Cooperative office data processing method and device

Abstract

The invention discloses a collaborative office data processing method and device, and relates to the technical field of collaborative office, and the method comprises the steps: receiving form data; identifying a plurality of entities and relationships among the entities based on the form data; establishing a graph structure by taking the form version identifier and the plurality of entities as nodes and taking the relationship between the entities as edges; monitoring whether each table cell of the form is selected or not, and locking a first table cell when the first table cell is selected; receiving data transmitted by the first cell, associating the first cell with a first entity in the graph structure according to the rank of the first cell and the rank of the entity, and configuring the data transmitted by the first cell as the attribute of the first entity to obtain an updated graph structure; when the first cell is cancelled to be selected, the first cell is unlocked, and data transmitted by the first cell is displayed in the form; and storing the updated graph structure in a graph database. According to the invention, effective utilization of collaborative office data can be improved.

Description

Technical Field

[0001] The present invention relates to the field of collaborative office technology, and in particular to a collaborative office data processing method and device. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention recited in the claims. No admission is made that the description herein is prior art by inclusion in this section.

[0003] Collaborative office refers to the integration of multiple office functions and resources to achieve efficient information sharing, communication and collaboration, and business process management among team members. In a collaborative office environment, multiple people can modify and improve a document at the same time, and each person's job responsibilities and progress requirements can be clearly defined to ensure the smooth progress of the project.

[0004] In the existing technology, employees input collaborative office data at the front end, and the back end usually stores the collaborative office data directly in a document-type database after receiving the collaborative office data. However, collaborative office data contains a large amount of knowledge and experience. Documents, discussion records, project summaries and other data are all valuable knowledge assets of the enterprise. Storing them in a document-type database will make it difficult to continue to mine useful information from the collaborative office data later. Summary of the invention

[0005] The embodiment of the present invention provides a collaborative office data processing method for optimizing the storage process of collaborative office data, improving the effective use of collaborative office data, and reducing the difficulty of subsequent mining of collaborative office data. The method includes:

[0006] Receive form data and create a form version identifier for the form data; the form data includes table row and column data and characters filled in the form;

[0007] Perform semantic recognition on form data to obtain multiple entities, relationships between entities, and rows and columns in which entities are located;

[0008] A graph structure is established with form version identifiers and multiple entities as nodes, and with the relationships between form version identifiers and entities, and the relationships between entities as edges;

[0009] Monitor whether each cell in the form is selected. When the first cell is selected, lock the first cell.

[0010] Receive data transmitted by the first cell, associate the first cell with the first entity in the graph structure according to the row and column where the first cell is located and the row and column where the entity is located, configure the data transmitted by the first cell as an attribute of the first entity, and obtain an updated graph structure;

[0011] When the first cell is unselected, unlock the first cell and display the data transmitted by the first cell in the form;

[0012] The updated graph structure is stored in the graph database.

[0013] In one embodiment, receiving form data includes: receiving form data filled in according to a preset form template; the preset form template corresponds to a collaborative office data type; the collaborative office data type includes one or any combination of the following:

[0014] Document data type, communication data type, task data type, process data type.

[0015] In one embodiment, semantic recognition is performed on form data to obtain multiple entities, relationships between entities, and rows and columns in which the entities are located, including: based on table row and column data and characters filled in the table, determining the row and column in which the second cell in which the characters are filled in is located; performing semantic recognition on the characters filled in each second cell to obtain multiple entities; each entity carries the row and column in which the second cell is located; based on a machine learning algorithm, performing relationship extraction processing on all entities to obtain relationships between entities.

[0016] In one embodiment, establishing a graph structure includes: adding one or any combination of the following attributes to a node:

[0017] Permission attributes, time attributes, geographic location attributes, lock status attributes, and security attributes; the permission attributes include node access restriction information, the time attributes include node status change time point information, and the security attributes include node encryption information.

[0018] In one embodiment, monitoring whether each cell of the form is selected includes: monitoring whether each cell of the form is selected based on a long connection communication mode.

[0019] In one embodiment, after storing the updated graph structure in the graph database, the method further includes: identifying multiple nodes whose degree centrality values ​​are higher than a preset value in the updated graph structure through a centrality measurement algorithm, and printing key information identifiers for the multiple nodes higher than the preset value.

