data content in the same first cell; The parsed data is generated according to the first matching result and the target data.

3. The data processing method according to claim 2, characterized in that: The step of inputting the two target data into a first matching model for matching processing to obtain a first matching result includes: Inputting the target data into the encoder of the first matching model for encoding processing to obtain a first feature vector corresponding to the target data; The first feature vectors corresponding to the two target data are input into the matching sub-model of the first matching model for matching processing to obtain the first matching result.

4. The data processing method according to claim 3, characterized in that: The step of inputting the target data into the encoder of the first matching model for encoding to obtain a first feature vector corresponding to the target data includes: using the encoder to perform the following steps: Performing semantic vectorization processing on the recognition text of the target data to obtain a first semantic vector; Performing encoding processing on the first semantic vector to obtain an encoding vector; Normalizing the position information corresponding to the recognized text to a preset position range to obtain target position information; Performing word vector processing on the target position information to obtain a first word vector; The encoding vector and the first word vector are concatenated to obtain a first feature vector corresponding to the target data.

5. The data processing method according to claim 4, characterized in that: If the recognized text is a number, the semantic vectorization processing is performed on the recognized text of the target data to obtain a first semantic vector, including: Normalizing the recognized text of the target data into a preset text; The preset text is semantically vectorized to obtain the first semantic vector.

6. The data processing method according to claim 1, characterized in that: The step of inputting the parsed data and the second data into a second matching model for matching processing to obtain a second matching result includes: Performing semantic vectorization processing on the parsed data to obtain a second semantic vector; Inputting the second semantic vector into the encoder of the second matching model for encoding processing to obtain a second feature vector; Performing semantic vectorization processing on the second data to obtain a third semantic vector; Inputting the third semantic vector into the encoder of the second matching model for encoding processing to obtain a third feature vector; Inputting the second feature vector and the third feature vector into the operation layer of the second matching model for data processing to obtain the similarity between the parsed data type and the second data type; If the similarity is greater than a similarity threshold, it is determined that the parsed data type and the second data type represent the same data type.

7. A data processing method, characterized in that: Applied to a terminal device, the data processing method includes: Sending a file to be processed to a server, the file to be processed comprising: a plurality of first cells and first data in at least part of the first cells, the first data comprising: a first data type and a first data content, the server being used to parse the file to be processed, obtain parsed data corresponding to the first data, determine whether the parsed data type and any second data type of a standard file represent the same data type, and if so, generate a target file according to the parsed data content and the second data type, the parsed data comprising: the parsed data type corresponding to the first data type and the parsed data content corresponding to the first data content, the standard file comprising: a plurality of second cells and second data in at least part of the second cells, the second data comprising: the second data type, the target file comprising: a plurality of third cells and the second data type and the parsed data content in the third cells, the layout of the third cells being the same as that of the second cells; receiving the target file sent by the server, and displaying the target file for the user to confirm the target file; The determining whether the parsed data type and any second data type of the standard file represent the same data type includes: inputting the parsed data and the second data into a second matching model for matching processing to obtain a second matching result, wherein the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

8. A data processing device, characterized in that: Applied to a server, the data processing device comprises: A receiving module, configured to receive a to-be-processed file sent by a terminal device, wherein the to-be-processed file includes: a plurality of first cells and first data in at least part of the first cells, wherein the first data includes: a first data type and first data content; A parsing module, configured to parse the to-be-processed file to obtain parsed data corresponding to the first data, wherein the parsed data includes: a parsed data type corresponding to the first data type and parsed data content corresponding to the first data content; a determination module, configured to determine whether the parsed data type and any second data type of a standard file represent the same data type, the standard file comprising: a plurality of second cells and second data in at least part of the second cells, the second data comprising: the second data type; a generating module, configured to, if yes, generate a target file according to the parsed data content and the second data type, the target file comprising: a plurality of third cells and the second data type and the parsed data content in the third cells, the layout of the third cells being the same as the layout of the second cells; A sending module, used for sending the target file to the terminal device, so that the terminal device displays the target file for user confirmation; The determination module is specifically used to: input the parsed data and the second data into a second matching model for matching processing to obtain a second matching result, wherein the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type.

9. A data processing device, characterized in that: Applied to a terminal device, the data processing device comprises: A sending module, used for sending a to-be-processed file to a server, wherein the to-be-processed file comprises: a plurality of first cells and first data in at least part of the first cells, wherein the first data comprises: a first data type and a first data content, wherein the server is used for parsing the to-be-processed file, obtaining parsed data corresponding to the first data, and determining whether the parsed data type and any second data type of a standard file represent the same data type, and if so, generating a target file according to the parsed data content and the second data type, wherein the parsed data comprises: the parsed data type corresponding to the first data type and the parsed data content corresponding to the first data content, wherein the standard file comprises: a plurality of second cells and second data in at least part of the second cells, wherein the second data comprises: the second data type, and wherein the target file comprises: a plurality of third cells and the second data type and the parsed data content in the third cells, wherein the layout of the third cells is the same as that of the second cells; wherein determining whether the parsed data type and any second data type of the standard file represent the same data type comprises: inputting the parsed data and the second data into a second matching model for matching processing, and obtaining a second matching result, wherein the second matching result is used to indicate whether the parsed data type and the second data type represent the same data type; The processing module is used to receive the target file sent by the server and display the target file for the user to confirm the target file.

10. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the data processing method according to any one of claims 1 to 7 when executing the computer program.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor is caused to implement the data processing method according to any one of claims 1 to 7.

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