Method, apparatus and electronic device for processing shared document

Abstract

The application discloses a shared document processing method and device and electronic equipment, and belongs to the technical field of shared document processing. The method comprises the following steps: detecting a first position of abnormal data in a first document, wherein the first document represents a second document of a shared document after N times of operation, and N is a positive integer; obtaining a feature data set corresponding to the first position, wherein the feature data set comprises M feature data corresponding to M times of operation from the second document to the first document, each feature data comprises an operation user, operation content of the operation user and operation result, and M is a positive integer less than or equal to N; comparing the feature data set with the second document to determine first feature data in the feature data set that causes data of the first position to be abnormal; and determining a first processing scheme of the first document according to the first feature data.

Description

Technical Field

[0001] This application belongs to the field of shared document processing technology, specifically relating to a method, apparatus, and electronic device for processing shared documents. Background Technology

[0002] With the widespread use of the internet, the demand for collaborative document sharing among multiple users is increasing. However, during collaborative document sharing, problems often arise due to overlapping or misaligned user actions. Different users' editing behaviors may influence each other, leading to errors or inconsistencies in the document. Current solutions typically address these errors or inconsistencies by comparing the current version with the original version and correcting the current version based on the original. However, if multiple user actions have caused data errors, correcting the current version using this method requires users who performed the correct actions to repeat the same process, resulting in low efficiency. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, and electronic device for processing shared documents, which can solve the problem that existing methods for correcting shared documents result in low operational efficiency.

[0004] To solve the above-mentioned technical problems, this application is implemented as follows:

[0005] Firstly, embodiments of this application provide a method for processing shared documents, including:

[0006] The first position where abnormal data is detected in the first document is represented. The first document represents the document obtained after N operations on the second document of the shared document, where N is a positive integer.

[0007] Obtain the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user of the operation, the operation content of the user, and the operation result. M is a positive integer less than or equal to N.

[0008] The feature dataset is compared with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal;

[0009] Based on the first feature data, a first processing scheme for the first document is determined.

[0010] Secondly, embodiments of this application provide a shared document processing apparatus, including:

[0011] The detection module is used to detect the first position where abnormal data is located in the first document, where the first document represents the document obtained after the second document of the shared document has been processed by N operations, where N is a positive integer;

[0012] The first acquisition module is used to acquire the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations that the first position goes through from the second document to the first document. Each feature data includes: the operating user, the operation content of the operating user, and the operation result. M is a positive integer less than or equal to N.

[0013] The first determining module is used to compare the feature dataset with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal;

[0014] The second determining module is used to determine a first processing scheme for the first document based on the first feature data.

[0015] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0016] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0017] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0018] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0019] In this embodiment, by detecting the first position of abnormal data in the first document obtained after N operations on the second document (i.e., the original document) of the shared document, and obtaining the feature dataset corresponding to the first position, the feature dataset is compared with the second document to determine the first feature data in the feature dataset that causes the data at the first position to be abnormal. Based on the first feature data, a first processing scheme for the first document is determined. That is, the position of the abnormal data in the first document (i.e., the first position) is first located. Since the feature dataset includes M feature data corresponding to the M operations from the second document to the first document at the first position, each feature data includes: the operating user, the operation content of the operating user, and the operation result. Therefore, based on the operating user, operation content, and operation result of each operation at the first position, it can be determined which erroneous operation caused the data abnormality, improving the accuracy of erroneous operation location. Furthermore, the feature data corresponding to the erroneous operation is determined as the first feature data. The first processing scheme for the first document is determined based on the specific first feature data. The first processing scheme is used to correct the first document, which can improve the user's operation efficiency and improve the accuracy of the data. Attached Figure Description

[0020] Figure 1 This is one of the flowcharts illustrating the shared document processing method provided in the embodiments of this application;

[0021] Figure 2 This is a second flowchart illustrating the shared document processing method provided in this application embodiment;

[0022] Figure 3 This is a schematic diagram of the structure of a shared document processing device provided in an embodiment of this application;

[0023] Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of this application;

[0024] Figure 5 This is a structural block diagram of another electronic device provided in the embodiments of this application. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0026] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0027] The method for processing shared documents provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0028] like Figure 1 As shown in the figure, this application provides a method for processing shared documents, which can be applied to a shared document processing system, and may specifically include the following steps:

[0029] Step 101: Detect the first position where the abnormal data is located in the first document. The first document represents the document obtained after the second document of the shared document has been processed by N operations, where N is a positive integer.

[0030] In step 101, the second document (i.e., the original document) of the shared document is first obtained. Since the second document is a shared document, multiple users can operate on it. After N operations, the second document becomes the first document. If anomaly detection is required on the first document, natural language processing technology can be used to analyze and detect the speech and grammar of the first document to determine if there is any abnormal data. If no abnormal data is detected, the first document is considered normal, and the N operations from the second document to the first document are all correct. If abnormal data is detected in the first document, it is considered abnormal, and the location of the abnormal data in the first document (i.e., the first position) needs to be obtained.

[0031] For example, if both the first and second documents are tables, abnormal data could include inconsistent cell formats, incorrect formulas, or data mismatches. By using natural language processing technology to analyze the speech and syntax of the first document, including its data format and formula calculations, abnormal data can be automatically identified.

