Information processing method and device, equipment and storage medium

Abstract

The embodiment of the invention relates to an information processing method and device, equipment and a storage medium. The method provided by the invention comprises the following steps: acquiring configuration for analyzing a real-time interaction scene, wherein the configuration comprises at least one of task description or a result presentation mode; determining an analysis result for the real-time interaction scene based on the configuration and the data of the real-time interaction scene; and providing the analysis result in a target result presentation mode. In this way, the real-time interaction scene can be analyzed more flexibly based on the configuration.

Description

Technical Field

[0001] Example embodiments of the present disclosure generally relate to the field of computers, and more particularly, to methods, apparatuses, devices, and computer-readable storage media for information processing. Background Art

[0002] With the rapid development of Internet technology, real-time interactive applications such as online meetings and live video chats have become an important way of daily communication. However, traditional real-time interactive application management and analysis tools can only collect some basic data in the real-time interaction process, and it is difficult to conduct a relatively accurate analysis of the real-time interactive content, so there are obvious shortcomings. Summary of the invention

[0003] In a first aspect of the present disclosure, an information processing method is provided. The method comprises: obtaining a configuration for analyzing a real-time interactive scene, the configuration comprising at least one of a task description or a result presentation mode; determining an analysis result for the real-time interactive scene based on the configuration and data of the real-time interactive scene; and providing the analysis result in a target result presentation mode.

[0004] In a second aspect of the present disclosure, a device for information processing is provided. The device includes: an acquisition module configured to acquire a configuration for analyzing a real-time interactive scene, the configuration including at least one of a task description or a result presentation mode; a determination module configured to determine an analysis result for the real-time interactive scene based on the configuration and data of the real-time interactive scene; and a presentation module configured to provide the analysis result in a target result presentation mode.

[0005] In a third aspect of the present disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory, the at least one memory is coupled to the at least one processing unit and stores instructions for execution by the at least one processing unit. When the instructions are executed by the at least one processing unit, the device executes the method of the first aspect.

[0006] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, wherein a computer program is stored on the computer-readable storage medium, and the computer program can be executed by a processor to implement the method of the first aspect.

[0007] It should be understood that the contents described in this content section are not intended to limit the key features or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0009] Figure 1 A schematic diagram showing an example environment in which embodiments of the present disclosure can be implemented;

[0010] FIG. 2A to FIG. 2B A schematic diagram showing a configuration interface for information processing according to some embodiments of the present disclosure;

[0011] Figure 3 A flowchart showing a process for information processing according to some embodiments of the present disclosure is shown;

[0012] Figure 4 A flowchart showing a process for information processing according to some embodiments of the present disclosure is shown;

[0013] Figure 5 A block diagram showing an apparatus for information processing according to some embodiments of the present disclosure; and

[0014] Figure 6 A block diagram of a device capable of implementing various embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0015] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0016] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0017] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0018] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0019] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0020] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0021] It should be noted that the titles of any sections / subsections provided herein are not restrictive. Various embodiments are described throughout this article, and any type of embodiment may be included under any section / subsection. In addition, the embodiments described in any section / subsection may be combined in any manner with any other embodiments described in the same section / subsection and / or different sections / subsections.

[0022] Herein, unless explicitly stated, executing a step “in response to A” does not mean executing the step immediately after “A” but may include one or more intermediate steps.

[0023] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may be included below. The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may be included below.

[0024] As used herein, the term "model" can learn the association between the corresponding input and output from the training data, so that after the training is completed, the corresponding output can be generated for a given input. The generation of the model can be based on machine learning technology. Deep learning is a machine learning algorithm that processes inputs and provides corresponding outputs by using multiple layers of processing units. In this article, "model" may also be referred to as "machine learning model", "machine learning network" or "network", which are used interchangeably in this article. A model may also include different types of processing units or networks.

[0025] As used herein, a "unit", "operating unit" or "subunit" may consist of a machine learning model or network of any suitable structure. As used herein, a group of elements or similar expressions may include one or more such elements. For example, a "group of convolutional units" may include one or more convolutional units.

