Screen sharing method, system, device and medium

Abstract

The present application discloses a screen sharing method, system, device and medium, which relates to the field of intelligent recognition technology. The method includes: receiving a pre-sharing interface and customer information sent by a business end; obtaining interface information in the pre-sharing interface; inputting the interface information and customer information into a preset neural network model to obtain term definitions output by the neural network model; integrating the term definitions in the pre-sharing interface to obtain a sharing interface; and sending the sharing interface to the client and the business end. The technical solution provided by the present application can help customers understand the professional terms in the shared content sent by the salesperson during the business handling process. At the same time, the salesperson can also provide further explanations to customers based on the term definitions in the sharing interface, so that customers have a clearer understanding of the business content and improve their business experience.

Description

Technical Field

[0001] The present application relates to the field of intelligent recognition technology, and in particular to a screen sharing method, system, device and medium. Background Art

[0002] When handling financial business, in order to improve business handling efficiency, sales staff often choose to share the screen remotely with customers to introduce relevant details or agency products.

[0003] In related technologies, when customers participate in screen sharing, they often encounter problems with not fully understanding the shared content, especially some professional terms. However, oral explanations by business personnel are often not clear and specific enough, which is not conducive to customer understanding and affects customer experience and the progress of business processing. Summary of the invention

[0004] In order to solve or partially solve the problems existing in the related art, the present application provides a screen sharing method, system, device and medium, which can display corresponding term definitions in the sharing interface when screen sharing is performed to help customers understand professional terms.

[0005] A first aspect of the present application provides a screen sharing method, characterized by comprising:

[0006] Receive the pre-shared interface and customer information sent by the business end;

[0007] Acquiring interface information in the pre-shared interface;

[0008] Inputting the interface information and customer information into a preset neural network model to obtain the term interpretation output by the neural network model;

[0009] Integrating the term definitions into the pre-shared interface to obtain a shared interface;

[0010] The shared interface is sent to the client and the service end.

[0011] Optionally, before integrating the term interpretation into the pre-sharing interface to obtain the sharing interface, the method further includes:

[0012] In the pre-sharing interface, a target sentence corresponding to the term definition is marked.

[0013] Optionally, integrating the term interpretation into the pre-sharing interface to obtain a sharing interface includes:

[0014] Based on the term interpretation, construct a hyperlink to the target sentence;

[0015] The hyperlink is added to the pre-shared interface to obtain a shared interface.

[0016] Optionally, integrating the term interpretation into the pre-sharing interface to obtain a sharing interface includes:

[0017] generating a semantic interface displaying the definitions of the terms;

[0018] The semantic interface and the pre-shared interface are spliced ​​to obtain a shared interface.

[0019] Optionally, integrating the term interpretation into the pre-sharing interface to obtain a sharing interface includes:

[0020] Determine a target area in the pre-sharing interface; the target area is a blank area in the pre-sharing interface;

[0021] Adding the term definition to the target area obtains a sharing interface.

[0022] Optionally, the method further comprises:

[0023] Receive and store feedback information sent by the client or the service end, and send the feedback information to the agent end; the feedback information includes the sentence to be interpreted and / or the interpretation of the term.

[0024] Optionally, sending the sentence to be interpreted to the agent terminal includes:

[0025] The sentence interpretation corresponding to the sentence to be interpreted sent by the agent end is received, and forwarded to the client end and the service end.

[0026] A second aspect of the present application provides a screen sharing system, comprising:

[0027] Information processing module, used for:

[0028] Receive the pre-shared interface and customer information sent by the business end;

[0029] Acquiring interface information in the pre-shared interface;

[0030] An interpretation acquisition module, used for inputting the interface information and customer information into a preset neural network model to obtain the term interpretation output by the neural network model;

[0031] Interface processing module, used for:

[0032] Integrating the term definitions into the pre-shared interface to obtain a shared interface;

[0033] The shared interface is sent to the client and the service end.

[0034] A third aspect of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described above when executing the computer program.

