Operation data processing method and device of online collaboration drawing board and storage medium

Abstract

The invention provides an operation data processing method and device of an online collaboration drawing board and a storage medium. The method comprises the steps of obtaining target operation data received by a target online collaboration drawing board document; acquiring first object attribute information of the target object and second object attribute information of the plurality of collaborative objects, and acquiring first historical operation data of the target object and second historical operation data of the plurality of collaborative objects; determining an identity confidence coefficient corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence coefficient corresponding to the target operation data based on the first historical operation data and the second historical operation data; and calculating target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determining a rationality evaluation result of the target operation data according to the target confidence. According to the method, rationality evaluation can be performed on the operation data received in the online collaborative drawing board, so that the safety of the content drawn by the online collaborative drawing board can be improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of online documents, and in particular, to an operation data processing method, device and storage medium of an online collaboration board. BACKGROUND

[0002] An online collaboration board is a virtual board that can be edited online by multiple people. It has the characteristic of infinite space compared with a real board, and thus can be applied to large-scale users to simultaneously edit complex engineering drawings online.

[0003] When the number of users simultaneously editing the edited work of the online collaboration board is large, some users may have abnormal editing operations on the edited work. At present, the online collaboration board lacks reasonable evaluation of the received operation data, resulting in low safety of the edited work of the online collaboration board. SUMMARY

[0004] The embodiments of the present disclosure provide an operation data processing method, device and storage medium of an online collaboration board, which can improve the safety of the edited work of the online collaboration board.

[0005] According to an aspect of the present disclosure, an operation data processing method of an online collaboration board is provided, comprising:

[0006] Obtaining target operation data received by a target online collaboration board document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration board document;

[0007] Obtaining first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and obtaining first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that collaboratively edit the target online collaboration board document with the target object;

[0008] Determining an identity confidence degree corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence degree corresponding to the target operation data based on the first historical operation data and the second historical operation data;

[0009] Calculating a target confidence degree corresponding to the target operation data according to the identity confidence degree and the behavior confidence degree, and determining a reasonable evaluation result of the target operation data according to the target confidence degree.

[0010] According to an aspect of the present disclosure, an operation data processing device of an online collaboration board is provided, comprising:

[0011] The first obtaining unit is configured to obtain target operation data received by a target online collaboration whiteboard document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration whiteboard document;

[0012] The second obtaining unit is configured to obtain first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and to obtain first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that collaboratively edit the target online collaboration whiteboard document with the target object;

[0013] The first determining unit is configured to determine an identity confidence corresponding to the target operation data based on the first object attribute information and the second object attribute information, and to determine a behavior confidence corresponding to the target operation data based on the first historical operation data and the second historical operation data;

[0014] The second determining unit is configured to calculate a target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and to determine a rationality evaluation result of the target operation data according to the target confidence.

[0015] Optionally, in some embodiments, the online collaboration whiteboard operation data processing apparatus provided by the present disclosure further includes:

[0016] The updating subunit is configured to perform content updating on the target online collaboration whiteboard document based on the target operation data when the rationality evaluation result indicates that the target operation data is reasonable.

[0017] The control subunit is configured to reject a request for performing content updating on the target online collaboration whiteboard document based on the target operation data when the rationality evaluation result indicates that the target operation data is unreasonable.

[0018] Optionally, in some embodiments, the online collaboration whiteboard operation data processing apparatus provided by the present disclosure further includes:

[0019] The first generating subunit is configured to generate abnormality prompt information based on the target operation data.

[0020] The sending subunit is configured to send the abnormality prompt information to a client corresponding to the collaborative object.

[0021] Optionally, in some embodiments, the online collaboration whiteboard operation data processing apparatus provided by the present disclosure further includes:

[0022] The second generating subunit is configured to generate an abnormality label according to the target operation data and the first object attribute information.

[0023] a labeling subunit, configured to label the target object based on the abnormal label.

[0024] Optionally, in some embodiments, the operation data processing apparatus of the online collaboration whiteboard provided by the present disclosure further comprises:

[0025] an acquisition subunit, configured to acquire execution state information corresponding to the target operation data;

[0026] a revocation subunit, configured to, when the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is not rational, revoke an execution result corresponding to the target operation data in the target online collaboration whiteboard document.

[0027] Optionally, in some embodiments, the revocation subunit comprises:

[0028] an acquisition module, configured to, when the execution state information indicates that the target operation data has been executed, acquire associated operation data dependent on the target operation data;

[0029] a revocation module, configured to revoke execution results of the target operation data and the associated operation data in the target online collaboration whiteboard document.

[0030] Optionally, in some embodiments, the first determination unit comprises:

[0031] an extraction subunit, configured to extract first login address information and first identity label information from the first object attribute information, and extract second login address information and second identity label information from the second object attribute information;

[0032] a first determination subunit, configured to cluster the second login address information to obtain a plurality of login address classes, and determine a first confidence degree according to a first subordination relationship between the first login address information and the plurality of login address classes;

[0033] a second determination subunit, configured to cluster the second identity label information to obtain a plurality of identity label classes, and determine a second confidence degree according to a second subordination relationship between the first identity label information and the plurality of identity label classes;

[0034] a first calculation subunit, configured to calculate an identity confidence degree corresponding to the target operation data according to the first confidence degree and the second confidence degree.

[0035] Optionally, in some embodiments, the first calculation subunit comprises:

[0036] determining a first weight corresponding to the first confidence degree and a second weight corresponding to the second confidence degree according to the first subordination relationship, the second subordination relationship and a preset subordination relationship matching rule;

[0037] The first calculation module is configured to perform weighted calculation on the first confidence degree and the second confidence degree based on the first weight and the second weight, to obtain an identity confidence degree corresponding to the target operation data.

[0038] Optionally, in some embodiments, the first determination unit can further include:

[0039] The third determination subunit is configured to determine a third confidence degree according to the historical rationality of the first historical operation data.

[0040] determine a fourth confidence degree according to the association between the first historical operation data and the target operation data;

[0041] The fourth determination subunit is configured to determine a fifth confidence degree based on the association between the second historical operation data and the target operation data.

[0042] The second calculation subunit is configured to calculate a behavior confidence degree corresponding to the target operation data according to the third confidence degree, the fourth confidence degree and the fifth confidence degree.

[0043] Optionally, in some embodiments, the third determination subunit includes:

[0044] The first aggregation module is configured to perform multi-dimensional aggregation processing on the first historical operation data, and generate a first behavior vector according to multi-dimensional aggregated values.

[0045] The second aggregation module is configured to perform multi-dimensional aggregation processing on the plurality of second historical operation data respectively, and generate a plurality of second behavior vectors according to multi-dimensional aggregated values.

[0046] The clustering module is configured to perform clustering processing on the plurality of second behavior vectors to obtain a clustering center vector.

[0047] The second calculation module is configured to calculate a cosine similarity between the first behavior vector and the clustering center vector, and determine a third confidence degree of the first historical operation data according to the cosine similarity.

[0048] Optionally, in some embodiments, the third determination subunit includes:

[0049] The first drawing module is configured to perform aggregation processing on the first historical operation data, and draw a first behavior statistical chart according to an aggregation result.

[0050] a second drawing module configured to aggregate the plurality of second historical operation data, and draw a plurality of second behavior statistical charts according to an aggregation result;

[0051] an extraction module configured to perform graph feature extraction on the first behavior statistical chart and the plurality of second behavior statistical charts respectively based on a preset graph feature extraction model, to obtain first graph features corresponding to the first behavior statistical chart and second graph features corresponding to each of the second behavior statistical charts;

[0052] a third calculation module configured to calculate a feature mean of the plurality of second graph features, and determine a third confidence degree of the first historical operation data based on a similarity between the first graph features and the feature mean.

[0053] According to an aspect of the present disclosure, a storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the operation data processing method of the online collaboration whiteboard as described above.

[0054] According to an aspect of the present disclosure, a computer program product is provided, which includes a computer program. The computer program is read and executed by a processor of a computer device, so that the computer device performs the operation data processing method of the online collaboration whiteboard as described above.

[0055] The operation data processing method of the online collaboration whiteboard provided by the embodiments of the present disclosure specifically includes obtaining target operation data received by a target online collaboration whiteboard document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration whiteboard document; obtaining first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and obtaining first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that edit the target online collaboration whiteboard document collaboratively with the target object; determining an identity confidence degree corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence degree corresponding to the target operation data based on the first historical operation data and the second historical operation data; calculating a target confidence degree corresponding to the target operation data according to the identity confidence degree and the behavior confidence degree, and determining a rationality evaluation result of the target operation data according to the target confidence degree.

[0056] In the embodiments of the present disclosure, when the operation data of an object is received in the online collaboration whiteboard, the identity attribute information of the input object of the operation data can be acquired, and the identity attribute information of other collaboration objects in the online collaboration whiteboard is combined to determine the identity confidence of the input object. In addition, the historical operation data of the input object of the operation data and the historical operation data of a plurality of collaboration objects can be acquired, and the behavior confidence is determined according to the historical operation data of the two. Further, the identity confidence and the behavior confidence can be combined to reasonably evaluate the operation data received in the online collaboration whiteboard, and the input control of the operation data is performed according to the evaluation result. In this way, the unreasonable operation data can be avoided to affect the security of the work of the online collaboration whiteboard, and the security of the work of the online collaboration whiteboard is ensured.

[0057] Other features and advantages of the present disclosure will be set forth in the following description, and in part will become apparent from the description, or can be learned by practice of the present disclosure. The objects and other advantages of the present disclosure can be achieved and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0058] The accompanying drawings are intended to provide a further understanding of the technical solutions of the present disclosure, and constitute a part of the specification, and are used together with the embodiments of the present disclosure to explain the technical solutions of the present disclosure, and do not constitute a limitation on the technical solutions of the present disclosure.