[0026] As briefly mentioned above, with the rapid development of Internet technology, real-time interactive applications such as online meetings and live video chats have become an important way of daily communication. However, traditional real-time interactive application management and analysis tools can only collect some basic data in the real-time interaction process, and it is difficult to conduct a relatively accurate analysis of the real-time interactive content, so there are obvious shortcomings.

[0027] To this end, an embodiment of the present disclosure proposes a scheme for information processing. According to various embodiments of the present disclosure, a configuration for analyzing a real-time interactive scene is obtained, the configuration including at least one of a task description or a result presentation mode; based on the configuration and data of the real-time interactive scene, an analysis result for the real-time interactive scene is determined; and the analysis result is provided in a target result presentation mode.

[0028] In this way, the embodiments of the present disclosure can analyze the real-time interactive scene based on the configuration including the task description and / or the result presentation mode, so that the real-time interactive scene can be managed more flexibly and effectively.

[0029] Example embodiments of the present disclosure are described below with reference to the accompanying drawings. Example Environment

[0030] Figure 1 1 is a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. In the example environment 100 , a component execution platform 110 can support the execution of a business component 125 . A user 140 can interact with the business component 125 via a client of the component execution platform 110 .

[0031] In some embodiments, the service component 125 can be downloaded and installed on the terminal device of the user 140. In some embodiments, the service component 125 can also be accessed through other means, such as through a web page. Figure 1 In the environment 100 , in response to the business component 125 being started, the client of the component execution platform 110 may present the interface 150 of the business component 125 .

[0032] The business component 125 includes but is not limited to one or more of the following: a chat business component (also known as an instant messaging business IM component), a document business component, an audio and video conference business component, an email business component, a task business component, a calendar business component, an objective and key result (OKR) business component, etc. It can be understood that although Figure 1 A single business component is shown in FIG. 1 , but in fact, multiple business components can be installed on the terminal device. Multiple business components can be integrated on the component operation platform 110, and such a component operation platform 110 can be regarded as a multifunctional collaboration platform. In the case where multiple business components are installed in the terminal device, these multiple business components can be integrated on one or more component operation platforms 110. In the component operation platform 110, people can start different business components as needed to complete corresponding information processing, sharing, communication, etc. The business component 125 can provide a content entity 126. The content entity 126 can be a content instance created by the user 140 or other users on the business component 125. For example, depending on the type of the business component 125, the content entity 126 can be a document (e.g., a word document, a pdf document, a presentation, a spreadsheet document, etc.), an email, a message (e.g., a conversation message on an instant messaging business component), a calendar, a schedule, a task, an audio, a video, an image, and the like.

[0033] In some embodiments described below, for ease of discussion, the interaction window between the user and the digital assistant is mainly taken as an example of a conversation window.

[0034] The component operation platform 110 may be deployed locally on the terminal device of each user 140, and / or may be supported by a server-side device. For example, the terminal device of the user 140 may run a client of the component operation platform 110, which may support the interaction between the user 140 and the component operation platform 110 provided by the server. In the case where the component operation platform 110 runs locally on the user's terminal device, the user 140 may directly interact with the local component operation platform 110 using the terminal device. In the case where the component operation platform 110 runs on the server-side device, the server-side device may provide services to the client running in the terminal device based on the communication connection with the terminal device. The component operation platform 110 may present a corresponding interface 150 to the user 140 based on the operation of the user 140, so as to output to the user 140 and / or receive from the user 140 information related to the use of the component.

[0035] In some embodiments, at least part of the functionality of the business component 125 may be implemented based on a target model. During the operation of the business component 125, one or more target models 155 may be called. The target model 155 may be used to understand user input, and to provide services based on the output of the target model 155, such as providing a response to the user.

[0036] Although shown as being independent of the component runtime platform 110, one or more target models 155 may be run on the component runtime platform 110, or other remote servers. In some embodiments, the target model 155 may be a machine learning model, a deep learning model, a learning model, a neural network, etc. In some embodiments, the model may be based on a language model (LM). The language model can have question-answering capabilities by learning from a large amount of corpus. The target model 155 may also be based on other appropriate models.