[0035] A fourth aspect of the present application provides a computer-readable storage medium, characterized in that a computer program is stored thereon, and the computer program implements the method described above when executed.

[0036] The screen sharing method provided in the present application can obtain interface information according to the pre-shared interface after receiving the pre-shared interface and customer information sent by the service end, and further input the interface information and customer information into a preset neural network model to obtain the term interpretation output by the neural network model.

[0037] Then, the terminology interpretation is integrated into the pre-sharing interface to obtain the sharing interface, and finally the sharing interface is sent to the client and the business end. The technical solution provided by this application can help customers understand the professional terms in the shared content sent by the salesperson during the business handling process. At the same time, the salesperson can also provide further explanations to customers based on the terminology interpretation in the sharing interface, so that customers have a clearer understanding of the business content and improve their business experience.

[0038] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0040] Figure 1 is a flowchart of a screen sharing method shown in an embodiment of the present application;

[0041] Figure 2 is a schematic diagram of a sharing interface shown in an embodiment of the present application;

[0042] Figure 3 is a flowchart of another screen sharing method shown in an embodiment of the present application;

[0043] Figure 4 is a flowchart of another screen sharing method shown in an embodiment of the present application;

[0044] Figure 5 is a flowchart of another screen sharing method shown in an embodiment of the present application;

[0045] Figure 6 is a schematic diagram of the module structure of the screen sharing system shown in an embodiment of the present application;

[0046] Figure 7 It is a schematic diagram of the structure of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0047] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0048] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0049] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0050] The embodiments of the present application are described below in conjunction with the accompanying drawings.

[0051] The purpose of this application is to provide a screen sharing method, system, device and medium, which can add preset interpretations according to the shared content during the screen sharing process to help customers understand the terms.

[0052] The above screen sharing method can be applied to the server in the remote assistance system. Figure 1 , Figure 1 The following is a flowchart of a screen sharing method. The screen sharing method may include the following steps:

[0053] Step 101: Receive the pre-sharing interface and customer information sent by the service end.

[0054] During the process of handling banking business, when the distance between the salesperson and the customer is far or face-to-face communication is difficult, the salesperson can choose to start remote screen sharing to handle business or introduce products to the customer; in the application, after the salesperson determines the content to be shared on the business side, such as choosing to share a certain document through screen projection, the business side determines the operation based on the shared content performed by the salesperson to generate a corresponding pre-sharing interface, and sends the pre-sharing interface to the server; at the same time, the salesperson can also enter customer information on the business side, and the business side will send the customer information and the pre-sharing interface to the server together.

[0055] The customer information may include, for example, the customer's age, education background, occupation, and work experience.

[0056] Step 102: Obtain interface information in the pre-shared interface.

[0057] After receiving the pre-shared interface sent by the service end, the server can obtain the corresponding interface information, which can be either text information or image information in the pre-shared interface; the server can obtain text information by extracting text in the pre-shared interface, or obtain image information by intercepting the current frame image of the pre-shared interface. It should be noted that when the interface information is image information, the image should contain text content.

[0058] Step 103: Input the interface information and customer information into a preset neural network model to obtain the term interpretation output by the neural network model.

[0059] After obtaining the interface information, the server can input it together with the customer information into a pre-trained neural network model, and then the neural network model outputs the corresponding preset term definitions.

[0060] Step 104: Integrate the term definitions into the pre-sharing interface to obtain a sharing interface.

[0061] In the application, the professional terms displayed in the pre-shared interface are zero, one or more, and correspondingly, the term definitions output by the neural network model based on the interface information and customer information are also zero, one or more; when the term definitions output by the neural network model are one or more, the server adds the term definitions to the corresponding pre-shared interface to obtain a shared interface displaying the term definitions; when the term definitions output by the neural network model are zero, the corresponding pre-shared interface can be used as a shared interface.

[0062] Step 105: Send the sharing interface to the client and the service end.