[0032] Shared documents refer to documents that can be shared and edited by multiple users.

[0033] Determining whether to perform anomaly detection on the first document can be done in several ways, including but not limited to the following: If a detection command is received, it indicates that anomaly detection is required on the first document. Alternatively, if anomaly detection is required every first time interval starting from the acquisition of the second document, then after acquiring the first document, if the time interval between the current time and the last anomaly detection is the first time interval, it indicates that anomaly detection is required on the first document. Or, if anomaly detection is required after each operation, then after performing N operations to obtain the first document, anomaly detection is required on the first document.

[0034] It is understandable that the user who can operate on the second document can be any user or an authorized user, and can be configured as needed.

[0035] In addition, the second document and the document after each operation of the second document can be uploaded to the blockchain to ensure data security and traceability, thereby improving the reliability and stability of shared documents.

[0036] Step 102: Obtain the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user performing the operation, the content of the operation performed by the user, and the result of the operation. M is a positive integer less than or equal to N.

[0037] Specifically, since the aforementioned N operations are not necessarily all operations on the first position, we obtain M operations on the first position from the N operations from the second document to the first document. We then obtain the feature data corresponding to each of these M operations, resulting in M ​​feature data sets. These M feature data sets form the feature dataset for the first position. Each feature data set includes: the number of operations, the user performing the operation, the content of the user's operation, and the result of the operation. This allows us to determine how many operations occurred at the first position, the user performing each operation, the content of the operation, and the result of each operation, providing a clearer understanding of the operation process at the first position.

[0038] For example, the feature data corresponding to the first operation at the first position is: P(1) = {user A, operation content B, operation result C}.

[0039] Step 103: Compare the feature dataset with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal.

[0040] Specifically, each of the M feature data points at the first position in the first document obtained above is compared with the feature data points at the first position in the second document. This allows us to identify the abnormal feature data (i.e., the first feature data) among the M feature data points, and thus determine which erroneous operation caused the abnormal data at the first position in the first document, thereby improving the accuracy of locating the erroneous operation.

[0041] In addition, technologies such as deep learning can be combined to analyze and compare user operations and extracted feature data to improve the accuracy of locating erroneous operations.

[0042] Step 104: Determine the first processing scheme for the first document based on the first feature data.

[0043] Specifically, by determining the first processing scheme for the first document based on the first feature data corresponding to the erroneous operation, and correcting the first document using the first processing scheme, the user's operating efficiency and data accuracy can be improved.

[0044] In addition, explainable artificial intelligence technology can be used to provide an interpretable description and explanation of the process of the first processing solution, thereby improving users' trust in and reliability of the system.

[0045] In the above embodiments of this application, by detecting the first position of abnormal data in the first document obtained after N operations on the second document of the shared document, and obtaining the feature dataset corresponding to the first position, the feature dataset is compared with the second document to determine the first feature data in the feature dataset that causes the data at the first position to be abnormal. Based on the first feature data, a first processing scheme for the first document is determined. That is, the position of the abnormal data in the first document (i.e., the first position) is first located. Since the feature dataset includes M feature data corresponding to the M operations from the second document to the first document at the first position, each feature data includes: the operating user, the operation content of the operating user, and the operation result. Therefore, based on the operating user, operation content, and operation result of each operation at the first position, it can be determined which erroneous operation caused the data abnormality, thus improving the accuracy of erroneous operation location. Furthermore, the feature data corresponding to the erroneous operation is determined as the first feature data. The first processing scheme for the first document is determined based on the specific first feature data. The first processing scheme is used to correct the first document, which can improve the user's operation efficiency and improve the accuracy of the data.

[0046] As an optional specific embodiment of step 104, determining the first processing scheme for the first document based on the first feature data may specifically include:

[0047] Obtain the data anomaly type to which the first feature data belongs;

[0048] Based on the first feature data and the data anomaly type, a first processing scheme is determined for the abnormal data at the first location in the first document.

[0049] Specifically, the data anomaly type corresponding to the first feature data of the erroneous operation is obtained. Based on the first feature data and the data anomaly type to which the first feature data belongs, a first processing scheme for the abnormal data at the first position in the first document is determined. The abnormal data at the first position in the first document is corrected through the first processing scheme, which can improve the user's operation efficiency and improve the accuracy of the data.

[0050] Furthermore, if both the second document and the first document are tables, then the data anomaly types can include, but are not limited to, the following four:

[0051] The first type is data anomalies where the unique, unadjustable characteristic changes; for example, the unique characteristic changes but remains unique; or the unique characteristic is missing; or the unique characteristic is duplicated, i.e., the unique characteristic loses its uniqueness, etc.

[0052] Among them, the owner of the shared document can customize certain features in the second document to be unadjustable. For example, if the shared document is a table, the owner can set the related formulas of multiple cells to be unadjustable and the unique features to be unadjustable (such as employee ID).

[0053] The second type is data anomalies caused by changes in related cells, such as changes in the related formulas of cells.

[0054] The third type: data anomalies caused by changes in cell format; for example, changes in date or text data.