[0059] Figure 1 is a system architecture diagram applied by the operation data processing method of the online collaboration whiteboard according to the embodiments of the present disclosure;

[0060] Figure 2 is Figure 1 is a software structure diagram of the online collaboration whiteboard in the embodiments of the present disclosure;

[0061] Figure 3 is a flowchart of the operation data processing method of the online collaboration whiteboard of the present disclosure;

[0062] Figure 4 is a scene diagram of the operation data processing method of the online collaboration whiteboard provided by the present disclosure;

[0063] Figure 5 is another scene diagram of the operation data processing of the online collaboration whiteboard provided by the present disclosure;

[0064] Figure 6 is still another scene diagram of the operation data processing method of the online collaboration whiteboard provided by the present disclosure;

[0065] Figure 7 is another flowchart of the operation data processing method of the online collaboration whiteboard provided by the present disclosure;

[0066] Figure 8 A structural schematic diagram of an operation data processing apparatus of an online collaboration whiteboard provided by an embodiment of the present disclosure is shown in FIG. 1.

[0067] Figure 9 The online collaboration whiteboard is shown in FIG. 1 according to an embodiment of the present disclosure Figure 3 A terminal structural diagram of an operation data processing method of an online collaboration whiteboard is shown in FIG. 2.

[0068] Figure 10 The online collaboration whiteboard is shown in FIG. 1 according to an embodiment of the present disclosure Figure 3 A server structural diagram of an operation data processing method of an online collaboration whiteboard is shown in FIG. 3. DETAILED DESCRIPTION

[0069] In order to make the objectives, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and should not be used to limit the present disclosure.

[0070] An online collaboration whiteboard is a whiteboard document that can be edited by multiple people online at the same time, and has the characteristics of unlimited space and support for multiple format content input. The online collaboration whiteboard can be widely used in online meetings, online education, collaborative design office and other fields to improve work efficiency in these fields.

[0071] When using an online collaboration whiteboard to draw a large work, a large number of collaboration objects may need to edit the same online collaboration whiteboard document online at the same time. In order to ensure the safety of the work, in the related art, the creator of the online collaboration whiteboard document can act as a quality supervision role to check and supervise the content displayed in the online collaboration whiteboard document. However, when there are many collaboration objects, the online collaboration whiteboard receives a large number of editing operations at the same time, resulting in a high frequency of changes in the content of the online collaboration whiteboard document, making it difficult to comprehensively check the content displayed in the online collaboration whiteboard document. In addition, checking the content displayed in the online collaboration whiteboard is a post-checking, when the problem is found during checking, the abnormal operation may have been performed for a period of time, and new operations have been generated based on this operation, resulting in a large impact on the quality of the work.

[0072] Moreover, the operations of the drawing personnel of the online collaboration whiteboard are independent of each other, unless there is a conflict between the operations, which needs to be coordinated by a conflict algorithm, otherwise each independently edits the work in the online collaboration whiteboard, making it difficult for other collaboration objects to discover the abnormal operation of the abnormal object in time.

[0073] When the number of collaboration objects of the online collaboration drawing board is large, it is difficult to avoid the existence of malicious objects. The abnormal behavior of the malicious objects can cause damage to the drawn work and affect the security of the drawn work. In addition, normal collaboration objects can also have misoperations (such as misinputting data or misdeleting data, etc.), which can cause the drawn work to be damaged unintentionally. In summary, the current online collaboration drawing board has low security of the drawn work when multiple people collaborate to draw the work.

[0074] To solve the problem of low security of the drawn work when multiple people collaborate to draw the work using the online collaboration drawing board, the present disclosure provides an operation data processing method of an online collaboration drawing board, so as to improve the security of the drawn work to a certain extent.

[0075] System architecture and scenario to which the embodiments of the present disclosure are applied

[0076] Figure 1 It is a system architecture diagram to which the operation data processing method of the online collaboration drawing board according to the embodiments of the present disclosure is applied. It includes a terminal 140, an Internet 130, a gateway 120, a server 110, etc.

[0077] The terminal 140 includes a desktop computer, a laptop computer, a PDA (personal digital assistant), a mobile phone, a vehicle-mounted terminal, a home theater terminal, a special-purpose terminal, a smart voice interaction device, a smart home appliance, or an aircraft, etc. various forms of devices with a display screen. In addition, it can be a single device or a collection of multiple devices. The terminal 140 can communicate with the Internet 130 in a wired or wireless manner to exchange data. In the embodiments of the present disclosure, the terminal 140 can be multiple, and each terminal 140 can be loaded with an online collaboration drawing board application. Multiple collaboration objects can simultaneously edit the same online collaboration drawing board document based on the online collaboration drawing board applications loaded in the multiple terminals 140.

[0078] The server 110 refers to a computer system capable of providing certain services to the terminal 140. Compared with the ordinary terminal 140, the server 110 has higher requirements in stability, security, performance, and the like. The server 110 can be a high-performance computer in a network platform, a cluster of multiple high-performance computers, a part of a high-performance computer (for example, a virtual machine), a combination of parts of multiple high-performance computers (for example, virtual machines), or the like. In the embodiments of the present disclosure, the server 110 can specifically be an application server of an online collaboration whiteboard, configured to process operation data uploaded by clients of the online collaboration whiteboard application loaded in the multiple terminals 140 and determine content displayed in the online collaboration whiteboard. The server 110 can also specifically be connected with a storage, which can be the aforementioned distributed storage service, and the storage can store identity registration information, permission information, collaboration whiteboard element templates, and the like of a user of the online collaboration whiteboard application.

[0079] The gateway 120 is also called an internetworking connector or a protocol converter. The gateway implements network interconnection at the transport layer and is a computer system or device acting as a conversion function. The gateway is a translator between two systems using different communication protocols, data formats or languages, or even having completely different architectures. Meanwhile, the gateway can also provide filtering and security functions. Messages sent by the terminal 140 to the server 110 are sent to the corresponding server 110 through the gateway 120. Messages sent by the server 110 to the terminal 140 are also sent to the corresponding terminal 140 through the gateway 120. In the embodiments of the present disclosure, the terminal 140 sends operation data received in the client of the online collaboration whiteboard to the server 110 through the gateway 120, and the server 110 sends a display screen generated based on the operation data sent by multiple clients to each terminal 140 for display through the gateway 120.

[0080] Exemplarily, a software structure diagram of the online collaboration whiteboard is as shown in FIG. 2. Figure 2As shown: the background architecture of the online collaboration drawing board can be divided into a business layer, an access layer, a collaboration layer, an engine layer and a storage layer. Among them, the business layer is used for facing users, providing user operation interfaces, and receiving user editing operation information; for example, new, edit, insert (file), collaboration, etc. The access layer is used to provide a communication interface between the online collaboration drawing board background and the outside, supporting multiple communication protocols; for example, Remote Procedure Call (RPC), Hypertext Transfer Protocol (HTTP), Websocket (a protocol for full-duplex communication on a single Transmission Control Protocol connection), Common Gateway Interface (CGI), etc. The collaboration layer is used to convert various types of data received based on the business layer and the access layer into a unified format and forward it to the engine layer. The engine layer is the main function implementation part of the online collaboration drawing board, including the involved link management, basic capability module, core capability module. Among them, the involved links include gateway, document management, etc., the basic capabilities include collaborative editing, operation execution, etc., and the core capabilities include operation data processing. The storage layer is used to store various types of data of the engine layer, and provides local cache, Remote Dictionary Server (Redis), distributed storage and other storage services.

[0081] The operation data processing method of the online collaboration drawing board provided by the present disclosure can be applied in the server 110. Specifically, when the operation data processing method of the online collaboration drawing board provided by the present disclosure is applied in the server 110, the server 110 obtains target operation data received by a target online collaboration drawing board document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration drawing board document; then, the server 110 obtains first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and obtains first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that collaboratively edit the target online collaboration drawing board document with the target object; further, the server 110 determines an identity confidence corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determines a behavior confidence corresponding to the target operation data based on the first historical operation data and the second historical operation data; then, the server 110 calculates a target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determines a rationality evaluation result of the target operation data according to the target confidence.

[0082] The embodiments of the present disclosure can be applied in various scenarios, such as online collaboration drawing scenarios or online meeting scenarios, etc.

[0083] When the embodiments of the present disclosure are applied in an online collaborative drawing scenario, a work initiator creates an online collaborative drawing board document, and then sends the document to several responsible persons of work modules, and each responsible person of the work module is responsible for further calling a team for efficient drawing of the work. At this time, each responsible person of the work module can draw a work framework in the respective module, and then send the online collaborative drawing board document to other drawers for drawing of detailed content of each work module. When the detailed content is drawn, the drawer can also send the online collaborative drawing board document to others for assisting in drawing. In this way, since a large work drawing project can be divided into multiple modules and then distributed to multiple levels for collaborative drawing tasks, the drawing operation of some collaborators can not be controllable, thereby affecting the safety of the overall drawing work.

[0084] When the embodiments of the present disclosure are applied in an online collaborative drawing scenario, a work initiator creates an online collaborative drawing board document, and then sends the document to several responsible persons of work modules, and each responsible person of the work module is responsible for further calling a team for efficient drawing of the work. At this time, each responsible person of the work module can draw a work framework in the respective module, and then send the online collaborative drawing board document to other drawers for drawing of detailed content of each work module. When the detailed content is drawn, the drawer can also send the online collaborative drawing board document to others for assisting in drawing. In this way, since a large work drawing project can be divided into multiple modules and then distributed to multiple levels for collaborative drawing tasks, the drawing operation of some collaborators can not be controllable, thereby affecting the safety of the overall drawing work.