[0063] After obtaining the shared interface, the server sends the shared interface to the client and the business end respectively, so that the salesperson can communicate with the customer based on the shared interface; it can be understood that when the server sends the shared interface to the business end, it replaces the pre-shared interface previously displayed on the screen of the business end.

[0064] In the embodiments of the present application, the problem that customers do not have a good understanding of the professional terms in the content shared by the salesperson can be effectively solved; when the content that the salesperson prepares to share with the customer (such as brochures, agreements and other documents) contains professional terms, that is, professional terms are displayed in the pre-sharing interface, the above-mentioned screen sharing method provided by the present application can be used to obtain a sharing interface that displays the terminology definitions to replace the pre-sharing interface; the salesperson communicates with the customer through the sharing interface, which can help the customer understand the relevant details more easily and deepen the impression, and the salesperson can also give further explanations to the customer based on the relevant terminology definitions, which reduces customer doubts and improves the customer experience.

[0065] In one embodiment, the above-mentioned step of integrating the term definitions in the pre-sharing interface to obtain the sharing interface may include the following steps:

[0066] Generate semantic interfaces that display term definitions;

[0067] The shared interface is obtained by concatenating the semantic interface and the pre-shared interface.

[0068] See also Figure 2 , Figure 2 Schematic diagram of the sharing interface, 201 is the pre-sharing interface, 202 is the semantic interface; in the application, when the customer views the information in the pre-sharing interface 201 on the client, if he has any questions about the professional terms involved, he can view the corresponding term definitions in the semantic interface 202 to deepen his understanding.

[0069] In one embodiment, the above-mentioned step of integrating the term definitions in the pre-sharing interface to obtain the sharing interface may include the following steps:

[0070] Determine the target area in the pre-shared interface;

[0071] Adding term definitions to the target area results in a shared interface.

[0072] Among them, the target area is the blank area in the pre-shared interface; after obtaining the term definition, the server can search for a suitable blank area in the pre-shared interface, such as the bottom and side of the interface. When the blank area is larger than the estimated area occupied by the term definition, the blank area can be used as the target area and the term definition can be added to the target area.

[0073] In one embodiment, before integrating the term definitions in the pre-sharing interface and obtaining the sharing interface, the following operations may be performed:

[0074] In the pre-sharing interface, target sentences corresponding to the term definitions are marked.

[0075] The target sentence is one or more preset professional terms displayed in the pre-shared interface. The server can search for the preset professional terms based on the interface information obtained above to obtain the target sentence in the pre-shared interface, or it can perform semantic search based on the term interpretation output by the neural network model to find the corresponding target sentence in the pre-shared interface. When marking the target sentence, the target sentence can be bolded, filled with color, underlined, etc., which can be flexibly set according to the actual situation.

[0076] In the embodiment of the present application, by marking the target sentence, it can serve as a reminder to the customer, thereby preventing the customer from quickly skipping over some professional terms due to insufficient understanding of the customer, resulting in ignoring important information.

[0077] Furthermore, the above-mentioned integration of term definitions in the pre-sharing interface to obtain the sharing interface may also include the following steps:

[0078] Based on the definition of the term, construct a hyperlink to the target sentence;

[0079] Add a hyperlink to the pre-shared interface to get the shared interface.

[0080] After obtaining the term definition, you can also create a hyperlink to display the term definition corresponding to the target sentence; in the application, the salesperson can click on the target sentence in the sharing interface on the business side to display the corresponding term definition to the customer.

[0081] The following is a further introduction to the above neural network model; the following operations can be performed when training the neural network model:

[0082] Input the training samples into the neural network model to obtain the interpretation prediction results output by the neural network model;

[0083] Obtaining prediction deviation data based on interpretation prediction results and preset term interpretation reference data;

[0084] Adjust the parameters of the neural network model based on the prediction deviation data.

[0085] When training the neural network model, training samples are first obtained from the training sample set as the input of the neural network model, and then the term interpretation corresponding to each training sample (term interpretation reference data) is used as the output matching target of the neural network model. The prediction deviation data is further obtained based on the prediction results and reference data, so as to train the weight coefficient of the neural network model and finally obtain a trained neural network model.