[0055] In one specific embodiment, the first processing scheme may include:

[0056] Based on the target feature data of the target location in the first document and the data anomaly type, the operation content in the target feature data is corrected to obtain the correction operation result;

[0057] Determine whether the operation corresponding to the target feature data is the last operation at the target location;

[0058] If the operation is the last operation at the target location, the result of the correction operation is determined as the correct data corresponding to the target location in the first document;

[0059] Wherein, the target location includes the first location; when the target location includes the first location, the target feature data is the first feature data.

[0060] Specifically, the first feature data of the first position in the first document is obtained. Based on the first feature data of the first position in the first document and the data anomaly type to which the first feature data of the first position belongs, the erroneous operation content in the first feature data of the first position is corrected to obtain the correction operation result. Then, it is determined whether the operation corresponding to the first feature data is the Mth operation at the first position. If the operation is the Mth operation at the first position, it means that there are no other operations after the operation. The correction operation result is the correct data of the first position in the first document.

[0061] For the first document, the patterns in its rows and columns are extracted. The entire row and column data is treated as a complete data chain, and the corresponding feature data within each data chain is identified: cell format, formula matching and calculation, row number, column number, content, save time, etc. A detailed description follows:

[0062] For a first document with M rows and N columns, as shown in Table 1 below, the total number of cells in the table is t, namely P(1), P(2), ..., P(t). Since some cells may be merged, M*N is greater than or equal to t. Calculate the number of characters in each cell, the table width and height, and the total width and height X1*Y1 of the table.

[0063] Table 1

[0064] P(n+1) P(n+2) P(n+3) … … … … … … … … … … … P(t)

[0065] Each cell serves as a location within the document. The characteristic data corresponding to any cell includes, but is not limited to, the following: cell text content, font, font size, row width, column width, whether it is a merged cell and which cells it is merged from, which cell it is associated with in detail by a formula, and the detailed formula information of that association. The characteristic data of cells with formula associations are bound together to form an associated feature chain. For example, if P(1) is associated with P(i), the information of these two cells mutually supports each other to form an associated feature chain; if multiple cell features of P(1), P(i), and P(j) are associated, a multi-associated feature chain is formed, for example: T(P(1))○T(P(i))=T(P(j)), where T is a correlation function of a certain pattern, and ○ represents interaction, such as weighted interactions like addition, subtraction, multiplication, division, etc.

[0066] In another specific embodiment, the first processing scheme may further include:

[0067] If the operation is not the last operation at the target location, update the operation result of each operation after the operation at the target location based on the correction operation result;

[0068] The result of the last updated operation is determined as the correct data corresponding to the target location in the first document.

[0069] Specifically, if it is determined that the operation is not the Mth operation at the first position, it means that there are other operations after this operation. After obtaining the correction operation result, it is also necessary to update the operation result of each operation according to the operation order and the feature data corresponding to each operation after this operation, based on the correction operation result. The updated operation result corresponding to the Mth operation is used as the correct data of the first position in the first document. In this way, not only is the operation result of the erroneous operation corrected, but other correct operations are also preserved, which improves the accuracy of the data of the first position of the first document obtained in the end.

[0070] Additionally, it should be noted that if the operation involves multiple operations, it is processed in segments. The M operations are divided into multiple segments according to the operation, and each segment is corrected and updated in the manner described above. Then, the next segment is corrected and updated until the correct data for the first position of the first document is obtained.

[0071] For example, if M is 6, and this operation is the second and fourth operation, then the first and second operations are divided into the first segment, the third and fourth operations into the second segment, and the fifth and sixth operations into the third segment. In the first segment, the first operation is correct and requires no processing. The second operation is incorrect and needs to be corrected to obtain a corrected result, which serves as the final correct data for the first segment. Since the third operation is correct, it is performed based on the corrected result of the second operation, combined with the corresponding feature data, to obtain the third operation result. Since the fourth operation is incorrect, it needs to be corrected to obtain a corrected result, which serves as the final correct data for the second segment. Since the fifth operation is correct, the operation is performed based on the correction result of the fourth operation, combined with the feature data corresponding to the fifth operation, to obtain the result of the fifth operation. Since the sixth operation is correct, the operation is performed based on the result of the fifth operation, combined with the feature data corresponding to the sixth operation, to obtain the result of the sixth operation. This result of the sixth operation is the correct data for the first position of the first document.

[0072] As another optional specific embodiment of step 104, determining the first processing scheme for the first document based on the first feature data may further include:

[0073] Based on the first feature data and the data anomaly type, detect whether there is second feature data of the same data anomaly type as the first feature data in the second position other than the first position in the first document;

[0074] If so, then based on the processing scheme of the first feature data, determine the first processing scheme of the second feature data of the second position of the first document.

[0075] Specifically, based on the first feature data and the data anomaly type to which the first feature data belongs, it is detected whether there is any second feature data of the same data anomaly type as the first feature data in the second position of the first document. In other words, it is detected whether there is any erroneous operation content in the second position of the first document that is the same as the first position, with the same user, operation result, and data anomaly type. If there is no second feature data of the same data anomaly type in the second position of the first document, then only the first processing solution for the anomaly data in the first position of the first document needs to be determined. If there is second feature data of the same data anomaly type in the second position of the first document, then after determining the first processing solution for the anomaly data in the first position of the first document, the first processing solution for the anomaly data in the second position is determined based on the first processing solution for the anomaly data in the first position, thereby improving processing efficiency.