[0085] It should be understood that the above only illustrates the description of part of the application scenarios of the present disclosure. The business scenarios to which the present disclosure can be applied can include but are not limited to the specific scenarios mentioned above.

[0086] Overall description of embodiments of the present disclosure

[0087] The embodiments of the present disclosure provide an operation data processing method of an online collaborative drawing board. As shown in Figure 3 FIG. 1 is a flowchart of an operation data processing method of an online collaborative drawing board provided by the present disclosure. The method can be applied to an operation data processing device of an online collaborative drawing board, and the device can be integrated in a background server of the online collaborative drawing board. The operation data processing method of the online collaborative drawing board specifically includes:

[0088] At step 310, target operation data received by the target online collaboration whiteboard document is acquired.

[0089] In the related art, while the online collaboration whiteboard provides the function of simultaneous online editing by multiple persons, there is a lack of effective rationality evaluation of operation data received by the online collaboration whiteboard, which affects the content security of the online collaboration whiteboard. To this end, the present case provides a method for evaluating the rationality of operation data received in the online collaboration whiteboard, so as to accurately evaluate the rationality of operation data received in the online collaboration whiteboard, and then control the reception of operation data based on the rationality of the operation data, to avoid the input of unreasonable operation data into the online collaboration whiteboard to affect the safety of the work drawn in the online collaboration whiteboard.

[0090] The online collaboration whiteboard operation data rationality evaluation method provided in the present application can be specifically applied to the server of the online collaboration whiteboard. It can be understood that the online collaboration whiteboard is an application that can create multiple online collaboration whiteboard documents, and the online collaboration whiteboard server can evaluate the rationality of operation data received in each online collaboration whiteboard document created based on the online collaboration whiteboard application. The processing method of the online collaboration whiteboard operation data provided in the present case will be described in detail below.

[0091] In the embodiments of the present disclosure, for different online collaboration whiteboard documents, the online collaboration whiteboard server can use the same method to evaluate the rationality of operation data received therein, so the method provided in the present disclosure can be introduced by taking any target online collaboration whiteboard document as an example.

[0092] When any target object starts the loaded online collaboration whiteboard application in its terminal and opens the target online collaboration whiteboard document, the content already drawn in the target online collaboration whiteboard document can be displayed. The target object can perform secondary creation and drawing on the already drawn content, or can draw in the blank part of the target online collaboration whiteboard document. Whether it is secondary creation on the existing content or original creation, the target object needs to input editing operations into the target online collaboration whiteboard. At this time, the server of the online collaboration whiteboard can acquire target operation data received by the target online collaboration whiteboard document, and the target operation data can be data corresponding to the editing operation of the target object on the target online collaboration whiteboard document.

[0093] The target object can be any object that edits the target online collaboration whiteboard document, i.e., the creator of the target online collaboration whiteboard document, the person in charge of the aforementioned certain module drawing task, or the drawer who specifically performs a certain detail drawing task.

[0094] In some embodiments, a white list can also be maintained in the server of the online collaboration whiteboard, and operation data input by an object in the white list can not need to be subjected to reasonableness assessment, and only operation data input by an object outside the white list is subjected to reasonableness assessment. At this time, the target object can be an object outside the white list. Alternatively, in some other embodiments, whether operation data input by an object needs to be subjected to reasonableness assessment can be determined according to identity permission information of the object. For example, operation data input by some objects with preset permissions and higher permissions can not need to be subjected to reasonableness assessment, and only operation data input by an object without the above permissions is subjected to reasonableness assessment. At this time, the target object can be an object without the above permissions.

[0095] The data corresponding to the editing operation of the target object (i.e., target operation data) can specifically include an edited element object, a type of editing operation, an operation parameter or operation content of the editing operation, and the like. The edited element object can specifically include, but is not limited to, a text box object, a text object, a table object, a picture object, a model object in a picture, a video object, an audio object, and a document object, and the like. The type of editing operation includes, but is not limited to, an adding operation, a deleting operation, a dragging operation, a zooming-in or zooming-out operation, a modification of a text attribute of an object, a modification of a color of an object, and the like. The operation parameter can include a size parameter of an object, a frequency parameter of change, a color parameter of an object, a time parameter of editing, and the like. The operation content can include text content, shape content, audio content, video content, and the like.

[0096] The target operation data can be obtained when the target object is received by the server of the online collaboration whiteboard, or can be obtained in response to other trigger instructions. For example, when the server of the online collaboration whiteboard receives complaint / report information of another operation object, the other operation object reports that an element in the online collaboration whiteboard is abnormal. The server of the online collaboration whiteboard can analyze the element, determine an editing operation associated with the element and a target object corresponding to the editing operation, and then obtain the target operation data of the target object and the editing operation associated with the abnormal element, or obtain the target operation data of the target object and the editing operation corresponding to the target object within a certain time.

[0097] In step 320, first object attribute information of the target object and second object attribute information of the plurality of collaborative objects are obtained, and first historical operation data of the target object and second historical operation data of the plurality of collaborative objects are obtained.

[0098] After obtaining the target operation data, the server of the online collaboration whiteboard can analyze the rationality of the target operation data. Specifically, first object attribute information of the target object and second object attribute information of the plurality of collaborative objects can be obtained. The collaborative objects can specifically be objects that collaborate with the target object to edit the target online collaboration whiteboard document.

[0099] The object attribute information (the first object attribute information of the target object or the second object attribute information of the collaborative objects) can specifically include information input when the online collaboration whiteboard application is first enabled, such as basic identity attribute information of the object, tag information of the object, login address information of the object logging into the online collaboration whiteboard application, and the like. The object attribute information can be obtained on the basis of obtaining authorization of the object and complying with relevant regulations. The tag information of the object can be role tag information of the object in the collaborative drawing transaction corresponding to the target online collaboration whiteboard document, such as A project leader, B project executor, C module leader, and unknown project executor, or can be identity tags unrelated to the current online collaboration whiteboard document, such as XX enterprise employee and XX group member. The login address information of the object logging into the online collaboration whiteboard application can be login address information of the object currently logging into the online collaboration whiteboard application, can be common login address information of the object logging into the online collaboration whiteboard application, or can be login address information of the object logging into the online collaboration whiteboard application within a certain period of time (for example, in the last week or month).

[0100] In addition, in addition to obtaining the object attribute information of the target object and the collaborative objects, the historical operation data of the target object and the collaborative objects can be further obtained. The historical operation data can be operation data corresponding to all editing operations input by the target object or the collaborative objects in the target online collaboration whiteboard document, or can be operation data corresponding to editing operations input by the target object or the collaborative objects in the target online collaboration whiteboard document within a certain period of time.

[0101] In order to obtain the historical operation data of the object, the disclosure further provides a method for object-dimensionally counting the object operation data in each online collaboration whiteboard document. First, an editing operation capturing module is designed on the client side of each online collaboration whiteboard, which is used to capture all editing operations of each object and encapsulate the editing operations into editing operation events and send them to the server of the online collaboration whiteboard for processing. Then, an editing operation storage module is designed on the server side of the online collaboration whiteboard, which is responsible for receiving editing operation events from the client and storing them according to the object dimension. That is, in the corresponding memory of the server, an object operation object storage area is set for each online collaboration whiteboard document, and in the storage area, the storage area is divided into multiple storage blocks according to the object dimension, and the detailed data of the editing operation events of an object is stored in each storage block. In some embodiments, a relational database or a NoSQL database can be used to store the object operation data, and a separate data table or collection is created for each object to store the operation data corresponding to all editing operations. Each editing operation event corresponds to a record in the database, and the record can include the following fields: object ID, operation time, edited object ID, operation type, operation data, etc. The object ID is used to identify the initiator of the operation; the operation time is used to record the time of the operation; the edited object ID is used to identify the edited content; the operation type is used to represent the performed operation, such as insertion, deletion, modification, etc.; and the operation data is used to store the specific content of the operation, such as inserted graphics, modified text, etc. In order to improve the data query efficiency, indexes can be created for the object ID, operation time and other key fields in the database. In addition, partition tables, sharding and other technologies can be used to distribute the storage of a large number of object editing operation events, further improving the data processing performance.

[0102] In addition, an editing operation management module can also be designed in the server of the online collaboration whiteboard, which is responsible for processing query requests from the processor, such as querying all historical operation data of a certain object within a certain time period. The query request can query all editing operation events of a certain object within a certain time period by specifying the object ID and the time range. The query result will be sorted according to the operation time to ensure the order of the operation events. In order to ensure the query performance, cache technology can be used to cache hot data in the memory to reduce the access pressure on the database.

[0103] Further, in some embodiments, an operation data aggregation module can also be designed to aggregate operation data corresponding to each online collaboration whiteboard document according to object dimensions, to generate operation data aggregation results for each object. The operation data aggregation results can include total operation times of the object, operation times of each operation type, most active operation time period, and the like. To achieve efficient aggregation processing, a MapReduce or similar distributed computing framework can be used. First, in the Map phase, the object's edit operation event list is traversed, and each edit operation event is mapped to a set of key-value pairs, with the key being the operation type and the value being 1. For example, for an insertion operation, the key-value pair ("insert", 1) is generated; for a deletion operation, the key-value pair ("delete", 1) is generated. Then, in the Reduce phase, the key-value pairs generated in the Map phase are reduced. For each operation type, the corresponding values are added to obtain the total number of times of the operation type. For example, for an insertion operation, the values of all ("insert", 1) key-value pairs are added to obtain the total number of insertion operations.

[0104] Further, in some embodiments, an operation data display module can also be designed to display operation data corresponding to each online collaboration whiteboard document according to object dimensions. The displayed content can include the total operation times of the object, the operation times of each operation type, the most active operation time period, and the like. The display method can use various chart types such as column chart, pie chart, and heat map.