[0037] The component operation platform 110 can be run on appropriate electronic devices. The electronic device here can be any type of device with computing capabilities, including terminal devices or server devices. The terminal device can be any type of mobile terminal, fixed terminal or portable terminal, including mobile phones, desktop computers, laptop computers, notebook computers, netbook computers, tablet computers, media computers, multimedia tablets, personal communication systems (PCS) devices, personal navigation devices, personal digital assistants (PDAs), audio / video players, digital cameras / camcorders, positioning devices, television receivers, radio broadcast receivers, e-book devices, gaming devices, or any combination of the foregoing, including accessories and peripherals of these devices or any combination thereof. The server device can include, for example, a computing system / server, such as a mainframe, an edge computing node, a computing device in a cloud environment, and the like. In some embodiments, the component operation platform 110 can be implemented based on cloud services.

[0038] It should be understood that the structure and functionality of environment 100 are described for exemplary purposes only and does not imply any limitation on the scope of the present disclosure.

[0039] Some example embodiments of the present disclosure will be described below with continued reference to the accompanying drawings. Specific embodiments

[0040] The following will refer to FIG. 2A to FIG. 2B An example information processing process according to an embodiment of the present disclosure is described below. FIG. 2A to FIG. 2B Example information processing configuration interfaces 200A to 200B according to some embodiments of the present disclosure are shown. Such example information processing interfaces can be implemented by an appropriate component execution platform or a combination of component execution platforms.

[0041] In some embodiments, the component operation platform 110 obtains a configuration for analyzing a real-time interactive scene, and the configuration includes at least one of a task description or a result presentation mode. The task description indicates the analysis task to be performed, such as the target of the analysis, the specific operation, etc. The result presentation mode indicates the presentation mode of the analysis result, such as presentation in a word document, presentation in a table, etc. As an example, the real-time interactive scene can be, for example, an online meeting scene, a live broadcast scene, a video chat scene, etc.

[0042] In some scenarios, the component execution platform 110 obtains the configuration for analyzing the real-time interactive scene via the configuration interface. For example, the component execution platform 110 may provide the configuration interface to the user 140, and obtain the configuration for analyzing the real-time interactive scene from the user 140 via the configuration interface.

[0043] Figure 2A An example configuration interface 200A for information processing for online conference analysis is shown. The interface 200A includes at least various controls for configuring information processing. Through these controls, the user 140 can input the configuration for information processing. The component operation platform 110 can obtain the configuration information 210 in the interface 200A to generate the configuration for online conference analysis. Figure 2A As shown, the configuration information 210 may include, for example, a meeting 220 to be analyzed, a category 230 of the analysis task, a task description 240 , keyword information 250 , and a result presentation mode 260 , which are input by the user 140 .

[0044] In some embodiments, the configuration and / or configuration information 210 may include a task description. The task description may include at least one of a selected preset task description and an input custom task description. Figure 2A As shown, the configuration information 210 in the interface 200A may include a task description 240. The content of the task description 240 may be, for example, a preset task description selected by the user 140 from at least one task description preset by the system, such as "Task 1". Additionally or alternatively, although not shown, the task description 240 may be a customized task description input by the user 140, such as a task description in natural language form "Analyze the meeting results of all the meetings I attended today".

[0045] In some embodiments, the configuration and / or configuration information 210 may include a result presentation mode. The result presentation mode may include at least one of a selected preset result presentation mode and an input custom result presentation mode. Figure 2AAs shown, the result presentation mode 250 can be a preset result presentation mode, i.e., a table, selected by the user 140 from at least one result presentation mode preset by the system. Additionally or alternatively, although not shown, the result presentation mode 250 can be a customized result presentation mode input by the user 140, such as presenting the analysis results in an email.

[0046] In some embodiments, the result presentation mode indicates that the analysis result is presented in at least one of the following: a session, a table, a document, an email, or an application notification. As an example, when the result presentation mode is a session, an email, or an application notification, the component execution platform 110 may distribute the analysis result to the terminal device of the corresponding user.