[0076] The first processing solution described above will be explained in detail below through specific embodiments, with both the second and first documents being tables:

[0077] For the first type of data anomaly, where the unique feature changes but remains unique, the feature data of the first position in the second document is obtained. By comparing the feature dataset of the first position in the first document with the feature data of the first position in the second document, it can be identified that the data anomaly is caused by the first feature data in the feature dataset. If the first feature data indicates that user D has modified the unique feature, the resulting operation result is abnormal. Therefore, it is necessary to correct the unique feature changed by user D based on the unique feature of the first position in the second document, obtain the correction operation result, and update the data at the first position in the first document based on the correction operation result. Furthermore, it is scanned to detect whether user D has modified the unique feature in other positions (i.e., the second position). If so, the first processing scheme for the second feature data of the second position is executed according to the first processing scheme for the first position in the first document, so as to modify the second feature data of the second position accordingly.

[0078] Furthermore, for the first type of data anomaly where unique features are missing or duplicated, the feature data of the first position in the second document is obtained. By comparing the feature dataset of the first position in the first document with the feature data of the first position in the second document, it can be identified that the data anomaly is caused by the first feature data in the feature dataset. If the first feature data indicates that user E performed a unique feature deletion operation, resulting in the unique feature missing at the first position, then the unique feature deleted by user E can be added either through forward calculation or through reverse calculation to obtain a correction result. The data at the first position in the first document is then updated based on the correction result. Additionally, it is scanned to detect whether user E performed a unique feature deletion operation at the second position. If so, the first processing scheme for the second feature data at the second position is executed according to the first processing scheme for the first position in the first document to modify the second feature data at the second position accordingly.

[0079] The forward calculation method involves resimulating the operation process from the first position in the second document to the first position in the first document, and using the calculated result as the latest missing value to supplement it.

[0080] The reverse calculation method is as follows: If there is a formula related to the first position and multiple cells, the specific result of the cell in the first position can be calculated in reverse using the information of other cells. For example, if two of them are known in (T(P(1))○T(P(i))=T(P(j))), the other one can be calculated. The result of the reverse calculation is used as the latest missing value to supplement it.

[0081] For the second type of data anomaly, the feature data of the first position in the second document is obtained. By comparing the feature dataset of the first position in the first document with the feature data of the first position in the second document, the data anomaly caused by the first feature data in the feature dataset can be identified. If the first feature data indicates that user F has changed the association feature formula, then the association feature formula changed by user F is corrected according to the association feature formula of the first position in the second document, and the calculation result is refreshed to obtain the correction operation result. The data at the first position in the first document is updated based on the correction operation result. Furthermore, the system scans to detect whether user F has changed the association feature formula in other positions. If so, the first processing scheme for the second feature data of the second position is executed according to the first processing scheme for the first position in the first document to modify the second feature data of the second position accordingly.

[0082] For the third type of data anomaly, the feature data of the first position in the second document is obtained. By comparing the feature dataset of the first position in the first document with the feature data of the first position in the second document, the data anomaly caused by the first feature data in the feature dataset can be identified. If the first feature data indicates that user G has changed the data format, the changed data format of user G is corrected according to the data format of the first position in the second document. For example, the format painter is used to refresh the changed data format of user G to the data format of the second document, thus obtaining the correction operation result. The data at the first position in the first document is updated based on the correction operation result. Furthermore, the scan detects whether user G has changed the data format at the second position. If so, the first processing scheme for the second feature data at the second position is executed according to the first processing scheme for the first position in the first document to modify the second feature data at the second position accordingly.

[0083] In one specific embodiment, the first processing scheme may include:

[0084] Based on the target feature data of the target location in the first document and the data anomaly type, the operation content in the target feature data is corrected to obtain the correction operation result;

[0085] Determine whether the operation corresponding to the target feature data is the last operation at the target location;

[0086] If the operation is the last operation at the target location, the result of the correction operation is determined as the correct data corresponding to the target location in the first document;

[0087] Wherein, the target location includes the second location; and when the target location includes the second location, the target feature data is the second feature data.

[0088] Specifically, the second feature data of the second position in the first document is obtained. Based on the second feature data of the second position in the first document and the data anomaly type to which the second feature data of the second position belongs, the erroneous operation content in the second feature data of the second position is corrected to obtain the correction operation result. Then, it is determined whether the operation corresponding to the second feature data is the last operation at the second position. If the operation is the last operation at the second position, it means that there are no other operations after this operation. The correction operation result is the correct data of the second position in the first document.

[0089] In another specific embodiment, the first processing scheme may further include:

[0090] If the operation is not the last operation at the target location, update the operation result of each operation after the operation at the target location based on the correction operation result;

[0091] The result of the last updated operation is determined as the correct data corresponding to the target location in the first document.

[0092] Specifically, if it is determined that the operation is not the last operation in the first position, it means that there are other operations after this operation. After obtaining the correction operation result, it is also necessary to update the operation result of each operation according to the operation order and the feature data corresponding to each operation after this operation, based on the correction operation result. The updated operation result corresponding to the last operation is used as the correct data in the second position of the first document. In this way, not only is the operation result of the erroneous operation corrected, but other correct operations are also preserved, which improves the accuracy of the data in the second position of the first document obtained in the end.