[0105] Step 330, determining the identity confidence of the target operation data based on the first object attribute information and the second object attribute information, and determining the behavior confidence of the target operation data based on the first historical operation data and the second historical operation data.

[0106] When the first object attribute information of the target object corresponding to the target operation data to be evaluated for rationality is determined, and the first historical operation data of the target object is obtained, and the second object attribute information of the collaboration object is determined, and the second historical operation data of the collaboration object is obtained, the target operation data can be analyzed for rationality based thereon.

[0107] Specifically, the identity confidence of the target operation data can be determined based on the first object attribute information and the second object attribute information; then the behavior confidence of the target operation data can be determined based on the first historical operation data and the second historical operation data, and finally the target operation data can be jointly analyzed according to the identity confidence and the behavior confidence to determine its rationality.

[0108] In some embodiments, the identity confidence of the target operation data is determined based on the first object attribute information and the second object attribute information, including:

[0109] extract first login address information and first identity tag information from the first object attribute information, and extract second login address information and second identity tag information from the second object attribute information;

[0110] cluster the second login address information to obtain a plurality of login address classes, and determine a first confidence degree according to a first subordination relationship between the first login address information and the plurality of login address classes;

[0111] cluster the second identity tag information to obtain a plurality of identity tag classes, and determine a second confidence degree according to a second subordination relationship between the first identity tag information and the plurality of identity tag classes;

[0112] calculate an identity confidence degree corresponding to the target operation data according to the first confidence degree and the second confidence degree.

[0113] In the embodiments of the present disclosure, the object attribute information can at least include login address information and identity tag information, so that the identity confidence degree corresponding to the target operation data can be determined based on the login address information and the identity tag information of the object.

[0114] Specifically, the first login address information and the first identity tag information can be extracted from the first object attribute information, and the second login address information and the second identity tag information can be extracted from each second object attribute information.

[0115] In the embodiments of the present disclosure, the first login address information of the target object and the second login address information of the collaborative object can be the login address information when logging in to the online collaboration board application last time. For the target object, the first login address information can be further determined as the login address information corresponding to the login address when sending the target operation data to the server. Then, the plurality of second login address information is clustered to obtain a plurality of login address classes. Further, the first subordination relationship between the first login address information and the plurality of login address classes can be detected. Specifically, it can be checked whether the first login address corresponding to the first login address information belongs to a certain login address class. If it belongs, it is determined that the object has a higher possibility of being a normal object, and the first confidence degree can be set as a higher confidence value. Otherwise, it is determined that the object has a higher possibility of being an abnormal object, so the first confidence degree can be set as a lower confidence value.

[0116] Specifically, the login address information can be the location information of the terminal when logging into the online collaboration whiteboard application. Generally, the large collaboration drawing task of the online collaboration whiteboard is completed by one or more organizations, and the geographical positions of the members of each organization are close to each other to some extent and can be aggregated into one or more aggregated address categories. If the login address of a user of an online collaboration whiteboard belongs to any aggregated address category, it means that the user is more likely to belong to a certain organization. If the login address of a user of an online collaboration whiteboard does not belong to any aggregated address category, the user is more likely to not belong to any organization, and the user is more likely to be an abnormal user.

[0117] In some embodiments, the historical login address information of the target object can also be further obtained, that is, the login address information of the target object when logging into the online collaboration whiteboard application in the past period of time can be obtained. Then, the first login address information is matched with the historical login address information. If the two are matched (the positions are the same or the distances are close), it means that the login behavior of the object is relatively normal. If the first login address information and the historical login address information are not matched (the positions are far away from each other), there can be an abnormal login situation, for example, the account of the object is stolen. At this time, the current login IP address information and the historical login IP address information of the target object can be further obtained. If the current login IP address information and the historical login IP address information are the same, it means that the target object can be on a business trip, and it can be determined that the login behavior is normal. On the contrary, if the login IP address information and the historical login IP address information of the target object are different, the target object is more likely to be an abnormal login, and the first confidence degree of the target object can be determined as a low value.

[0118] As described above, the login address information can only generally determine the rationality of the login behavior of the object, and the determination is more based on experience. Therefore, in the embodiments of the present disclosure, the identity tag information of the target object and the collaboration object is further obtained, the second confidence degree is determined based on the identity tag information of the target object and the collaboration object, and then the accurate identity confidence degree is determined by combining the first confidence degree and the second confidence degree.

[0119] Specifically, the identity tag information of the target object or the collaboration object can include the identity tag related to the target online collaboration whiteboard document and the identity tag unrelated to the target online collaboration whiteboard document. The identity tag related to the online collaboration whiteboard document can be the role tag information related to the drawing task of the target online collaboration whiteboard document (for example, the person in charge of the drawing task module and the participant as described above), and the identity information unrelated to the online collaboration whiteboard document can be the work information (for example, XX enterprise employee authentication) and other tag information counted when the application is registered.

[0120] After obtaining the second identity tag information of each collaboration object, the multiple second identity tag information can be clustered to obtain multiple identity tag classes, and then it is determined whether the first identity tag information corresponds to one of the identity tag classes. If yes, a larger second confidence can be determined, and if not, a smaller second confidence can be determined.

[0121] After determining the first confidence and the second confidence, the accurate identity confidence corresponding to the target operation data can be calculated based on the first confidence and the second confidence.

[0122] In some embodiments, the identity confidence corresponding to the target operation data is calculated according to the first confidence and the second confidence, including:

[0123] The first weight corresponding to the first confidence and the second weight corresponding to the second confidence are determined according to the first subordination relationship, the second subordination relationship, and a preset subordination relationship matching rule.

[0124] The first confidence and the second confidence are weighted and calculated based on the first weight and the second weight to obtain the identity confidence corresponding to the target operation data.

[0125] In the embodiments of the present disclosure, different weight coefficients can be set for the first confidence determined according to the login address and the second confidence determined according to the identity tag. In order to further improve the accuracy of the identity confidence, the embodiments of the present disclosure also provide a method for dynamically determining the weight coefficients corresponding to the first confidence and the second confidence.

[0126] Specifically, the first weight corresponding to the first confidence and the second weight corresponding to the second confidence can be determined according to the first subordination relationship, the second subordination relationship, and a preset subordination relationship matching rule. The preset subordination relationship matching rule can be a matching relationship between multiple different subordination relationship combinations and weight settings determined according to the first subordination relationship and the second subordination relationship. For example, the first subordination relationship is that the login address corresponding to the first login address information belongs to one of multiple login address classes, and the second subordination relationship is that the identity tag corresponding to the first identity tag information also belongs to one of multiple identity tag classes, then it can be determined that the first weight and the second weight are both 50%. Or, if there is a strong matching class in the multiple identity tag classes, for example, a certain identity tag class is the manager of the drawing task of the target online collaboration whiteboard document, at this time, no matter whether the login address corresponding to the first login address information belongs to one of the multiple login address classes, the first confidence can be set to a small weight (for example, 10%), and the second confidence can be set to a high weight (for example, 90%).

[0127] In some embodiments, the behavior confidence corresponding to the target operation data is determined based on the first historical operation data and the second historical operation data, including:

[0128] The third confidence is determined according to the historical rationality of the first historical operation data;

[0129] The fourth confidence is determined according to the relevance between the first historical operation data and the target operation data;

[0130] The fifth confidence is determined based on the relevance between the second historical operation data and the target operation data;

[0131] The behavior confidence corresponding to the target operation data is calculated according to the third confidence, the fourth confidence and the fifth confidence.

[0132] In the embodiments of the present disclosure, after the first historical operation data of the target object and the second historical operation data of the plurality of collaborative objects are obtained, the behavior confidence of the target operation data can be further evaluated according to the first historical operation data of the target object and the second historical operation data of the plurality of collaborative objects.

[0133] Specifically, the overall confidence of the operation behavior of the target object, i.e., the third confidence, can be determined according to the historical rationality of the first historical operation data of the target object itself. At the same time, the fourth confidence can be determined according to the relevance between the first historical operation data and the target operation data, whether the current operation conforms to the operation expectation of the target object, and the fifth confidence can be determined according to the relevance between the second historical operation data and the target operation data, the relationship between the current operation and the overall drawing behavior.

[0134] The historical rationality of the first historical operation data can be determined according to whether there is operation data with lower rationality identified in the first historical operation data of the target object, whether there is operation data complained, and the relevance between a plurality of operation data included in the first historical operation data. When the first historical operation data is less, the historical rationality of the first historical operation data can also be determined according to the relevance between the first historical operation data and the second historical operation data, so as to obtain the third confidence.

[0135] In some embodiments, the third confidence is determined according to the historical rationality of the first historical operation data, including:

[0136] The first historical operation data is aggregated in multiple dimensions, and a first behavior vector is generated according to the aggregated values of the multiple dimensions;

[0137] The plurality of second historical operation data are respectively subjected to multi-dimensional aggregation processing, and a plurality of second behavior vectors are generated according to the multi-dimensional aggregation values;

[0138] The plurality of second behavior vectors are subjected to clustering processing to obtain a clustering center vector;

[0139] The cosine similarity between the first behavior vector and the clustering center vector is calculated, and the third confidence of the first historical operation data is determined according to the cosine similarity.

[0140] In the embodiments of the present disclosure, when the historical rationality of the first historical operation data is determined in combination with the second historical operation data, the first historical operation data can be subjected to multi-dimensional aggregation processing first, and a first behavior vector is generated according to the multi-dimensional aggregation values. Then, the plurality of second historical operation data can also be subjected to multi-dimensional aggregation processing, and a plurality of second behavior vectors are generated according to the multi-dimensional aggregation values. Further, the plurality of second behavior vectors can be subjected to clustering processing to obtain a clustering center vector. In this way, the cosine similarity between the first behavior vector and the clustering center vector can be calculated, and the third confidence of the first historical operation data can be determined according to the cosine similarity. This method can fully extract the statistical features of the historical operation data, and determine the accurate historical rationality of the first historical operation data according to the similarity between the statistical features.