[0047] In some embodiments, the user may provide natural language input in the configuration interface to indicate the configuration information of the user's analysis of the real-time interactive scene. The component operation platform 110 may process the natural language input to obtain at least a portion of the configuration for information processing. The configuration may be input into a large model for information processing to determine the analysis results. In some embodiments, the component operation platform 110 may determine an adjusted prompt based on the user's natural language input and a preset prompt template, and then input the prompt into the large model to obtain the analysis results output by the large model. In some embodiments, the component operation platform 110 may perform multiple iterations with the user 140 to determine an optimized prompt for input into the large model.

[0048] As an example, the component execution platform 110 may generate a prompt based on a preset prompt template in response to receiving a natural language input from the user 140. The component execution platform 110 may input the prompt into the target model 155 and obtain an analysis result from the target model 155.

[0049] In some embodiments, the component operation platform 110 determines the analysis result for the real-time interaction scene based on the acquired configuration and data of the real-time interaction scene. As an example, the component operation platform 110 may input the configuration information of the online meeting analysis task and the relevant data of the online meeting into the target model 155 in response to receiving the relevant data of the online meeting, so as to determine the result of the online meeting analysis task.

[0050] In some embodiments, the analysis of the real-time interactive scene may include objective analysis, that is, statistical analysis of the data of the real-time interactive scene to determine the statistical information of the real-time interactive scene. The statistical information of the real-time interactive scene can be used as at least a part of the analysis results. As an example, the statistical information of the real-time interactive scene may include the attendance rate of the online meeting, the duration of the online meeting, the composition of the personnel participating in the online meeting, etc.

[0051] Additionally or alternatively, the analysis of the real-time interactive scene may include subjective analysis, that is, analyzing the data of the real-time interactive scene based on subjective rules / models to determine the content information of the real-time interactive scene. The content information of the real-time interactive scene may be used as at least a part of the analysis results. As an example, the content information of the real-time interactive scene may include the importance of the meeting, the status of the participants, whether the meeting is on topic, etc.

[0052] In some embodiments, when analyzing a real-time interactive scene, at least one analysis dimension may be determined based on a configuration. The at least one analysis dimension may include at least one of an interactive content dimension or an interactive entity dimension of the real-time interactive scene. Furthermore, a machine learning model may be used to determine an analysis result based on the data of the real-time interactive scene and the at least one analysis dimension.

[0053] As an example, the interactive content dimension of the real-time interactive scene may indicate the type of online meeting, the importance of the meeting topic, the concentration of the meeting content, etc. The interactive entity dimension may indicate the emotional state of the participants in the online meeting or the performance of the participants in the meeting.

[0054] In some embodiments, an intermediate analysis result can be determined using a machine learning model for each analysis dimension in at least one analysis dimension. Based on the intermediate analysis result, the analysis result can be further determined. For example, if a user configures multiple analysis dimensions that require the use of a large model, the model can be called separately for each analysis dimension for analysis. The large model for each analysis dimension can be the same or similar, or it can be a different model trained for different focuses. The intermediate analysis results for separate analysis dimensions can be combined to determine the final analysis result.

[0055] In some embodiments, the component operation platform 110 can obtain keyword information for analyzing the real-time interactive scene based on the configuration; and determine the analysis result, such as the concentration of the meeting content, based on the matching of the keyword information and the data of the real-time interactive scene. As an example, Figure 2A The keyword information 250 is shown in FIG. Figure 2B The configuration interface 200B shown provides a keyword editing control. Using this control, the component execution platform 110 can obtain the keyword information input by the user 140. The keyword information may include, for example, a keyword name and a keyword explanation.

[0056] Based on the keyword information, the component operation platform 110 can determine the matching of the data of the real-time interactive scene with the keyword information, thereby obtaining the analysis result. For example, the component operation platform 110 can match the data of the real-time interactive scene based on the obtained keyword name and keyword explanation to determine the number of times the keyword appears in the conference transcript, for example, to generate the analysis result. The analysis result may include, for example, the number of occurrences of the keyword and the score of the keyword detection task. In some examples, the higher the number of occurrences of the keyword, the more relevant the content of the meeting is, that is, the more concentrated the content of the meeting is.