[0093] Additionally, it should be noted that if the operation involves multiple operations, it is processed in segments. All operations at the second position are divided into multiple segments according to the operation, and each segment is corrected and updated in the manner described above. Then, the next segment is corrected and updated until the correct data at the second position of the first document is obtained.

[0094] For example, if the total number of operations for the second position is 6, and this operation includes the second and fourth operations, then the first operation is divided into the first segment, the second and third operations into the second segment, and the fourth, fifth, and sixth operations into the third segment. In the first segment, the first operation is correct and requires no processing; its result is the final correct data for the first segment. Since the second operation is incorrect, its content needs to be corrected to obtain a corrected result. Since the third operation is correct, based on the corrected result of the second operation and combined with the corresponding feature data, the third operation result is used as the final correct data for the second segment. Since the fourth operation was incorrect, it needs to be corrected to obtain the corrected result. Since the fifth operation was correct, it is performed based on the corrected result of the fourth operation, combined with the feature data corresponding to the fifth operation, to obtain the result of the fifth operation. Since the sixth operation was correct, it is performed based on the result of the fifth operation, combined with the feature data corresponding to the sixth operation, to obtain the result of the sixth operation. This result of the sixth operation is the correct data for the second position of the first document.

[0095] As an optional specific embodiment, after determining the first processing scheme for the first document based on the first feature data in step 104, the method may further include:

[0096] Obtain S second processing schemes for the first document from S users, where S is a positive integer;

[0097] The second processing scheme and the first processing scheme are combined to obtain the target processing scheme;

[0098] The first document is processed using the target processing scheme.

[0099] Specifically, the second processing solutions of S users for the first document are obtained, and the second processing solutions of the S users are merged with the first processing solution to obtain the final target processing solution. The first document is processed through the target processing solution, which not only improves the accuracy of the corrected data, but also meets the needs of the users.

[0100] In addition, after obtaining the target processing solution, the solution can be designated as a solution to be confirmed by the user. Only after the user confirms the solution can the first document be processed. This can further meet the customer's needs and further improve the accuracy of the corrected data.

[0101] It should be noted that the system can automatically record and save information such as the target processing scheme, correction time, correction type, and correction result for each data correction, allowing users to view and trace it at any time. Furthermore, when recording the correction process, the historical records can be sorted according to user priority and weight.

[0102] Furthermore, when S is greater than 1, the step of obtaining the second processing scheme for the first document from S users can specifically include:

[0103] Obtain the third processing plan for the first document for each of the S users;

[0104] Based on the S third processing schemes, the priorities of the S users, and their corresponding weights, the second processing schemes for the first document by the S users are determined.

[0105] Specifically, when one user discovers abnormal data in the first document, they can mark the abnormal data through collaborative repair and provide a third-party solution for repair. Users can directly mark the abnormal data in the first document and add corresponding comments or explanations to help other users understand. Other users can view the abnormal data markings through collaborative repair and provide third-party solutions or assistance in processing the data. Users can directly reply to other users' third-party solutions in the first document and provide corresponding modifications or replacements. The third-party solutions from S users are integrated to obtain a second-party solution. During the integration process, the most suitable second-party solution can be determined based on the priority and weight of different users.

[0106] In addition, speech recognition and voice interaction technologies can be combined to process data through voice input and voice feedback, making it easier for users to collaborate and share documents.

[0107] In another specific embodiment, customization features can be added according to user needs. That is, users can customize their own rules and styles for handling abnormal data according to their own needs and habits, including but not limited to: font, font size, color, alignment, etc.

[0108] Based on different users' processing rules and styles, the system automatically analyzes and processes abnormal data in the first document, providing corresponding third-party processing solutions. Through this customization feature, users can quickly convert the style of shared documents to their desired style and ultimately achieve a unified style adjustment. Users can choose their preferred style template or create a custom style template for rapid style conversion and unification.

[0109] like Figure 2 As shown, the above-mentioned customization and standardization are illustrated below through a specific embodiment:

[0110] Step 201: Perform abnormal data processing on the first document using the first processing scheme.

[0111] Step 202: Determine if customization is needed; if so, proceed to step 203; if not, end the process.

[0112] Step 203: Customize the first document.

[0113] Step 204: After the customization process, determine the unified style template.

[0114] Specifically, users can choose their desired style template from a variety of preset templates, or they can customize their own style templates for quick style switching and consistency adjustments. In particular, users can select style templates for fonts, font sizes, colors, alignment, and other aspects, and apply them to their first document.

[0115] Step 205: Adjust the style of the first document according to the unified style template to ensure the overall style consistency of the first document.

[0116] It should be noted that the shared document processing system can automatically apply various elements from the first document, such as text, images, and tables, to a unified style template.

[0117] For text, the system automatically analyzes its content and location, identifying and applying appropriate fonts, sizes, colors, alignment, and other styles. Simultaneously, it automatically adjusts styles based on the user-selected template to ensure consistency in text style.