[0141] In some embodiments, the third confidence is determined according to the historical rationality of the first historical operation data, including:

[0142] The first historical operation data is subjected to aggregation processing, and a first behavior statistical chart is drawn according to the aggregation result;

[0143] The plurality of second historical operation data are subjected to aggregation processing, and a plurality of second behavior statistical charts are drawn according to the aggregation results;

[0144] The first behavior statistical chart and the plurality of second behavior statistical charts are subjected to graph feature extraction based on a preset graph feature extraction model, to obtain a first graph feature corresponding to the first behavior statistical chart and a second graph feature corresponding to each second behavior statistical chart;

[0145] The feature mean of the plurality of second graph features is calculated, and the third confidence of the first historical operation data is determined based on the similarity between the first graph feature and the feature mean.

[0146] In the embodiments of the present disclosure, when determining the historical rationality of the first historical operation data based on the plurality of second historical operation data, a first behavior statistical chart can be drawn according to the aggregation result of the first historical operation data, and a plurality of second behavior statistical charts can be drawn according to the aggregation result of the plurality of second historical operation data. Then, the first graph feature and the plurality of second graph features can be obtained by respectively extracting the graph features of the first behavior statistical chart and the plurality of second behavior statistical charts. Further, the feature mean of the plurality of second graph features can be calculated, and then the similarity (which can be cosine similarity) between the feature mean and the first graph feature can be calculated, and the historical rationality of the first historical operation can be determined according to the similarity, and thus the third confidence of the first historical operation data is obtained.

[0147] The fourth confidence is determined according to the association between the first historical operation data and the target operation data. Specifically, the statistical features of the first historical operation data can be obtained by operation behavior statistics, and the behavior features of the target operation data can be extracted. Then, the similarity between the behavior features and the statistical features is calculated to obtain the fourth confidence. For example, if the first historical operation data are all operations of editing element A, and the target operation data is an operation of editing element B, the corresponding features will differ in the editing object dimension, resulting in a low similarity of the features, and thus a low value of the fourth confidence is determined.

[0148] In addition, when the fifth confidence is determined based on the association between the second historical operation data and the target operation data, it is normal that the operation objects corresponding to the second historical operation data and the target operation data are inconsistent, because these operations are performed by different operators. However, according to the second historical operation data, it can be inferred that the unified goal that the overall operation data in the target online collaboration whiteboard document should achieve, for example, drawing a picture with certain semantics. At this time, if it is detected that the operation target of the editing operation corresponding to the target operation data is inconsistent with the target, it can be suspected that the editing operation corresponding to the target operation data is an abnormal operation, and at this time the fifth confidence can be determined as a low value.

[0149] In step 340, the target confidence corresponding to the target operation data is calculated according to the identity confidence and the behavior confidence, and the rationality evaluation result of the target operation data is determined according to the target confidence.

[0150] After the identity confidence and the behavior confidence corresponding to the target operation data are calculated, the target confidence corresponding to the target operation data can be further calculated according to the identity confidence and the behavior confidence. Then, the rationality evaluation result of the target operation data is determined according to the target confidence.

[0151] The specific process of calculating the target confidence according to the identity confidence and the behavior confidence can also use a dynamic weight weighting method to calculate. The specific weight value of the identity confidence and the behavior confidence can be dynamically determined according to the specific value of the identity confidence and the behavior confidence. For example, when one of the identity confidence or the behavior confidence is greater than a preset threshold, for example, 0.9, that is, it is determined that the confidence is high, a larger weight can be given to the confidence. Because when a certain confidence is very high, it can be determined to some extent that the target operation data is normal data, at this time, a larger weight can be set for the higher confidence.

[0152] In some embodiments, after calculating the target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determining the rationality evaluation result of the target operation data according to the target confidence, the method further comprises:

[0153] When the rationality evaluation result indicates that the target operation data is reasonable, updating the content of the target online collaboration whiteboard document based on the target operation data;

[0154] When the rationality evaluation result indicates that the target operation data is unreasonable, rejecting the request for updating the content of the target online collaboration whiteboard document based on the target operation data.

[0155] Specifically, after determining the rationality evaluation result of the target operation data, the data content displayed in the online collaboration whiteboard can be further updated according to the rationality evaluation result of the target operation data.

[0156] Specifically, when the rationality evaluation result indicates that the target operation data is reasonable, the content of the target online collaboration whiteboard document can be updated based on the target operation data, that is, the editing request of the target object to the element in the target online collaboration whiteboard document is received.

[0157] When the rationality evaluation result indicates that the target operation data is unreasonable, the server rejects the request for updating the content of the target online collaboration whiteboard document based on the target operation data at this time, so as to avoid the existing content in the target online collaboration whiteboard document from being destroyed, and affect the content security of the online collaboration whiteboard.

[0158] In some embodiments, after rejecting the request for updating the content of the online collaboration whiteboard document based on the target operation data when the rationality evaluation result indicates that the target operation data is unreasonable, the method further comprises:

[0159] generating abnormal prompt information based on the target operation data;

[0160] Send the abnormal prompt information to the client corresponding to the collaborative object.

[0161] In the embodiments of the present disclosure, when the server determines that the editing operation corresponding to the target operation data is an unreasonable editing operation, not only can the request of updating the content of the target online collaboration whiteboard document based on the target operation data be rejected, but further, abnormal prompt information can be generated based on the target operation data. The abnormal prompt information can prompt that there is an abnormal editing risk for a certain whiteboard element, and please pay attention to the quality of the work. Then, the server can send the abnormal prompt information to the collaborative object, so as to display the abnormal prompt label in the display interface of the target online collaboration whiteboard in the client of the collaborative object.

[0162] In some embodiments, in order to avoid the expansion of the influence of abnormal operation data, the abnormal prompt information can not be sent to all collaborative objects. Instead, the target collaborative object related to the whiteboard element corresponding to the target operation data can be determined first, and then the abnormal prompt information can be sent to the target collaborative object.

[0163] After receiving the abnormal prompt information, the target collaborative object can display the abnormal prompt label in the display interface of the target online collaboration whiteboard document. As shown in Figure 4 , it is a scene diagram of the processing method of the operation data of the online collaboration whiteboard provided by the present disclosure. As shown in the figure, in the first collaboration whiteboard display interface 400, an abnormal prompt label 410 can be displayed, and the abnormal prompt text “detecting abnormal editing behavior on element A, please pay attention to the safety of the work” is displayed in the abnormal prompt label 410. In addition, the view control 411 and the close control 412 are also displayed in the abnormal prompt label 410. The user can jump to the display area of element A to view whether the current drawing effect of element A is normal by clicking the view control 411, or if the user is currently busy with editing other elements, the close control 412 can be clicked to close the abnormal prompt label.

[0164] In some embodiments, in addition to sending the abnormal prompt information to the collaborative object to prompt the collaborative object, operation abnormal information can also be sent to the target object to prompt the target object that the current operation is abnormal. After the client corresponding to the target object receives the operation abnormal information, an operation abnormal label can be displayed in the display interface of the target online collaboration whiteboard document. As shown in Figure 5As shown, in the second collaboration whiteboard display interface 500 of the target object, an operation exception label 510 is displayed, which contains the prompt text "Your current editing operation is detected as an abnormal editing operation". In addition, the operation exception label 510 can also display a undo control 511 and a complaint control 512. The target object can click the undo control 511 to undo the target editing operation, or the target object can also click the complaint control 512 to initiate a complaint request to the online collaboration whiteboard server. The complaint request can include the target operation data and the complaint reason, complaint proof and other contents, so as to be manually audited and confirmed by the background service personnel.

[0165] In some embodiments, if the target object has multiple editing operations that are evaluated as unreasonable editing operations, for example, the target object is detected to have reached a preset number of times of unreasonable editing operations, the server can further send a warning information to the creator (administrator) of the target online collaboration whiteboard. When the administrator's client receives the warning information, a warning label can be displayed on the page of the target online collaboration whiteboard. As shown, Figure 6 As shown, in the third collaboration whiteboard display interface 600, a warning label 610 is displayed, which displays the warning information "User X has multiple abnormal operations". In addition, the warning label 610 also displays a view details control 611 and a release control 612. The administrator can click the view details control 611 to view the abnormal operation details, including the whiteboard element, operation content and operation time information; or the administrator can also click the release control 612 to release the content editing permission of the target online collaboration whiteboard document of user X.

[0166] In some embodiments, when the rationality evaluation result indicates that the target operation data is unreasonable, after rejecting the request to update the content of the online collaboration whiteboard document based on the target operation data, the method further includes:

[0167] generating an exception label according to the target operation data and the first object attribute information;

[0168] annotating the target object based on the exception label.

[0169] In the embodiments of the present disclosure, when it is determined that the rationality evaluation result of the target operation data is unreasonable, an abnormal label of the target object can be further generated according to the target operation data and the first object attribute information, and then the target object can be labeled with the abnormal label, that is, the target object is labeled based on the abnormal label. Specifically, the target object is abnormally labeled, which can specifically be adding a new label in the first object attribute information of the target object, or updating the original label of the target object.

[0170] So that the next time the identity confidence is determined according to the first object attribute information, it can be prompted that the target object has an abnormal operation behavior.