[0086] Among them, the above-mentioned training samples include: customer information and documents and / or pictures with financial business information; documents or pictures with financial business information are the shared content that the salesperson will involve when sharing the screen with the customer, that is, representing the above-mentioned interface information; customer information includes: customer's name, age, education, occupation, work experience, historical business handling information, etc.; term interpretation is the preset text interpretation and / or the address information of the interpretation video.

[0087] The embodiment of the present application selects a neural network for training, so as to use the trained neural network model to predict the definition of the term corresponding to the pre-sharing interface sent by the service end.

[0088] Taking the convolutional neural network (CNN) as an example, the convolutional neural network includes: an input layer, an output layer, and multiple hidden layers; among which, the hidden layer includes a series of convolutional layers, pooling layers, and fully connected layers. When training the convolutional neural network, training samples can be randomly selected from the training sample set, and the training samples can be input into the convolutional neural network to extract feature information, and the term interpretation label corresponding to the training sample is used as the output matching target of the convolutional neural network. After that, the convolutional neural network is repeatedly trained through forward propagation, back propagation, and weight update until the weight coefficient of the convolutional neural network converges to the preset range; after the final training determines the weight of the convolutional neural network, the weight parameters and the corresponding network structure can be used as the preset neural network model.

[0089] In the application, the preset neural network model can output the corresponding term interpretation according to the interface information and customer information; as mentioned above, the term interpretation can be a text interpretation and / or the address information of the interpretation video, and the neural network model can output different forms of prediction results according to the customer information, that is, term interpretations in different forms (font size, text, video address); for example, output text interpretations in different font sizes according to the customer's age; output text interpretations or the address information of the interpretation video according to the customer's historical business handling situation, education and work experience. Among them, text interpretations can also be divided into professional text interpretations and ordinary text interpretations. Professional text interpretations are related definitions of professional terms, while ordinary text interpretations include not only the definitions of professional terms, but also corresponding examples.

[0090] According to the different forms of prediction results output by the neural network model based on the customer information, the output matching target (term interpretation label) can be adjusted and determined during the model training process; for example, the customer information in a training sample includes the customer's work experience. If the work experience indicates that the customer has worked in financial business or related business, the term interpretation label in the form of text interpretation can be set accordingly. Furthermore, text interpretations of different font sizes can be set as term interpretation labels according to the customer's age; conversely, if the customer has not worked in related work, the education information in the customer information can be further referred to, and the term interpretation label can be set as text interpretation or the address information of the interpretation video. Among them, the interpretation video is the corresponding explanation video produced in advance according to different professional terms; in the application, when the customer has doubts about the professional terminology, the salesperson can find the corresponding explanation video through the address information of the interpretation video to answer the customer's questions.

[0091] Furthermore, considering the work experience of the salesperson, when the salesperson lacks work experience, it is difficult to provide clear explanations to customers based on text interpretation alone. Therefore, in order to avoid this problem, the training samples in the model training process can also include business information; among which, the business information can exemplarily include the salesperson's years of work, position level, work performance rating and other information.

[0092] Accordingly, in one embodiment, see Figure 3 , Figure 3 The following is a flowchart of another screen sharing method according to an embodiment of the present application. The screen sharing method may include the following steps:

[0093] Step 301: Receive the pre-sharing interface, customer information and service information sent by the service end.

[0094] Step 302: Obtain interface information in the pre-shared interface.

[0095] Step 303: Input the interface information, customer information and business information into the preset neural network model to obtain the term interpretation output by the neural network model.

[0096] Step 304: Integrate the term definitions in the pre-sharing interface to obtain a sharing interface.

[0097] Step 305: Send the sharing interface to the client and the service end.

[0098] Among them, the execution operations of the above steps 301, 302, 303, 304 and 305 can refer to the aforementioned steps 101, 102, 103, 104 and 105 respectively; the relevant introduction of the neural network model can also refer to the aforementioned content, which will not be repeated here.