[0020] In one embodiment, the graph database includes a plurality of graph structures;

[0021] After printing the identification of key information for multiple nodes higher than the preset value, the method also includes: using a community detection algorithm to unify the entity identifiers of the graph structure in the graph database to obtain multiple graph structures with unified identifications; merging the multiple graph structures with unified identifications to obtain an integrated graph database.

[0022] The embodiment of the present invention further provides a collaborative office data processing device, which is used to optimize the storage process of collaborative office data, improve the effective use of collaborative office data, and reduce the difficulty of subsequent mining of collaborative office data. The device includes:

[0023] An initial processing module, used to receive form data and establish a form version identifier for the form data; the form data includes table row and column data and characters filled in the table;

[0024] The graph structure building module is used to perform semantic recognition on the form data to obtain multiple entities, the relationships between entities, and the rows and columns in which the entities are located; the graph structure is built with the form version identifier and multiple entities as nodes and the relationships between entities as edges;

[0025] A monitoring module is used to monitor whether each cell of the form is selected, and when the first cell is selected, the first cell is locked;

[0026] A graph structure updating module, configured to receive data transmitted by a first cell, associate the first cell with a first entity in the graph structure according to a row and column where the first cell is located and a row and column where the entity is located, configure the data transmitted by the first cell as an attribute of the first entity, and obtain an updated graph structure;

[0027] The monitoring module is further used to unlock the first cell when the first cell is unselected, and display the data transmitted by the first cell in the form;

[0028] The graph database storage module is used to store the updated graph structure in the graph database.

[0029] An embodiment of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned collaborative office data processing method when executing the computer program.

[0030] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the collaborative office data processing method described above is implemented.

[0031] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the collaborative office data processing method is implemented.

[0032] In the embodiment of the present invention, multiple entities and relationships between entities are identified based on the form data of collaborative office, thereby establishing a graph structure, and storing the data input by collaborative office employees as node attributes in the graph structure, thereby realizing graph structure storage of collaborative office data. Compared with the prior art of directly storing in a document-type database, the storage process of the collaborative office data is optimized, and finally the collaborative office data is stored in a graph database. Compared with a document-type database, a graph database can support faster query speeds and more effective data analysis capabilities. This method improves the effective use of collaborative office data and reduces the difficulty of subsequent mining of collaborative office data by storing the collaborative office data in a graph database. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0034] Figure 1 Schematic diagram of the process of collaborative office data processing method in an embodiment of the present invention;

[0035] Figure 2 A diagram showing a specific example of a collaborative office data processing method according to an embodiment of the present invention;

[0036] Figure 3 FIG. 2 is another specific example diagram of the collaborative office data processing method in an embodiment of the present invention;

[0037] Figure 4 is a schematic diagram of a collaborative office data processing device in an embodiment of the present invention;

[0038] Figure 5 Schematic diagram of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0039] To make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0040] The acquisition, transmission, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0041] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0042] Figure 1 FIG. 1 is a flow chart of a collaborative office data processing method according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0043] Step 101: receiving form data and establishing a form version identifier for the form data; the form data includes table row and column data and characters filled in the form;

[0044] Step 102: semantically identify the form data to obtain multiple entities, relationships between entities, and rows and columns where the entities are located;

[0045] Step 103: Establish a graph structure with the form version identifier and multiple entities as nodes, and the relationship between the form version identifier and the entity, and the relationship between the entities as edges;

[0046] Step 104: monitor whether each cell of the form is selected, and when the first cell is selected, lock the first cell;

[0047] Step 105: receiving data transmitted by the first cell, associating the first cell with the first entity in the graph structure according to the row and column where the first cell is located and the row and column where the entity is located, configuring the data transmitted by the first cell as an attribute of the first entity, and obtaining an updated graph structure;

[0048] Step 106: When the first cell is unselected, unlock the first cell and display the data transmitted by the first cell in the form;

[0049] Step 107: Store the updated graph structure in the graph database.

[0050] from Figure 1 It can be seen from the shown process that in the embodiment of the present invention, multiple entities and relationships between entities are identified based on the form data of collaborative office, thereby establishing a graph structure, and storing the data input by collaborative office employees as node attributes in the graph structure, thereby realizing graph structure storage of collaborative office data. Compared with the prior art of directly storing it in a document-type database, the storage process of the collaborative office data is optimized, and finally the collaborative office data is stored in a graph database. Compared with a document-type database, a graph database can support faster query speeds and more effective data analysis capabilities. This method improves the efficient use of collaborative office data and reduces the difficulty of subsequent mining of collaborative office data by storing the collaborative office data in a graph database.