[0057] In some embodiments, the configuration obtained by the component operation platform 110, such as the task description, may also include tag information. Tag information may include, for example, user tags and meeting tags. User tags are used to distinguish the identity information of participants in online meetings, and meeting tags are used to classify online meetings. Examples of tags may include, A business meeting, B group regular meeting, and so on. In other embodiments, tags may be generated by a large model. In the scenario of analyzing multiple meetings, multiple meetings can be grouped using tags, each group corresponding to a tag, and then the meetings are analyzed based on the grouping. If the analysis result indicates that the number of business groups involved in multiple meetings under the A business meeting tag is too large, the analysis result may be provided to the user to assist the user in optimizing the personnel organization structure of the A business.

[0058] In some embodiments, a real-time interactive scene may involve multiple standard time zones, such as an online meeting attended by multinational personnel. The component execution platform 110 may determine time-related statistical items in the statistical information of the real-time interactive scene based on a reference time zone in the multiple standard time zones.

[0059] As an example, in an online conference scenario, the component operation platform 110 can obtain the time zone of the online conference participant and the time corresponding to the participant. Accordingly, the component operation platform 110 can determine whether the participant participates in the online conference on time based on the time zone of the participant and the time corresponding to the participant, and score the participant.

[0060] Based on the determined analysis results, the component execution platform 110 provides the analysis results in a target result presentation mode. The target result presentation mode may be a result presentation mode included in the acquired configuration. In some embodiments, if the user does not configure the result presentation mode, the analysis results may be provided in a pre-configured default result presentation mode.

[0061] In some embodiments, the component operation platform 110 may provide one or more data items related to the analysis results in the data of the real-time interactive scene in association with the analysis results. As an example, when presenting the analysis results, the component operation platform 110 may also present the reasons for generating the analysis results. For example, in an online meeting scenario, the reasons for generating the analysis results may be, for example, the time when the participants attended the meeting, whether the participants actively spoke in the meeting, and the number of times the participants' speeches in the meeting hit keywords. Additionally, the component operation platform 110 may also allow users to provide feedback on the analysis results and automatically collect and count these feedbacks to optimize the analysis service.

[0062] In some embodiments, the component operation platform 110 may also obtain an analysis request for a real-time interactive scene initiated by a user, the analysis request indicating the user's configuration for the analysis. Further, the component operation platform 110 determines that the relevant real-time interactive scene can be analyzed based on determining that the user's authority meets the requirements, so as to generate an analysis result for the real-time interactive scene data.

[0063] As an example, the component operation platform 110 may obtain an analysis request initiated by a user for a target real-time interactive scene, and the analysis request may include, for example, configuration information and a user identifier of the user. Further, the component operation platform 110 may determine whether the user has permission to start the analysis task based on the user identifier of the user and the identifier of the target real-time interactive scene. When it is determined that the user has permission to start the analysis task, the component operation platform 110 may determine the analysis result of the real-time interactive scene data based on the analysis request.

[0064] In some embodiments, obtaining a user's real-time interactive scene analysis request includes receiving a real-time interactive scene analysis request before the real-time interactive scene starts, during the real-time interactive scene, or after the real-time interactive scene ends. The component operation platform 110 can obtain component data of the real-time interactive scene data or obtain all data of the real-time interactive scene in real time. Further, the component operation platform 110 can determine the analysis result based on the component data or all data of the real-time interactive scene data.

[0065] Figure 3 FIG. 300 is a process diagram for analyzing online conference content according to an embodiment of the present disclosure. Figure 3 As shown, the upstream service may send an analysis request for the target conference to the analysis service. After the analysis service receives the analysis request, the analysis service may generate a task identifier associated with the analysis request based on the analysis request, and temporarily store the configuration information of the analysis task included in the analysis request.

[0066] Furthermore, the analysis service may request the conference record service to send a conference link associated with the analysis request based on the analysis request. The analysis service request may query the authority of the user associated with the analysis request through the identifier of the conference record service.

[0067] After determining that the user has browsing permission for the target meeting, the analysis service can pull the text content of the target meeting recorded by the meeting record service in pages until the full text content of the target meeting is obtained.

[0068] Furthermore, the analysis service can determine whether the recognition model is turned on during the target meeting. When it is determined that the recognition model is turned on, the analysis service can obtain the text content of the target meeting recorded by the recognition model. After obtaining the text content of the target meeting recorded by the recognition model, the analysis service can request the analysis model to perform an analysis task based on the acquired data and obtain an analysis result. Finally, the analysis service can send the analysis result to the upstream service in response to receiving the analysis result query request sent by the upstream service.