[0099] It should be further explained that, considering the actual application, when the salesperson shares the screen with the customer, the salesperson will slide the screen on the business end as needed to change the shared content, that is, the interface information in the pre-sharing interface sent by the business end will change.

[0100] Accordingly, in one embodiment, see Figure 4 , Figure 4 The following is a flowchart of another screen sharing method according to an embodiment of the present application. The screen sharing method may include the following steps:

[0101] Step 401: Receive the pre-sharing interface and customer information sent by the service end.

[0102] Step 402: Acquire interface information in the pre-shared interface according to a preset time step.

[0103] Step 403: If the similarity between the currently acquired interface information and the previous interface information is less than a preset value, the currently acquired interface information and customer information are input into a preset neural network model to obtain the term interpretation output by the neural network model.

[0104] Step 404: Integrate the term definitions in the pre-sharing interface to obtain a sharing interface.

[0105] Step 405: Send the sharing interface to the client and the service end.

[0106] Among them, steps 401, 404, 405 and 406 can refer to the aforementioned steps 101, 104, 105 and 106 respectively, steps 402 and 403 correspond to the aforementioned step 103, and the relevant introduction can be referred to the aforementioned content by analogy, and will not be repeated here.

[0107] In the application, after the server obtains the interface information based on the pre-shared interface, it can compare the currently obtained interface information with the interface information obtained in the past. When the similarity between the two is less than the preset value, the currently obtained interface information is used as the input of the neural network model; when the interface information is text information, the server can compare the text information obtained before and after, and when the interface information is image information, the server compares the similarity of the pictures obtained before and after.

[0108] In an embodiment of the present application, by acquiring interface information according to a preset time step, the corresponding term definitions can be acquired in a timely manner for display in a shared interface, and by performing a similarity comparison on the interface information acquired before and after, computing resources can be saved to avoid repeated acquisition of corresponding term definitions when the interface information before and after changes little.

[0109] It should be noted that when the pre-shared interface does not contain text information or the interface image does not contain text content, the server does not obtain new interface information based on the pre-shared interface. Later, when the server obtains the interface information again, it will match the similarity with the previous interface information.

[0110] Furthermore, in one embodiment, considering that the salesperson only stays on a certain page for a short time when communicating with the customer, that is, the interface information obtained by the server changes too quickly, please refer to Figure 5 , Figure 5 The following is a flowchart of another screen sharing method according to an embodiment of the present application. The screen sharing method may include the following steps:

[0111] Step 501: Receive the pre-sharing interface and customer information sent by the service end.

[0112] Step 502: Acquire interface information in the pre-shared interface according to a preset time step.

[0113] Step 503: If the similarity between the currently acquired interface information and the previous interface information is less than a preset value, the currently acquired interface information is used as the target interface information, and new interface information is acquired after a preset time period.

[0114] Step 504: If the similarity between the target interface information and the new interface information is greater than a preset value, the new interface information and the customer information are input into a preset neural network model to obtain the term interpretation output by the neural network model.

[0115] Step 505: Integrate the term definitions in the pre-sharing interface to obtain a sharing interface.

[0116] Step 506: Send the sharing interface to the client and the service end.

[0117] The above steps 501 - 506 may refer to the related introduction of the above embodiment and will not be described in detail here.

[0118] In an embodiment of the present application, after obtaining the target interface information, the server will obtain new interface information after a preset period of time, and compare the target interface information and the newly obtained interface information for similarity. If the similarity between the two is greater than a preset value, it indicates that the newly obtained interface information may be the target that the salesperson is preparing to share with the customer, and then obtain the corresponding terminology interpretation to help the customer understand the shared content, avoiding the waste of computing resources caused by obtaining terminology interpretation for the interface information that appears briefly; of course, after obtaining the terminology interpretation, the server can also determine whether the interface information has changed. If it has not changed or the similarity between the interface information before and after the change is greater than a preset value, the terminology interpretation can be further integrated into the pre-shared interface.