[0171] In some embodiments, after the target confidence corresponding to the target operation data is calculated according to the identity confidence and the behavior confidence, and the rationality evaluation result of the target operation data is determined according to the target confidence, the method further includes:

[0172] Obtaining execution state information corresponding to the target operation data;

[0173] When the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is unreasonable, the execution result corresponding to the target operation data in the target online collaboration whiteboard document is revoked.

[0174] In some embodiments, since the rationality evaluation of the target operation data can be performed after receiving the editing operation input by the target object, or can be a post-rationality evaluation according to the report of other collaboration objects. Therefore, when the rationality of the target operation data is evaluated and it is determined that the evaluation result of the target operation data is unreasonable, the execution state information corresponding to the target operation data can be obtained. If the execution state information indicates that the target operation data has been executed, the execution result corresponding to the target operation data in the target online collaboration whiteboard document can be further revoked. For example, the state before the editing operation corresponding to the target operation data can be traced back.

[0175] In some embodiments, when the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is unreasonable, the execution result corresponding to the target operation data in the target online collaboration whiteboard document is revoked, including:

[0176] When the execution state information indicates that the target operation data has been executed, obtaining associated operation data dependent on the target operation data;

[0177] Revoking the execution result of the target operation data and the associated operation data in the target online collaboration whiteboard document.

[0178] In the embodiments of the present disclosure, if the target operation data is unreasonable abnormal operation data, but the editing operation corresponding to the target operation data has been executed and the execution of the operation also affects other editing operations, in order to avoid the influence of the abnormal editing operation on the safety of the collaborative drawing work, the associated operation data dependent on the target operation data can be acquired first, and then the execution results corresponding to the target operation data and the associated operation data in the target online collaborative drawing board document are revoked, so as to ensure the safety of the work.

[0179] In summary, the operation data processing method of the online collaborative drawing board provided by the embodiments of the present disclosure specifically includes: acquiring target operation data received by a target online collaborative drawing board document, the target operation data being data corresponding to an editing operation of a target object on the target online collaborative drawing board document; acquiring first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and acquiring first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that edit the target online collaborative drawing board document in collaboration with the target object; determining an identity confidence of the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence of the target operation data based on the first historical operation data and the second historical operation data; calculating a target confidence of the target operation data according to the identity confidence and the behavior confidence, and determining a rationality evaluation result of the target operation data according to the target confidence.

[0180] In the embodiments of the present disclosure, when operation data of an object is received in the online collaborative drawing board, identity attribute information of an input object of the operation data can be acquired, and the identity attribute information of the input object is determined in combination with identity attribute information of other collaborative objects in the online collaborative drawing board; in addition, historical operation data of the input object of the operation data and historical operation data of a plurality of collaborative objects can be acquired, and a behavior confidence is determined according to the historical operation data of the two; further, the operation data received in the online collaborative drawing board can be subjected to rationality evaluation in combination with the identity confidence and the behavior confidence, and the operation data is subjected to input control according to the rationality evaluation result. In this way, the influence of unreasonable operation data on the safety of the work of the online collaborative drawing board can be avoided, and the safety of the work of the online collaborative drawing board is ensured.

[0181] The embodiments of the present disclosure will be described in detail in combination with specific application scenarios

[0182] As Figure 7 shown, another flowchart of the operation data processing method of the online collaborative drawing board provided by the present disclosure is shown. The embodiments will introduce the operation data processing method of the online collaborative drawing board in combination with the execution subject of each step. The method specifically includes the following steps:

[0183] Step 701, the terminal receives the editing operation of the online collaboration whiteboard input by the user, and sends the editing operation and the document update request to the server.

[0184] In the embodiments of the present disclosure, a scheme for reasonably evaluating the editing operation of the online collaboration whiteboard and controlling the editing operation based on the evaluation result to improve the work safety of the online collaboration whiteboard is provided. Specifically, when a user opens an online collaboration whiteboard application in a terminal and opens an online collaboration whiteboard document to be edited, and performs an editing operation in the online collaboration whiteboard document. The terminal can receive the editing operation of the online collaboration whiteboard input by the user, and then generate an editing event according to the editing operation, and send the editing event to the server of the online collaboration whiteboard together with a document update request of the online collaboration whiteboard.

[0185] Step 702, the server receives the editing operation and obtains user information corresponding to the editing operation and historical editing behavior information of the user.

[0186] After the online collaboration whiteboard receives the editing event corresponding to the editing operation, the user information corresponding to the current editing operation, the edited online collaboration whiteboard information (specifically, the online collaboration whiteboard document), the editing object information, the editing time information and the specific editing content information are extracted in the editing event. After obtaining the user information, the server can further obtain the historical editing behavior information of the user, wherein the historical editing behavior information of the user can include historical editing behavior information in the current online collaboration whiteboard document, or can include historical editing behavior information of the user in other online collaboration whiteboard documents.

[0187] Step 703, the server determines the user identity confidence according to the relationship between the user information and the collaboration user information of editing the online collaboration whiteboard.

[0188] After obtaining the user information, the server can first preliminarily judge the identity confidence of the user according to the user information to obtain a first confidence. Wherein, the identity information of the user is preliminarily judged, which can be specifically obtaining the identity label of the user and the detailed identity information of the user, and then inputting the identity label and the detailed identity information into the identity confidence evaluation model for evaluation to obtain the output first confidence.

[0189] Further, the server can also query other collaborative users who edit the online collaborative whiteboard together with the user according to information of the online collaborative whiteboard corresponding to the editing operation, and then obtain identity tags and detailed identity information of the collaborative users. It can be understood that the detailed identity information of the user and the other collaborative users can be information provided by the user himself / herself when registering the application, and the information is obtained based on the authorization of the user and in compliance with relevant regulations. Then, the server can determine a second confidence degree according to the similarity between the identity tag and the detailed identity information of the user and the identity tags and the detailed identity information of the collaborative users. Specifically, identity feature vectors of the user identity and identity feature average vectors of the collaborative users can be constructed respectively, and then the cosine similarity between the identity feature vector of the user and the identity feature average vectors of the collaborative users can be calculated to obtain the second confidence degree of the user identity.

[0190] Further, the first confidence degree and the second confidence degree and a preset weight coefficient can be used for weighted calculation to obtain the user identity confidence degree.

[0191] In step 704, the server determines a behavior confidence degree according to the relationship between the historical editing behavior information of the user and the historical editing behavior information of the collaborative users.

[0192] After obtaining the historical editing behavior information of the user, the server can first analyze the historical editing behavior information (total editing behavior in the current online collaborative whiteboard document and other online collaborative whiteboard documents) of the user to obtain a third confidence degree, which is a behavior confidence degree based on the attributes of the user and irrelevant to the content (theme) of the online collaborative whiteboard and the historical editing behavior information of the collaborative users.

[0193] Then, the server can further determine a behavior confidence degree of the current editing operation according to the relationship between the historical behavior information of the user in the current online collaborative whiteboard document and the current editing operation to obtain a fourth confidence degree. The fourth confidence degree is a confidence degree for evaluating the rationality of the current editing operation based on the operation habit of the user in the online collaborative whiteboard document, and is irrelevant to the historical editing behavior information of the collaborative users.

[0194] Further, the server can determine a behavior confidence degree of the current editing operation according to the relationship between the historical behavior information of the collaborative users in the current online collaborative whiteboard and the current editing operation to obtain a fifth confidence degree. It can be understood that the fifth confidence degree is the association relationship between the current editing operation and the total operation data of the current online collaborative whiteboard document, i.e., a confidence degree for evaluating the rationality of the current editing operation based on the total operation data (which can also be understood as the document content) of the current online collaborative whiteboard document.

[0195] After the third confidence, the fourth confidence and the fifth confidence are calculated, the server can further calculate the behavior confidence corresponding to the current editing operation according to the third confidence, the fourth confidence and the fifth confidence.

[0196] The specific process of calculating the behavior confidence corresponding to the current editing operation according to the third confidence, the fourth confidence and the fifth confidence can be to first obtain the preset weight coefficients corresponding to the third confidence, the fourth confidence and the fifth confidence, and then perform weighted calculation to obtain the overall behavior confidence of the current editing operation.

[0197] In step 705, the server calculates the confidence of the editing operation according to the user identity confidence and the behavior confidence.

[0198] Further, after the user identity confidence and the behavior confidence corresponding to the current editing operation are calculated, the server can further perform weighted calculation on the two confidences to obtain the overall confidence of the current editing operation.

[0199] In step 706, the server determines the rationality of the editing operation according to the confidence of the editing operation.

[0200] After the confidence of the current editing operation is calculated, a preset confidence threshold can be obtained, and then the confidence is compared with the preset confidence threshold. When the confidence of the current editing operation is greater than the preset confidence threshold, it can be determined that the rationality evaluation result of the current editing operation is reasonable. Conversely, when the confidence of the current editing operation is not greater than the preset confidence threshold, it can be determined that the rationality evaluation result of the current editing operation is unreasonable.

[0201] In step 707, when the editing operation is reasonable, the server updates the content of the online collaboration whiteboard according to the editing operation.

[0202] If the rationality evaluation result of the editing operation is reasonable, the server can update the content of the online collaboration whiteboard according to the received editing operation.

[0203] In step 708, when the editing operation is unreasonable, the server sends an abnormal prompt information to the terminal.

[0204] If the rationality evaluation result of the editing operation is unreasonable, the server can send an abnormal prompt information to the terminal sending the editing operation to prompt the user that the current editing operation is abnormal, and to remind the user to standardize the editing behavior.

[0205] In step 709, the terminal receives the abnormal prompt information and displays a prompt tag in the online collaboration whiteboard.

[0206] When the terminal receives the abnormal prompt information, a prompt label can be displayed in the online collaboration board to prompt the user.