[0051] Below Figure 1 Each step is explained in detail.

[0052] Figure 1 The method in this section can be understood as a server-side implementation. When this method is implemented, the user administrator independently creates the form filling content on the front end, fills in the list of filling personnel, and sends the task to each filling personnel. The server receives the form data, which at least includes the table structure such as the table row and column data, and the characters filled in the table, such as the name of the filling personnel, department, filling content requirements, etc.

[0053] In one embodiment, considering that there are many types of collaborative office data, the collaborative office data types include at least one or any combination of the following:

[0054] Document data type, communication data type, task data type, process data type.

[0055] Document data types include various office documents, such as Word, Excel, PowerPoint and other files. These documents may contain project plans, reports, data analysis and other content. Document data is usually created, edited and shared by employees in the process of collaborative office work.

[0056] Communication data types (sales orders, purchase orders, etc.) include emails, instant messaging records, video conference records, etc. These data reflect the communication between employees, including work arrangements, problem discussions, decision-making processes, etc. For example, the subject, sender, recipient, text content, and attachments in an email are all part of the communication data.

[0057] The task data type contains information such as task assignment, progress tracking, and completion status. In collaborative office work, task management tools are often used to assign tasks, set deadlines, and track the progress of tasks. Task data can help team members understand their own and others' work tasks and improve work efficiency. For example, a project task assignment form.

[0058] The process data type involves the execution of various business processes, such as approval process, reimbursement process, etc. The process data records the processing time, processor, approval opinions and other information of each link. This data can be used to optimize business processes and improve the efficiency and transparency of the process. For example, invoice verification form, payment confirmation form, leave, reimbursement application form, contract approval form, etc.

[0059] In one embodiment, a preset form template is created in advance for each collaborative office data type, and the user administrator can directly obtain a suitable preset form template and input data as required.

[0060] Step 101 of receiving form data may include: receiving form data filled in according to a preset form template; the preset form template corresponds to the collaborative office data type.

[0061] When creating a preset form template, it is necessary to generate multiple requirement data based on the requirements of each department for collaborative office, and generate a preset form template by integrating multiple requirement data. The requirement data may include the timing of collaborative processing, field filling requirements, data transmission confidentiality requirements, etc.

[0062] Then, in step 102, semantic recognition is performed on the form data to obtain multiple entities, relationships between entities, and rows and columns where the entities are located.

[0063] For example, the acquired data is first preprocessed, and then based on natural language recognition, multiple entities, relationships between entities, and the rows and columns in which the entities are located are obtained.

[0064] For example, in an employee data form, "employee" can be regarded as an entity, and each employee has attributes such as name and employee number.

[0065] Figure 2 FIG. 1 is a specific example diagram of a collaborative office data processing method according to an embodiment of the present invention. Figure 2 As shown, semantic recognition is performed on the form data to obtain multiple entities, relationships between entities, and rows and columns where the entities are located, which may include:

[0066] Step 201, based on the table row and column data and the characters filled in the table, determine the row and column where the second cell filled in with the characters is located;

[0067] Step 202: semantically recognize the characters filled in each second cell to obtain multiple entities; each entity carries the row and column where the second cell is located;

[0068] Step 203: Based on the machine learning algorithm, perform relationship extraction on all entities to obtain the relationships between entities.

[0069] During implementation, determine which cells have been filled with characters, and semantically identify the meaning of the characters filled in each cell filled with characters in turn. Keywords can be identified based on a pre-established dictionary to determine entities. In the embodiment of the present invention, entities include user identifiers, such as the name of the person filling in the form. Afterwards, perform relationship extraction on all entities to obtain relationships between entities.

[0070] When performing relationship extraction based on machine learning algorithms, models can be trained to identify entity pairs and their relationships in text, which usually involves feature engineering, model training, evaluation, and tuning.

[0071] In order to reduce workload and improve processing efficiency, predefined rule templates can also be used to match entities and relationships in texts. For example, relationships can be clarified through keywords such as "located in", "founder", and "belong to".

[0072] In step 103, a graph structure is established with the form version identifier and multiple entities as nodes, and the relationship between the form version identifier and the entity, and the relationship between the entities as edges. This step implements temporary storage of the collaborative office form data in a graph structure.