[0069] In this way, the embodiments of the present disclosure can analyze the real-time interaction scene based on the configuration and data of the real-time interaction scene, so that the real-time interaction scene can be managed more effectively.

[0070] By using the solution disclosed in the present invention, real-time interactive scenes can be flexibly analyzed based on configuration, thereby better realizing the management of real-time interactive scenes. In this solution, a configuration system of flexible and diverse analysis standards is provided, which allows users to customize multiple analysis standards according to specific enterprise needs, including but not limited to the time, content, and behavior of participants of the meeting. This solution provides a configuration system that supports user-defined analysis standards and describes its application in video conference analysis.

[0071] This solution also provides an accurate cross-time zone meeting time analysis mechanism, specifically providing algorithms and system designs for processing and analyzing cross-time zone meeting times. A new time analysis mechanism is introduced that can accurately process cross-time zone meeting times, making the analysis results more accurate and reliable.

[0072] This solution also provides a multi-dimensional in-depth meeting content analysis function, which can deeply analyze the meeting content. Through natural language processing technology and large language models, it can identify and evaluate the main topics, discussion content and context of the meeting, and generate multi-dimensional analysis results.

[0073] This solution also provides a personalized analysis result presentation and report generation system, which supports customized presentation of analysis results and generation of reports according to user needs, so that the system can output analysis reports that meet specific format and content requirements to meet the personalized needs of different enterprises.

[0074] This solution also provides an automated user feedback and analysis result verification mechanism, which allows users to provide feedback on the analysis results and automatically collects and counts these feedbacks to optimize the accuracy of the analysis model. This solution provides an automated feedback collection and result verification system and its application in conference analysis.

[0075] This solution also provides a conference organizational structure analysis system based on label classification. The system can classify meetings according to the labels entered by users and analyze the distribution and organizational structure of participants in each meeting to optimize cross-departmental collaboration within the enterprise.

[0076] This solution also provides custom detection dimensions and scoring systems, specifically providing a system that supports user-defined detection dimensions, which can analyze meeting content based on these dimensions, output corresponding frequency data, and provide a score for meeting quality in combination with a scoring strategy.

[0077] This solution also provides an analysis system for data authorization compliance and privacy protection, which can protect user privacy and data security during data collection and analysis.

[0078] In addition, this solution can achieve the following beneficial effects. This solution can adapt to the specific needs of different companies and meeting types, provide more accurate and personalized meeting analysis results, and improve the applicability of analysis and support for corporate decision-making. This solution can accurately handle the analysis function of cross-time zone meeting time, and can accurately process and calculate cross-time zone meeting time, solving the error problem of existing tools in cross-time zone meeting time analysis, ensuring the accuracy of analysis results, and improving the efficiency of global companies in meeting management in different regions.

[0079] This solution can provide multi-dimensional and in-depth conference content analysis capabilities. Through natural language processing (NLP) and large language models, it can achieve multi-dimensional in-depth analysis of conference content, and can identify and evaluate conference topics, discussion content, and participant performance. This solution can provide more comprehensive and in-depth conference analysis, enabling enterprises to better understand the core content and effects of meetings, improve the overall efficiency and quality of conference management, and support more accurate strategic decision-making.

[0080] This solution can support customized presentation and report generation of personalized analysis results, support user-customized report generation and analysis result presentation, and can adjust the report format and content according to different user needs, making the analysis report more in line with user needs, enhancing the pertinence and operability of the analysis results, and improving user experience and satisfaction.

[0081] This solution can support automated user feedback collection and analysis result verification mechanisms, dynamically collect user feedback and automatically adjust the analysis model, improve the accuracy and reliability of the analysis model, and enable the conference analysis tool to be continuously optimized to ensure that user needs and expectations are continuously met.

[0082] This solution can support meeting classification and participant distribution analysis based on user-input tags. It can classify meetings according to user-input tags and analyze the composition and distribution of participants, thereby improving the accuracy and depth of meeting organization and participant structure analysis, helping enterprises optimize meeting organization methods and cross-departmental collaboration efficiency.