[0207] It can be understood that during the use of the online collaboration board, the editing operation of the user is performed simultaneously by multiple people, so that the server can simultaneously receive multiple editing operations sent by multiple terminals. At this time, the server can perform multi-threaded editing operation rationality analysis, each thread evaluating the editing operation sent by one terminal, thereby improving the accuracy of editing operation rationality evaluation.

[0208] To sum up, the operation data processing method of the online collaboration board provided by the embodiments of the present disclosure specifically includes obtaining target operation data received by a target online collaboration board document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration board document; obtaining first object attribute information of the target object and second object attribute information of multiple collaborative objects, and obtaining first historical operation data of the target object and second historical operation data of the multiple collaborative objects, the collaborative objects being objects that edit the target online collaboration board document in collaboration with the target object; determining an identity confidence corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence corresponding to the target operation data based on the first historical operation data and the second historical operation data; calculating a target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determining a rationality evaluation result of the target operation data according to the target confidence.

[0209] In the embodiments of the present disclosure, when the operation data of an object is received in the online collaboration board, the identity attribute information of the input object of the operation data can be obtained, and the identity attribute information of other collaborative objects in the online collaboration board is combined to determine the identity confidence of the input object. In addition, the historical operation data of the input object of the operation data and the historical operation data of multiple collaborative objects can also be obtained, and the behavior confidence is determined according to the historical operation data of both. Further, the identity confidence and the behavior confidence can be combined to perform rationality evaluation on the operation data received in the online collaboration board, and the input control of the operation data is performed according to the rationality evaluation result. In this way, the influence of unreasonable operation data on the security of the work of the online collaboration board can be avoided, and the security of the work of the online collaboration board is ensured.

[0210] Device and equipment description of the embodiments of the present disclosure

[0211] It can be understood that, although each step in each of the above flowcharts is displayed in sequence according to the representation of the arrow, these steps are not necessarily executed in the order represented by the arrow. Unless otherwise specified in the embodiments, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least part of the steps in the above flowcharts can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately executed with at least part of other steps or steps or stages in other steps.

[0212] Figure 8 The structural schematic diagram of the operation data processing apparatus 800 of the online collaboration whiteboard provided by the embodiments of the present disclosure is provided. The operation data processing apparatus 800 comprises:

[0213] The first acquisition unit 810 is configured to acquire target operation data received by a target online collaboration whiteboard document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration whiteboard document;

[0214] The second acquisition unit 820 is configured to acquire first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and acquire first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative object being an object that collaboratively edits the target online collaboration whiteboard document with the target object;

[0215] The first determination unit 830 is configured to determine an identity confidence corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determine a behavior confidence corresponding to the target operation data based on the first historical operation data and the second historical operation data;

[0216] The second determination unit 840 is configured to calculate a target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determine a rationality evaluation result of the target operation data according to the target confidence.

[0217] Optionally, in some embodiments, the operation data processing apparatus of the online collaboration whiteboard provided by the present disclosure further comprises:

[0218] The update sub-unit is configured to, when the rationality evaluation result indicates that the target operation data is reasonable, perform content update on the target online collaboration whiteboard document based on the target operation data;

[0219] The control sub-unit is configured to, when the rationality evaluation result indicates that the target operation data is unreasonable, reject a request for content update on the target online collaboration whiteboard document based on the target operation data.

[0220] Optionally, in some embodiments, the operation data processing apparatus of the online collaboration whiteboard provided by the present disclosure further comprises:

[0221] The first generation subunit is configured to generate abnormal prompt information based on the target operation data.

[0222] The sending subunit is configured to send the abnormal prompt information to the client corresponding to the collaboration object.

[0223] Optionally, in some embodiments, the operation data processing apparatus of the online collaboration whiteboard provided by the present disclosure further comprises:

[0224] The second generation subunit is configured to generate an abnormal label according to the target operation data and the first object attribute information.

[0225] The labeling subunit is configured to label the target object based on the abnormal label.

[0226] Optionally, in some embodiments, the operation data processing apparatus of the online collaboration whiteboard provided by the present disclosure further comprises:

[0227] The acquisition subunit is configured to acquire execution state information corresponding to the target operation data.

[0228] The revocation subunit is configured to, when the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is not reasonable, revoke the execution result of the target operation data corresponding to the target operation data in the target online collaboration whiteboard document.

[0229] Optionally, in some embodiments, the revocation subunit comprises:

[0230] The acquisition module is configured to, when the execution state information indicates that the target operation data has been executed, acquire associated operation data dependent on the target operation data.

[0231] The revocation module is configured to revoke the execution result of the target operation data and the associated operation data in the target online collaboration whiteboard document.

[0232] Optionally, in some embodiments, the first determination unit comprises:

[0233] The extraction subunit is configured to extract first login address information and first identity label information from the first object attribute information, and extract second login address information and second identity label information from the second object attribute information.

[0234] The first determination subunit is configured to cluster the second login address information to obtain a plurality of login address classes, and determine a first confidence degree according to a first subordination relationship between the first login address information and the plurality of login address classes.

[0235] The second determining sub-unit is configured to cluster the second identity label information to obtain a plurality of identity label classes, and determine a second confidence degree according to a second subordination relationship between the first identity label information and the plurality of identity label classes.

[0236] The first calculating sub-unit is configured to calculate an identity confidence degree corresponding to the target operation data according to the first confidence degree and the second confidence degree.

[0237] Optionally, in some embodiments, the first calculating sub-unit comprises:

[0238] The determining module is configured to determine a first weight corresponding to the first confidence degree and a second weight corresponding to the second confidence degree according to the first subordination relationship, the second subordination relationship and a preset subordination relationship matching rule;

[0239] The first calculating module is configured to perform weighted calculation on the first confidence degree and the second confidence degree based on the first weight and the second weight to obtain the identity confidence degree corresponding to the target operation data.

[0240] Optionally, in some embodiments, the first determining unit can further comprise:

[0241] The third determining sub-unit is configured to determine a third confidence degree according to a historical rationality of the first historical operation data;

[0242] The fourth determining sub-unit is configured to determine a fourth confidence degree according to an association between the first historical operation data and the target operation data;

[0243] The fifth determining sub-unit is configured to determine a fifth confidence degree based on an association between the second historical operation data and the target operation data;

[0244] The second calculating sub-unit is configured to calculate a behavior confidence degree corresponding to the target operation data according to the third confidence degree, the fourth confidence degree and the fifth confidence degree.

[0245] Optionally, in some embodiments, the third determining sub-unit comprises:

[0246] The first aggregating module is configured to perform multi-dimension aggregation processing on the first historical operation data, and generate a first behavior vector according to multi-dimension aggregation values;

[0247] The second aggregating module is configured to perform multi-dimension aggregation processing on the plurality of second historical operation data respectively, and generate a plurality of second behavior vectors according to multi-dimension aggregation values;

[0248] The clustering module is configured to perform clustering processing on the plurality of second behavior vectors to obtain a clustering center vector.

[0249] The second calculation module is configured to calculate a cosine similarity between the first behavior vector and the cluster center vector, and determine a third confidence of the first historical operation data according to the cosine similarity.

[0250] Optionally, in some embodiments, the third determination sub-unit comprises:

[0251] The first drawing module is configured to aggregate the first historical operation data, and draw a first behavior statistical chart according to an aggregation result.

[0252] The second drawing module is configured to aggregate the plurality of second historical operation data, and draw a plurality of second behavior statistical charts according to an aggregation result.

[0253] The extraction module is configured to perform graph feature extraction on the first behavior statistical chart and the plurality of second behavior statistical charts respectively based on a preset graph feature extraction model, to obtain a first graph feature corresponding to the first behavior statistical chart and a second graph feature corresponding to each second behavior statistical chart.

[0254] The third calculation module is configured to calculate a feature mean of the plurality of second graph features, and determine a third confidence of the first historical operation data based on a similarity between the first graph feature and the feature mean.

[0255] In the embodiments of the present application, the term "module" or "unit" refers to a computer program or a part of a computer program with a predetermined function, and works together with other related parts to achieve a predetermined target, and can be implemented entirely or partially by using software, hardware (such as a processing circuit or a memory) or a combination thereof. Similarly, one processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be a part of an overall module or unit that includes the functions of the module or unit.

[0256] Reference Figure 9 , Figure 9 A structure block diagram of a terminal 140 for implementing the operation data processing method of the online collaboration whiteboard of the embodiments of the present disclosure, the terminal 140 includes: a radio frequency (Radio Frequency, RF for short) circuit 1410, a memory 915, an input unit 930, a display unit 940, a sensor 950, an audio circuit 960, a wireless fidelity (wireless fidelity, WiFi for short) module 970, a processor 980, and a power supply 990, and the like. Those skilled in the art can understand that the terminal 140 structure shown does not constitute a limitation on mobile phones or computers, and can include more or fewer components than shown, or combine certain components, or different component arrangements. Figure 9 The terminal 140 structure shown does not constitute a limitation on mobile phones or computers, and can include more or fewer components than shown, or combine certain components, or different component arrangements.

[0257] The RF circuit 910 can be used for receiving and sending signals in the process of information or call, in particular, receiving the downlink information from the base station and processing by the processor 980; in addition, sending the uplink data to the base station.

[0258] The memory 915 can be used for storing software programs and modules, and the processor 980 can execute various functions and document editing of the terminal by running the software programs and modules stored in the memory 915.

[0259] The input unit 930 can be used for receiving inputted digital or character information, and generating key signal input related to the setting and function control of the terminal. Specifically, the input unit 930 can include a touch panel 931 and other input devices 932.

[0260] The display unit 940 can be used for displaying inputted information or provided information and various menus of the terminal. The display unit 940 can include a display panel 941.

[0261] The audio circuit 960, the speaker 961 and the microphone 962 can provide an audio interface.