[0073] In one embodiment, establishing a graph structure may include: adding one or any combination of the following attributes to a node:

[0074] Permission attributes, time attributes, geographic location attributes, lock status attributes, and security attributes.

[0075] The permission attribute includes node access restriction information, such as who can access the node, who can modify the node, etc. The time attribute includes the node status change time point information, which is used to record the node status change time point, such as creation time, last modification time, etc. The geographic location attribute includes the geographic location and IP address of the person filling in the node. The lock status attribute includes whether the node is locked or unlocked. The security attribute includes the encryption information of the node, such as encryption key, hash value, etc.

[0076] Then in step 104, it is monitored whether each cell of the sheet is selected, and when the first cell is selected, the first cell is locked.

[0077] It should be noted that in the embodiments of the present invention, "first" and "second" do not have special meanings, but are simply used to distinguish different cells to make the description clear.

[0078] In the embodiment of the present invention, the front end can be developed by using JavaScript combined with HTML5 to develop the front end page, and the server can be written in languages ​​such as Node.js or Java, and use the WebSocket framework (such as Socket.IO) to achieve real-time data exchange with the front end.

[0079] In one embodiment, monitoring whether each cell of the form is selected includes: monitoring whether each cell of the form is selected based on a long connection communication mode.

[0080] Use the WebSocket API program to establish a two-way communication channel between the front end and the server. When a reporting user tries to edit a cell, the front end sends a request to the server and waits for the server to return the locking result. After the lock is successful, the front end displays the editable status; if the lock fails, it prompts other reporting users that they are editing, and blocks the current reporting user's editing operation.

[0081] In one embodiment, in order to avoid long-term reuse of resources that prevents other reporting users from editing, a timeout period can be set for each lock, and the file will be automatically unlocked after the timeout period is exceeded. At the same time, a manual unlocking interface is provided to facilitate the reporting user to voluntarily give up the editing rights.

[0082] In step 105, the data transmitted by the first cell is received, and according to the row and column where the first cell is located and the row and column where the entity is located, the first cell is associated with the first entity in the graph structure, and the data transmitted by the first cell is configured as the attribute of the first entity to obtain an updated graph structure.

[0083] The embodiment of the present invention supports configuring the attributes of multiple nodes simultaneously through multi-threaded processing.

[0084] In step 106, when the first cell is unselected, the first cell is unlocked and the data transmitted by the first cell is displayed in the form. Thereafter, in step 107, the updated graph structure is stored in the graph database.

[0085] Compared with document-based databases, graph databases are more suitable for processing complex relationships, have rich relationship expressions, are suitable for associated queries, and can effectively utilize large amounts of collaborative office data.

[0086] In the embodiment of the present invention, the graph database can intuitively display the relationship between data in the form of a graph, which makes the structure and association of the data easier for developers to understand and gain insight into. In the embodiment of the present invention, through the visualization tool, the connection and relationship path between nodes can be clearly seen, which facilitates the discovery of patterns and trends in the data.

[0087] Figure 3 FIG. 1 is another specific example of the collaborative office data processing method in an embodiment of the present invention. Figure 3 As shown, after storing the updated graph structure in the graph database, the method may further include:

[0088] Step 301: Using a centrality measurement algorithm, multiple nodes with degree centrality values ​​higher than a preset value are identified in the updated graph structure, and key information labels are printed for the multiple nodes with degree centrality values ​​higher than the preset value.

[0089] Degree centrality is the ratio of a node's degree (i.e., the number of edges connected to the node) to the maximum possible degree in the network. In a directed graph, the degree can be divided into in-degree (the number of edges pointing to the node) and out-degree (the number of edges emanating from the node).

[0090] The formula for calculating degree centrality is: C(v) = d(v) / )(n-1), where C(v) represents the degree centrality of node v, d(v) is the degree of node v, and n is the total number of nodes in the network.

[0091] According to this method, more important key information in collaborative office data can be found, so as to facilitate the subsequent effective use of collaborative office data.

[0092] Furthermore, in one embodiment, the graph database includes multiple graph structures. After printing the identification of key information for multiple nodes higher than a preset value, the method may also include: using a community detection algorithm to unify the entity identifiers of the graph structures in the graph database to obtain multiple graph structures with unified identifications; merging the multiple graph structures with unified identifications to obtain an integrated graph database.