[0118] For images, the system automatically analyzes the image content and its location, identifying and applying appropriate styles, such as image size, border style, and alignment. Simultaneously, it automatically adjusts styles based on the user-selected style template to ensure consistency in image style.

[0119] For tables, the system automatically analyzes the table content and its location to identify and apply appropriate styles, such as table borders, font, font size, color, and alignment. It can also automatically adjust styles based on the user-selected style template to ensure consistency in table style.

[0120] Additionally, when applying a unified style template, the priority of style adjustments for various elements should be considered. For example, when an element is affected by multiple style adjustments simultaneously, adjustments should be made according to priority to ensure the correctness and consistency of the style adjustments.

[0121] When applying a unified style template, consider the ability to undo and redo style adjustments. For example, after a user modifies the style of an element, the style adjustment should be automatically undone or redoed to ensure its correctness and consistency.

[0122] Furthermore, the shared document processing system can automatically adjust various elements in the first document in batches, including text, images, tables, etc., based on the style template selected by the user, to ensure the overall style consistency of the first document.

[0123] In summary, the embodiments of this application, which locate the location of data anomalies in the first document (i.e., the first position), utilize a feature dataset comprising M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user performing the operation, the content of the operation performed by the user, and the result of the operation. Therefore, based on the user performing the operation, the content of the operation, and the result of each operation at the first position, it can be determined which erroneous operation caused the data anomaly, improving the accuracy of erroneous operation location. Furthermore, by determining the feature data corresponding to this erroneous operation as the first feature data, and using this specific first feature data to determine a first processing scheme for the first document, the first document can be corrected, improving user operation efficiency and data accuracy. Moreover, the customized and unified functional settings can meet the needs and habits of different users. Furthermore, the unified style adjustment ensures the overall style consistency of shared documents.

[0124] The shared document processing method provided in this application can be executed by a shared document processing device. This application uses the example of a shared document processing device executing the shared document processing method to illustrate the shared document processing device provided in this application.

[0125] like Figure 3 As shown in the illustration, this application also provides a shared document processing apparatus 300, including:

[0126] Detection module 301 is used to detect the first position where abnormal data is located in the first document, where the first document represents the document obtained after the second document of the shared document has been processed by N operations, where N is a positive integer;

[0127] The first acquisition module 302 is used to acquire the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations that the first position goes through from the second document to the first document. Each feature data includes: the operating user, the operation content of the operating user, and the operation result. M is a positive integer less than or equal to N.

[0128] The first determining module 303 is used to compare the feature dataset with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal;

[0129] The second determining module 304 is used to determine a first processing scheme for the first document based on the first feature data.

[0130] In the above embodiment, by detecting the first position of abnormal data in the first document obtained after N operations on the second document of the shared document, and obtaining the feature dataset corresponding to the first position, the feature dataset is compared with the second document to determine the first feature data in the feature dataset that causes the data at the first position to be abnormal. Based on the first feature data, a first processing scheme for the first document is determined. That is, the position of the abnormal data in the first document (i.e., the first position) is first located. Since the feature dataset includes M feature data corresponding to the M operations from the second document to the first document at the first position, each feature data includes: the operating user, the operation content of the operating user, and the operation result. Therefore, based on the operating user, operation content, and operation result of each operation at the first position, it can be determined which erroneous operation caused the data abnormality, improving the accuracy of erroneous operation location. Furthermore, the feature data corresponding to the erroneous operation is determined as the first feature data. The first processing scheme for the first document is determined based on the specific first feature data. The first processing scheme is used to correct the first document, which can improve the user's operation efficiency and improve the accuracy of the data.

[0131] Optionally, the second determining module 304 is specifically used for:

[0132] Obtain the data anomaly type to which the first feature data belongs;

[0133] Based on the first feature data and the data anomaly type, a first processing scheme is determined for the abnormal data at the first location in the first document.

[0134] Optionally, the second determining module 304 is further configured to:

[0135] Based on the first feature data and the data anomaly type, detect whether there is second feature data of the same data anomaly type as the first feature data in the second position other than the first position in the first document;

[0136] If so, then based on the processing scheme of the first feature data, determine the first processing scheme of the second feature data of the second position of the first document.

[0137] Optionally, the first processing scheme includes:

[0138] Based on the target feature data of the target location in the first document and the data anomaly type, the operation content in the target feature data is corrected to obtain the correction operation result;

[0139] Determine whether the operation corresponding to the target feature data is the last operation at the target location;

[0140] If the operation is the last operation at the target location, the result of the correction operation is determined as the correct data corresponding to the target location in the first document;

[0141] The target location includes at least one of the first location and the second location; when the target location includes the first location, the target feature data is the first feature data; when the target location includes the second location, the target feature data is the second feature data.

[0142] Optionally, the first processing scheme further includes:

[0143] If the operation is not the last operation at the target location, update the operation result of each operation after the operation at the target location based on the correction operation result;

[0144] The result of the last updated operation is determined as the correct data corresponding to the target location in the first document.

[0145] Optionally, the device further includes:

[0146] The second acquisition module is used to acquire S users' second processing schemes for the first document, where S is a positive integer;

[0147] The first processing module is used to merge the second processing scheme with the first processing scheme to obtain the target processing scheme;

[0148] The second processing module is used to process the first document using the target processing scheme.