[0119] In addition, in one embodiment, the server may also obtain interface information of the current pre-shared interface based on the definition query instruction sent by the business end; and then subsequently use the interface information as input to the neural network model to obtain the corresponding term definition.

[0120] In the application, salespeople can determine the information to be shared with customers based on actual needs. For example, if they need to add term definitions to the currently shared document, they can perform definition query operations on the business side, such as clicking a definition query button. The business side then sends a definition query instruction to the server to obtain the corresponding term definitions.

[0121] In one embodiment, the screen sharing method may further include the following steps:

[0122] Receive and store feedback information sent by the client or business end, and send the feedback information to the agent end; the feedback information includes sentences to be interpreted and / or term interpretations.

[0123] In the application, when the salesperson finds sentences to be explained during the communication with the customer, that is, sentences in the shared interface that the customer has doubts about and have no relevant terminology explanations, feedback can be given for the sentences to be explained; the customer can perform the feedback operation based on the client, or the salesperson can perform the feedback operation based on the business end, thereby sending the sentences to be explained to the agent end through the client or the business end, as a basis for subsequent training and improvement of the preset neural network model; at the same time, if the sentences to be explained come from the terminology explanation, it indicates that the previously set terminology explanation may need to be adjusted, so the server can send the sentences to be explained and the corresponding terminology explanations to the agent end together.

[0124] Furthermore, when the sentence to be interpreted is sent to the agent end, the agent at the agent end can interpret the meaning of the received sentence to be interpreted, and send the corresponding sentence interpretation to the client and the business end through the agent end; accordingly, the server can also perform the following operations:

[0125] Receive the sentence interpretation corresponding to the sentence to be interpreted sent by the agent end, and forward it to the client and business end.

[0126] In an embodiment of the present application, a customer or salesperson can provide feedback to the agent side through the client or business side regarding the sentences to be explained that lack relevant terminology explanations in the shared interface, thereby providing data support for subsequent training and improvement of the neural network model.

[0127] It can be understood that the above embodiments are merely exemplary and not limiting. In the absence of logical conflicts, the above embodiments can be combined with each other to form new embodiments.

[0128] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a screen sharing system, device, medium and corresponding embodiments.

[0129] See also Figure 6 , Figure 6 This is a schematic diagram of the module structure of a screen sharing system shown in an embodiment of the present application. The system includes:

[0130] The information processing module 61 is used to:

[0131] Receive the pre-shared interface and customer information sent by the business end;

[0132] Get the interface information in the pre-shared interface;

[0133] The definition acquisition module 62 is used to input the interface information and the customer information into the preset neural network model to obtain the definition of the term output by the neural network model;

[0134] The interface processing module 63 is used for:

[0135] Integrate the term definitions in the pre-shared interface to obtain a shared interface;

[0136] Send the shared interface to the client and business end.

[0137] In some embodiments, before integrating the term definitions in the pre-sharing interface to obtain the sharing interface, the interface processing module 63 is further used to:

[0138] In the pre-sharing interface, target sentences corresponding to the term definitions are marked.

[0139] In some embodiments, in terms of integrating the term definitions in the pre-sharing interface to obtain the sharing interface, the interface processing module 63 is specifically the same as:

[0140] Based on the definition of the term, construct a hyperlink to the target sentence;

[0141] Add a hyperlink to the pre-shared interface to get the shared interface.

[0142] In some embodiments, in terms of integrating the term definitions in the pre-sharing interface to obtain the sharing interface, the interface processing module 63 is specifically the same as:

[0143] Generate semantic interfaces that display term definitions;

[0144] The shared interface is obtained by concatenating the semantic interface and the pre-shared interface.

[0145] In some embodiments, in terms of integrating the term definitions in the pre-sharing interface to obtain the sharing interface, the interface processing module 63 is specifically the same as:

[0146] Determine a target area in the pre-sharing interface; the target area is a blank area in the pre-sharing interface;

[0147] Adding term definitions to the target area results in a shared interface.