[0262] In the embodiment, the processor 980 included in the terminal 140 can execute the operation data processing method of the online collaboration whiteboard of the previous embodiment.

[0263] The terminal 140 of the embodiment of the present disclosure includes but is not limited to a mobile phone, a computer, a smart voice interactive device, a smart home appliance, a vehicle-mounted terminal, an aircraft, etc.

[0264] Figure 10 A structural block diagram of part of the server 110 for implementing the operation data processing method of the online collaboration whiteboard of the embodiment of the present disclosure. The server 110 can have a large difference due to different configurations or performances, and can include one or more central processing units (CPUs) 1022 (for example, one or more processors) and a storage device 1032, one or more storage media 1030 (for example, one or more mass storage devices) for storing application programs 1042 or data 1044. Among them, the storage device 1032 and the storage medium 1030 can be temporary storage or persistent storage. The programs stored in the storage medium 1030 can include one or more modules (not shown in the figure), and each module can include a series of instruction operations in the server 110. Further, the central processing unit 1022 can be configured to communicate with the storage medium 1030 and execute the series of instruction operations in the storage medium 1030 on the server 110.

[0265] The server 110 can also include one or more power supplies 1026, one or more wired or wireless network interfaces 1050, one or more input / output interfaces 1058, and / or one or more operating systems 1041, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, and the like.

[0266] The central processing unit 1022 in the server 110 can be configured to execute the operation data processing method of the online collaboration whiteboard according to the embodiments of the present disclosure.

[0267] The embodiments of the present disclosure also provide a storage medium for storing program code, the program code being used to execute the operation data processing method of the online collaboration whiteboard according to the various embodiments.

[0268] The embodiments of the present disclosure also provide a computer program product including a computer program. The processor of the computer device reads the computer program and executes, so that the computer device executes the operation data processing method of the online collaboration whiteboard.

[0269] The terms "first", "second", "third", "fourth" and the like in the description of the present disclosure and the above drawings, if any, are used to distinguish similar objects, and do not necessarily indicate a particular order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described herein can be implemented in other than the order illustrated or described herein. In addition, the terms "include" and "contain" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device containing a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0270] It should be understood that in the present disclosure, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases of only A, only B and A and B existing at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0271] It should be understood that, in the description of the embodiments of the present disclosure, the meaning of multiple (or multiple items) is two or more, greater than, less than, more than, and the like are not included in the number, above, below, and the like are included in the number.

[0272] In several embodiments provided by the present disclosure, it should be understood that the disclosed system, device and method can be implemented by other manners. For example, the above-described device embodiments are only schematic, and the division of the units is only a logical function division, and other division manners can be adopted in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0273] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0274] In addition, each functional unit in each embodiment of the present disclosure can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0275] If the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on such understanding, the technical solutions of the present disclosure essentially or the part that makes a contribution to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the embodiments of the present disclosure. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0276] It should also be understood that the various embodiments provided by the present disclosure can be combined in any manner to achieve different technical effects.

[0277] The foregoing is a detailed description of embodiments of the present disclosure, but the present disclosure is not limited to the above-described embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present disclosure, and such equivalent modifications or substitutions are included in the scope defined by the claims of the present disclosure.

Claims

1. An operation data processing method of an online collaboration board, characterized by, The method comprises: obtaining target operation data received by a target online collaboration whiteboard document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration whiteboard document; obtaining first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and obtaining first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that collaboratively edit the target online collaboration whiteboard document with the target object; determining an identity confidence corresponding to the target operation data based on the first object attribute information and the second object attribute information, and determining a behavior confidence corresponding to the target operation data based on the first historical operation data and the second historical operation data; calculating a target confidence corresponding to the target operation data according to the identity confidence and the behavior confidence, and determining a rationality evaluation result of the target operation data according to the target confidence.

2. The method of claim 1, wherein, After the target confidence corresponding to the target operation data is calculated according to the identity confidence and the behavior confidence, and the rationality evaluation result of the target operation data is determined according to the target confidence, the method further comprises: when the rationality evaluation result indicates that the target operation data is reasonable, updating content of the target online collaboration whiteboard document based on the target operation data; when the rationality evaluation result indicates that the target operation data is unreasonable, rejecting a request to update content of the target online collaboration whiteboard document based on the target operation data.

3. The method of claim 2, wherein, After the request to update content of the online collaboration whiteboard document based on the target operation data is rejected when the rationality evaluation result indicates that the target operation data is unreasonable, the method further comprises: generating abnormal prompt information based on the target operation data; sending the abnormal prompt information to a client corresponding to the collaborative object.

4. The method of claim 2, wherein, After the request to update content of the online collaboration whiteboard document based on the target operation data is rejected when the rationality evaluation result indicates that the target operation data is unreasonable, the method further comprises: generating an abnormal label according to the target operation data and the first object attribute information; labeling the target object based on the abnormal label.

5. The method of claim 2, wherein, After the target confidence corresponding to the target operation data is calculated according to the identity confidence and the behavior confidence, and the rationality evaluation result of the target operation data is determined according to the target confidence, the method further comprises: obtaining execution state information corresponding to the target operation data; when the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is unreasonable, undoing an execution result corresponding to the target operation data in the target online collaboration whiteboard document.

6. The method of claim 5, wherein, When the execution state information indicates that the target operation data has been executed and the rationality evaluation result determines that the target operation data is unreasonable, the method further comprises: When the execution state information indicates that the target operation data has been executed, obtaining associated operation data dependent on the target operation data; Reversing execution results of the target operation data and the associated operation data in the target online collaboration whiteboard document.

7. The method of claim 1, wherein, The identity confidence corresponding to the target operation data is determined based on the first object attribute information and the second object attribute information, including: First login address information and first identity tag information are extracted from the first object attribute information, and second login address information and second identity tag information are extracted from the second object attribute information; The second login address information is clustered to obtain a plurality of login address classes, and a first confidence is determined according to a first subordination relationship between the first login address information and the plurality of login address classes; The second identity tag information is clustered to obtain a plurality of identity tag classes, and a second confidence is determined according to a second subordination relationship between the first identity tag information and the plurality of identity tag classes; The identity confidence corresponding to the target operation data is calculated according to the first confidence and the second confidence.

8. The method of claim 7, wherein, The identity confidence corresponding to the target operation data is calculated according to the first confidence and the second confidence, including: The first weight corresponding to the first confidence and the second weight corresponding to the second confidence are determined according to the first subordination relationship, the second subordination relationship, and a preset subordination relationship matching rule; The first confidence and the second confidence are weighted and calculated based on the first weight and the second weight to obtain the identity confidence corresponding to the target operation data.

9. The method of claim 1, wherein, The behavior confidence corresponding to the target operation data is determined based on the first historical operation data and the second historical operation data, including: A third confidence is determined according to the historical rationality of the first historical operation data; A fourth confidence is determined according to the relevance between the first historical operation data and the target operation data; A fifth confidence is determined based on the relevance between the second historical operation data and the target operation data; The behavior confidence corresponding to the target operation data is calculated according to the third confidence, the fourth confidence, and the fifth confidence.

10. The method of claim 9, wherein, The third confidence is determined according to the historical rationality of the first historical operation data, including: The first historical operation data is aggregated in multiple dimensions, and a first behavior vector is generated according to the aggregated values of multiple dimensions; The plurality of second historical operation data are respectively aggregated in the plurality of dimensions, and a plurality of second behavior vectors are generated according to the aggregated values of multiple dimensions; The plurality of second behavior vectors are clustered to obtain a cluster center vector; The cosine similarity between the first behavior vector and the cluster center vector is calculated, and the third confidence of the first historical operation data is determined according to the cosine similarity.

11. The method of claim 9, wherein, The third confidence is determined according to the historical rationality of the first historical operation data, including: The first historical operation data is aggregated, and a first behavior statistical chart is drawn according to the aggregation result; aggregate the plurality of second historical operation data, and draw a plurality of second behavior statistical charts according to an aggregation result; perform graph feature extraction on the first behavior statistical chart and the plurality of second behavior statistical charts based on a preset graph feature extraction model, to obtain a first graph feature corresponding to the first behavior statistical chart and a second graph feature corresponding to each second behavior statistical chart; calculate a feature mean of the plurality of second graph features, and determine a third confidence degree of the first historical operation data based on a similarity between the first graph feature and the feature mean.

12. An operation data processing apparatus of an online collaboration canvas, characterized by comprising: The apparatus comprises: a first obtaining unit configured to obtain target operation data received by a target online collaboration whiteboard document, the target operation data being data corresponding to an editing operation of a target object on the target online collaboration whiteboard document; a second obtaining unit configured to obtain first object attribute information of the target object and second object attribute information of a plurality of collaborative objects, and to obtain first historical operation data of the target object and second historical operation data of the plurality of collaborative objects, the collaborative objects being objects that collaboratively edit the target online collaboration whiteboard document with the target object; a first determining unit configured to determine an identity confidence degree corresponding to the target operation data based on the first object attribute information and the second object attribute information, and to determine a behavior confidence degree corresponding to the target operation data based on the first historical operation data and the second historical operation data; a second determining unit configured to calculate a target confidence degree corresponding to the target operation data according to the identity confidence degree and the behavior confidence degree, and to determine a rationality evaluation result of the target operation data according to the target confidence degree.

13. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the operation data processing method of the online collaboration whiteboard according to any one of claims 1 to 11.

14. A computer readable storage medium, the storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the operation data processing method of the online collaboration whiteboard according to any one of claims 1 to 11.

15. A computer program product, comprising a computer program, the computer program being read and executed by a processor of a computer device, so that the computer device executes the operation data processing method of the online collaboration whiteboard according to any one of claims 1 to 11.

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