[0149] Optionally, when S is greater than 1, the second acquisition module is specifically used for:

[0150] Obtain the third processing plan for the first document for each of the S users;

[0151] Based on the S third processing schemes, the priorities of the S users, and their corresponding weights, the second processing schemes for the first document by the S users are determined.

[0152] In summary, the embodiments of this application locate the location of data anomalies (i.e., the first position) in the first document. Since the feature dataset includes M feature data corresponding to the M operations performed from the second document to the first document at the first position, and each feature data includes: the operating user, the operation content of the operating user, and the operation result, it is possible to determine which erroneous operation caused the data anomaly based on the operating user, operation content, and operation result of each operation at the first position, thus improving the accuracy of erroneous operation location. Furthermore, by determining the feature data corresponding to this erroneous operation as the first feature data, and using this specific first feature data to determine the first processing scheme for the first document, the first document can be corrected, improving user operation efficiency and data accuracy. Moreover, the customized and unified functional settings can meet the needs and habits of different users. Furthermore, the unified style adjustment can ensure the overall style consistency of shared documents.

[0153] The document sharing processing device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0154] The document processing device in this application embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this application embodiment does not specifically limit the specific operating system used.

[0155] The shared document processing apparatus provided in this application embodiment can achieve Figures 1 to 2 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0156] Optionally, such as Figure 4 As shown, this application embodiment also provides an electronic device 400, including a processor 401 and a memory 402. The memory 402 stores a program or instructions that can run on the processor 401. When the program or instructions are executed by the processor 401, they implement the various steps of the above-described shared document processing method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0157] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0158] Figure 5 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0159] The electronic device 1000 includes, but is not limited to, components such as: radio frequency unit 1001, network module 1002, audio output unit 1003, input unit 1004, sensor 1005, display unit 1006, user input unit 1007, interface unit 1008, memory 1009, and processor 1010.

[0160] Those skilled in the art will understand that the electronic device 1000 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 1010 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 5 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0161] The processor 1010 is used to detect the first position where abnormal data is located in the first document, where the first document represents the document obtained after the second document of the shared document has been processed by N operations, and N is a positive integer.

[0162] Obtain the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user of the operation, the operation content of the user, and the operation result. M is a positive integer less than or equal to N.

[0163] The feature dataset is compared with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal;

[0164] Based on the first feature data, a first processing scheme for the first document is determined.

[0165] In the above embodiments of this application, by detecting the first position of abnormal data in the first document obtained after N operations on the second document of the shared document, and obtaining the feature dataset corresponding to the first position, the feature dataset is compared with the second document to determine the first feature data in the feature dataset that causes the data at the first position to be abnormal. Based on the first feature data, a first processing scheme for the first document is determined. That is, the position of the abnormal data in the first document (i.e., the first position) is first located. Since the feature dataset includes M feature data corresponding to the M operations from the second document to the first document at the first position, each feature data includes: the operating user, the operation content of the operating user, and the operation result. Therefore, based on the operating user, operation content, and operation result of each operation at the first position, it can be determined which erroneous operation caused the data abnormality, thus improving the accuracy of erroneous operation location. Furthermore, the feature data corresponding to the erroneous operation is determined as the first feature data. The first processing scheme for the first document is determined based on the specific first feature data. The first processing scheme is used to correct the first document, which can improve the user's operation efficiency and improve the accuracy of the data.

[0166] Optionally, when determining the first processing scheme for the first document based on the first feature data, the processor 1010 is specifically used for:

[0167] Obtain the data anomaly type to which the first feature data belongs;

[0168] Based on the first feature data and the data anomaly type, a first processing scheme is determined for the abnormal data at the first location in the first document.

[0169] Optionally, when determining the first processing scheme for the first document based on the first feature data, the processor 1010 is further configured to:

[0170] Based on the first feature data and the data anomaly type, detect whether there is second feature data of the same data anomaly type as the first feature data in the second position other than the first position in the first document;

[0171] If so, then based on the processing scheme of the first feature data, determine the first processing scheme of the second feature data of the second position of the first document.

[0172] Optionally, the first processing scheme includes:

[0173] Based on the target feature data of the target location in the first document and the data anomaly type, the operation content in the target feature data is corrected to obtain the correction operation result;

[0174] Determine whether the operation corresponding to the target feature data is the last operation at the target location;

[0175] If the operation is the last operation at the target location, the result of the correction operation is determined as the correct data corresponding to the target location in the first document;

[0176] The target location includes at least one of the first location and the second location; when the target location includes the first location, the target feature data is the first feature data; when the target location includes the second location, the target feature data is the second feature data.

[0177] Optionally, the first processing scheme further includes:

[0178] If the operation is not the last operation at the target location, update the operation result of each operation after the operation at the target location based on the correction operation result;

[0179] The result of the last updated operation is determined as the correct data corresponding to the target location in the first document.

[0180] Optionally, after determining the first processing scheme for the first document based on the first feature data, the processor 1010 is further configured to:

[0181] Obtain S second processing schemes for the first document from S users, where S is a positive integer;

[0182] The second processing scheme and the first processing scheme are combined to obtain the target processing scheme;

[0183] The first document is processed using the target processing scheme.