[0148] In some embodiments, the information processing module 61 is also the same as:

[0149] Receive and store feedback information sent by the client or business end, and send the feedback information to the agent end; the feedback information includes sentences to be interpreted and / or term interpretations.

[0150] In some embodiments, the information processing module 61 is also the same as:

[0151] Receive the sentence interpretation corresponding to the sentence to be interpreted sent by the agent end, and forward it to the client and business end.

[0152] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0153] The present application also provides an electronic device. Figure 7 , the electronic device 7000 includes a memory 7010 and a processor 7020.

[0154] The processor 7020 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0155] The memory 7010 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. Among them, ROM may store static data or instructions required by the processor 7020 or other modules of the computer. The permanent storage may be a readable and writable storage. The permanent storage may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In other embodiments, the permanent storage may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 7010 may include any combination of computer-readable storage media, including various types of semiconductor storage chips (such as DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 7010 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0156] The memory 7010 stores executable codes, and when the executable codes are processed by the processor 1020, the processor 7020 can execute part or all of the methods described above.

[0157] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0158] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by a processor of an electronic device (or server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0159] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A screen sharing method, characterized in that: include: Receive the pre-shared interface and customer information sent by the business end; Acquiring interface information in the pre-shared interface according to a preset time step; If the similarity between the currently acquired interface information and the previous interface information is less than a preset value, the currently acquired interface information is used as the target interface information, and new interface information is acquired after a preset time period; If the similarity between the target interface information and the new interface information is greater than a preset value, the new interface information and the customer information are input into a preset neural network model to obtain the term interpretation output by the neural network model; Integrating the term definitions into the pre-shared interface to obtain a shared interface; The shared interface is sent to the client and the service end.

2. The screen sharing method according to claim 1, characterized in that: Before integrating the term definitions into the pre-sharing interface to obtain a sharing interface, the method further includes: In the pre-sharing interface, a target sentence corresponding to the term definition is marked.

3. The screen sharing method according to claim 2, characterized in that: The step of integrating the term definitions into the pre-sharing interface to obtain a sharing interface includes: Based on the term interpretation, construct a hyperlink to the target sentence; The hyperlink is added to the pre-shared interface to obtain a shared interface.

4. The screen sharing method according to claim 1 or 2, characterized in that: The step of integrating the term definitions into the pre-sharing interface to obtain a sharing interface includes: generating a semantic interface displaying the definitions of the terms; The semantic interface and the pre-shared interface are spliced ​​to obtain a shared interface.

5. The screen sharing method according to claim 1 or 2, characterized in that: The step of integrating the term definitions into the pre-sharing interface to obtain a sharing interface includes: Determine a target area in the pre-sharing interface; the target area is a blank area in the pre-sharing interface; Adding the term definition to the target area obtains a sharing interface.

6. The screen sharing method according to claim 1, characterized in that: The method further comprises: Receive and store feedback information sent by the client or the service end, and send the feedback information to the agent end; the feedback information includes the sentence to be interpreted and / or the interpretation of the term.

7. The screen sharing method according to claim 6, characterized in that: The sending the sentence to be interpreted to the agent end includes: The sentence interpretation corresponding to the sentence to be interpreted sent by the agent end is received, and forwarded to the client end and the service end.

8. A screen sharing system, characterized in that: include: Information processing module, used for: Receive the pre-shared interface and customer information sent by the business end; Acquiring interface information in the pre-shared interface according to a preset time step; The interpretation acquisition module is used to use the currently acquired interface information as the target interface information if the similarity between the currently acquired interface information and the previous interface information is less than a preset value, and acquire new interface information after a preset time period; If the similarity between the target interface information and the new interface information is greater than a preset value, the new interface information and the customer information are input into a preset neural network model to obtain the term interpretation output by the neural network model; Interface processing module, used for: Integrating the term definitions into the pre-shared interface to obtain a shared interface; The shared interface is sent to the client and the service end.

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

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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