[0093] Community detection algorithms include Louvain algorithm, Girvan-Newman algorithm and other algorithms. Through community detection algorithms, groups of nodes with similar attributes or close connections can be identified in the graph database. When implementing, the first step is to select a suitable community detection algorithm and apply it to the graph data. The second step is to analyze the results of the algorithm and evaluate the quality of community division. Indicators such as modularity and internal density can be used for evaluation. The third step is to perform subsequent processing on the detected community as needed, such as visualization and further analysis.

[0094] Afterwards, multiple graph structures are merged in the graph database to reduce data redundancy and avoid resource waste.

[0095] The present invention also provides a collaborative office data processing device, as described in the following embodiments. Since the principle of solving the problem by the device is similar to that of the collaborative office data processing method, the implementation of the device can refer to the implementation of the collaborative office data processing method, and the repeated parts will not be repeated.

[0096] Figure 4 FIG. 1 is a schematic diagram of a collaborative office data processing device according to an embodiment of the present invention. Figure 4 As shown, the device includes an initial processing module 401, a graph structure establishment module 402, a monitoring module 403, a graph structure update module 404, and a graph database storage module 405.

[0097] The initial processing module 401 is used to receive form data and establish a form version identifier for the form data; the form data includes table row and column data and characters filled in the table.

[0098] The graph structure building module 402 is used to perform semantic recognition on the form data to obtain multiple entities, relationships between entities, and rows and columns where the entities are located; and to build a graph structure with the form version identifier and multiple entities as nodes and the relationships between entities as edges.

[0099] The monitoring module 403 is used to monitor whether each cell of the form is selected, and when the first cell is selected, the first cell is locked.

[0100] The graph structure update module 404 is used to receive data transmitted by the first cell, associate the first cell with the first entity in the graph structure according to the row and column where the first cell is located and the row and column where the entity is located, configure the data transmitted by the first cell as attributes of the first entity, and obtain an updated graph structure.

[0101] The monitoring module 403 is further configured to unlock the first cell when the first cell is unselected, and display the data transmitted by the first cell in the form.

[0102] The graph database storage module 405 is used to store the updated graph structure in the graph database.

[0103] In one embodiment, the initial processing module 401 is specifically used to: receive form data filled in according to a preset form template; the preset form template corresponds to a collaborative office data type; the collaborative office data type includes one or any combination of the following:

[0104] Document data type, communication data type, task data type, process data type.

[0105] In one embodiment, the graph structure establishing module 402 is specifically used for:

[0106] Based on the table row and column data and the characters filled in the table, determine the row and column where the second cell of the filled character is located;

[0107] Semantic recognition is performed on the characters filled in each second cell to obtain multiple entities; each entity carries the row and column where the second cell is located;

[0108] Based on machine learning algorithms, relationship extraction is performed on all entities to obtain the relationships between entities.

[0109] In one embodiment, the graph structure building module 402 is specifically used to add one or any combination of the following attributes to the node:

[0110] Permission attributes, time attributes, geographic location attributes, lock status attributes, and security attributes; the permission attributes include node access restriction information, the time attributes include node status change time point information, and the security attributes include node encryption information.

[0111] In one embodiment, the monitoring module 403 is specifically used for:

[0112] Based on the long connection communication method, monitor whether each cell in the form is selected.

[0113] In one embodiment, the device further comprises:

[0114] The key information identification module is used for the graph database storage module 405 to store the updated graph structure in the graph database, and then identify multiple nodes with degree centrality values ​​higher than the preset value in the updated graph structure through the centrality measurement algorithm, and print key information identification for the multiple nodes higher than the preset value.

[0115] In one embodiment, the graph database includes a plurality of graph structures; the device further includes:

[0116] The graph structure merging processing module is used for unifying the entity identifiers of the graph structure in the graph database by using the community detection algorithm after the key information identification module prints the key information identifications for multiple nodes higher than the preset value, and obtains multiple graph structures with unified identifications; and merges the multiple graph structures with unified identifications to obtain an integrated graph database.

[0117] Figure 5 Schematic diagram of a computer device in an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention further provides a computer device 500, including a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501, and the processor 501 implements the above-mentioned collaborative office data processing method when executing the computer program 503.

[0118] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the collaborative office data processing method described above is implemented.

[0119] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the collaborative office data processing method is implemented.