[0184] Optionally, when S is greater than 1, the processor 1010, when acquiring the second processing schemes for the first document from S users, specifically performs the following:

[0185] Obtain the third processing plan for the first document for each of the S users;

[0186] Based on the S third processing schemes, the priorities of the S users, and their corresponding weights, the second processing schemes for the first document by the S users are determined.

[0187] In summary, the embodiments of this application, which locate the location of data anomalies in the first document (i.e., the first position), utilize a feature dataset comprising M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user performing the operation, the content of the operation performed by the user, and the result of the operation. Therefore, based on the user performing the operation, the content of the operation, and the result of each operation at the first position, it can be determined which erroneous operation caused the data anomaly, improving the accuracy of erroneous operation location. Furthermore, by determining the feature data corresponding to this erroneous operation as the first feature data, and using this specific first feature data to determine a first processing scheme for the first document, the first document can be corrected, improving user operation efficiency and data accuracy. Moreover, the customized and unified functional settings can meet the needs and habits of different users. Furthermore, the unified style adjustment ensures the overall style consistency of shared documents.

[0188] It should be understood that, in this embodiment, the input unit 1004 may include a graphics processing unit (GPU) 10041 and a microphone 10042. The GPU 10041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 1006 may include a display panel 10061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 1007 includes a touch panel 10071 and at least one of other input devices 10072. The touch panel 10071 is also called a touch screen. The touch panel 10071 may include a touch detection device and a touch controller. Other input devices 10072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here.

[0189] The memory 1009 can be used to store software programs and various data. The memory 1009 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 1009 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 1009 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0190] The processor 1010 may include one or more processing units; optionally, the processor 1010 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into the processor 1010.

[0191] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described shared document processing method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0192] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0193] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described shared document processing method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0194] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0195] This application provides a computer program product that is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described shared document processing method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0196] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0197] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0198] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for processing shared documents, characterized in that, include: The first position where abnormal data is detected in the first document is represented. The first document is a document obtained after N operations on the second document of the shared document, where N is a positive integer. Obtain the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations performed from the second document to the first document at the first position. Each feature data includes: the user of the operation, the operation content of the user, and the operation result. M is a positive integer less than or equal to N. The feature dataset is compared with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal; Based on the first feature data, a first processing scheme for the first document is determined.

2. The method according to claim 1, characterized in that, The step of determining the first processing scheme for the first document based on the first feature data includes: Obtain the data anomaly type to which the first feature data belongs; Based on the first feature data and the data anomaly type, a first processing scheme is determined for the abnormal data at the first location in the first document.

3. The method according to claim 2, characterized in that, The step of determining the first processing scheme for the first document based on the first feature data further includes: Based on the first feature data and the data anomaly type, detect whether there is second feature data of the same data anomaly type as the first feature data in the second position other than the first position in the first document; If so, then based on the processing scheme of the first feature data, determine the first processing scheme of the second feature data of the second position of the first document.

4. The method according to claim 3, characterized in that, The first processing solution includes: Based on the target feature data of the target location in the first document and the data anomaly type, the operation content in the target feature data is corrected to obtain the correction operation result; Determine whether the operation corresponding to the target feature data is the last operation at the target location; If the operation is the last operation at the target location, the result of the correction operation is determined as the correct data corresponding to the target location in the first document; The target location includes at least one of the first location and the second location; when the target location includes the first location, the target feature data is the first feature data; when the target location includes the second location, the target feature data is the second feature data.

5. The method according to claim 4, characterized in that, The first processing solution also includes: If the operation is not the last operation at the target location, update the operation result of each operation after the operation at the target location based on the correction operation result; The result of the last updated operation is determined as the correct data corresponding to the target location in the first document.

6. The method according to claim 4, characterized in that, After determining the first processing scheme for the first document based on the first feature data, the method further includes: Obtain S second processing schemes for the first document from S users, where S is a positive integer; The second processing scheme and the first processing scheme are combined to obtain the target processing scheme; The first document is processed using the target processing scheme.

7. The method according to claim 6, characterized in that, When S is greater than 1, the second processing scheme for obtaining S users' views on the first document includes: Obtain the third processing plan for the first document for each of the S users; Based on the S third processing schemes, the priorities of the S users, and their corresponding weights, the second processing schemes for the first document by the S users are determined.

8. A shared document processing apparatus, characterized in that, include: The detection module is used to detect the first position where abnormal data is located in the first document, where the first document represents the document obtained after N operations on the second document of the shared document, where N is a positive integer; The first acquisition module is used to acquire the feature dataset corresponding to the first position. The feature dataset includes M feature data corresponding to the M operations that the first position goes through from the second document to the first document. Each feature data includes: the operating user, the operation content of the operating user, and the operation result. M is a positive integer less than or equal to N. The first determining module is used to compare the feature dataset with the second document to determine the first feature data in the feature dataset that makes the data at the first position abnormal; The second determining module is used to determine a first processing scheme for the first document based on the first feature data.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a program or instructions that can run on the processor, the program or instructions being executed by the processor to implement the steps of the shared document processing method as described in any one of claims 1-7.

10. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the shared document processing method as described in any one of claims 1-7.

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