[0120] In the embodiment of the present invention, multiple entities and relationships between entities are identified based on the form data of collaborative office, thereby establishing a graph structure, and storing the data input by collaborative office employees as node attributes in the graph structure, thereby realizing graph structure storage of collaborative office data. Compared with the prior art of directly storing the collaborative office data in a document-type database, the storage process of the collaborative office data is optimized, and finally the collaborative office data is stored in a graph database. Compared with a document-type database, a graph database can support faster query speeds and more effective data analysis capabilities. By storing the collaborative office data in a graph database, this method reduces the difficulty of subsequent mining of the collaborative office data.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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 A step that specifies a function in one or more boxes.

[0125] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A collaborative office data processing method, characterized in that: include: Receive form data and create a form version identifier for the form data; the form data includes table row and column data and characters filled in the form; Perform semantic recognition on form data to obtain multiple entities, relationships between entities, and rows and columns in which entities are located; A graph structure is established with form version identifiers and multiple entities as nodes, and with the relationships between form version identifiers and entities, and the relationships between entities as edges; Monitor whether each cell in the form is selected. When the first cell is selected, lock the first cell. Receive data transmitted by the first cell, associate the first cell with the first entity in the graph structure according to the row and column where the first cell is located and the row and column where the entity is located, configure the data transmitted by the first cell as an attribute of the first entity, and obtain an updated graph structure; When the first cell is unselected, unlock the first cell and display the data transmitted by the first cell in the form; The updated graph structure is stored in the graph database.

2. The collaborative office data processing method according to claim 1, characterized in that: Receive form data, including: Receive form data filled in according to a preset form template; the preset form template corresponds to a collaborative office data type; the collaborative office data type includes one or any combination of the following: Document data type, communication data type, task data type, process data type.

3. The collaborative office data processing method according to claim 1, characterized in that: Perform semantic recognition on form data to obtain multiple entities, relationships between entities, and rows and columns of entities, including: Based on the table row and column data and the characters filled in the table, determine the row and column where the second cell of the filled character is located; Semantic recognition is performed on the characters filled in each second cell to obtain multiple entities; each entity carries the row and column where the second cell is located; Based on machine learning algorithms, relationship extraction is performed on all entities to obtain the relationships between entities.

4. The collaborative office data processing method according to claim 1, characterized in that: Establishing the graph structure includes adding one or any combination of the following attributes to the nodes: Permission attributes, time attributes, geographic location attributes, lock status attributes, and security attributes; the permission attributes include node access restriction information, the time attributes include node status change time point information, and the security attributes include node encryption information.

5. The collaborative office data processing method according to claim 1, characterized in that: Monitor whether each cell in the form is selected, including: Based on the long connection communication method, monitor whether each cell in the form is selected.

6. The collaborative office data processing method according to claim 1, characterized in that: After storing the updated graph structure in the graph database, it also includes: Through the centrality measurement algorithm, multiple nodes with degree centrality values ​​higher than a preset value are identified in the updated graph structure, and identifications of key information are printed for the multiple nodes with degree centrality values ​​higher than the preset value.

7. The collaborative office data processing method according to claim 6, characterized in that: The graph database includes multiple graph structures; After printing the key information for multiple nodes above the preset value, it also includes: Use community detection algorithms to unify entity identifiers in graph structures in graph databases and obtain multiple graph structures with unified identifiers. Multiple graph structures with uniform identification are merged to obtain an integrated graph database.

8. A collaborative office data processing device, characterized in that: include: An initial processing module, used to receive form data and establish a form version identifier for the form data; the form data includes table row and column data and characters filled in the table; The graph structure building module is used to perform semantic recognition on form data to obtain multiple entities, relationships between entities, and the rows and columns in which entities are located; A graph structure is established with form version identifiers and multiple entities as nodes and relationships between entities as edges; A monitoring module is used to monitor whether each cell of the form is selected, and when the first cell is selected, the first cell is locked; A graph structure updating module, configured to receive data transmitted by a first cell, associate the first cell with a first entity in the graph structure according to a row and column where the first cell is located and a row and column where the entity is located, configure the data transmitted by the first cell as an attribute of the first entity, and obtain an updated graph structure; The monitoring module is further used to unlock the first cell when the first cell is unselected, and display the data transmitted by the first cell in the form; The graph database storage module is used to store the updated graph structure in the graph database.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the collaborative office data processing method according to any one of claims 1 to 7 is implemented.

10. 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 collaborative office data processing method according to any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the collaborative office data processing method according to any one of claims 1 to 7 is implemented.

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