[0083] This solution can support the implementation of custom detection dimensions and scoring mechanisms, allowing users to customize detection dimensions and scoring standards, and conduct meeting content analysis and quality scoring based on these standards, thereby enhancing the flexibility and accuracy of meeting analysis, providing enterprises with a more objective basis for meeting quality assessment, and supporting management decisions and improvements. This solution can ensure data authorization and privacy protection, ensure the security and compliance of data during collection and analysis, thereby protecting user privacy and data security, reducing the risk of data leakage or abuse, and increasing users' trust in and willingness to use meeting analysis tools. Example Process

[0084] Figure 4 400 is a flowchart showing an example process 400 of information processing according to some embodiments of the present disclosure. The process 400 may be implemented at the component execution platform 110. Figure 1 4. The process 400 is described below.

[0085] like Figure 4 As shown, in block 410 , the component execution platform 110 obtains a configuration for analyzing a real-time interactive scenario, where the configuration includes at least one of a task description or a result presentation mode.

[0086] In block 420 , the component execution platform 110 determines an analysis result for the real-time interactive scenario based on the configuration and the data of the real-time interactive scenario.

[0087] In block 430 , the component execution platform 110 provides the analysis result in a target result presentation mode.

[0088] In some embodiments, the task description includes at least one of the following: a selected preset task description, an input customized task description.

[0089] In some embodiments, the result presentation mode includes at least one of the following: a selected preset result presentation mode, an input customized result presentation mode.

[0090] In some embodiments, at least a portion of the configuration is generated based on a user's natural language input and a preset prompt template.

[0091] In some embodiments, the analysis result indicates at least one of the following: statistical information of the real-time interactive scene, content information of the real-time interactive scene.

[0092] In some embodiments, determining the analysis results based on the analysis configuration and the data of the real-time interactive scene includes: determining at least one analysis dimension based on the analysis configuration, the at least one analysis dimension including at least one of the interactive content dimension or the interactive entity dimension of the real-time interactive scene; and determining the analysis results based on the data of the real-time interactive scene and at least one analysis dimension using a machine learning model.

[0093] In some embodiments, determining the analysis result based on the configuration and the data of the real-time interactive scenario includes: determining an intermediate analysis result using the machine learning model for each analysis dimension of the at least one analysis dimension; and determining the analysis result based on the intermediate analysis result.

[0094] In some embodiments, determining the analysis results based on the analysis configuration and the real-time interactive scene data includes: obtaining keyword information for analyzing the real-time interactive scene based on the analysis configuration; and determining the analysis results based on the matching of the keyword information and the real-time interactive scene data.

[0095] In some embodiments, the data of the real-time interactive scene involves multiple standard time zones, and based on the analysis configuration and the data of the real-time interactive scene, determining the analysis results includes: determining time-related statistical items in the statistical information of the real-time interactive scene based on a reference time zone in the multiple standard time zones.

[0096] In some embodiments, providing the analysis result in the target result presentation mode includes: providing one or more data items related to the analysis result in the data of the real-time interactive scene in association with the analysis result.

[0097] In some embodiments, the target result presentation mode is a result presentation mode included in the configuration, or is a pre-configured default result presentation mode.

[0098] In some embodiments, process 400 also includes obtaining an analysis request initiated by a user for a real-time interactive scene, the analysis request indicating a configuration; and determining an analysis result for the real-time interactive scene data based on determining that the user's permissions meet the requirements.

[0099] In some embodiments, the result presentation mode indicates that the analysis result is presented in at least one of the following: session, form, document, email, application notification. Example devices and equipment

[0100] The embodiments of the present disclosure also provide corresponding devices for implementing the above methods or processes. Figure 5 A schematic structural block diagram of an apparatus 500 for information processing according to some embodiments of the present disclosure is shown. The apparatus 500 may be implemented as or included in the component execution platform 110. Each module / component in the apparatus 500 may be implemented by hardware, software, firmware or any combination thereof.

[0101] like Figure 5 As shown, the device 500 includes an acquisition module 510, which is configured to acquire a configuration for analyzing a real-time interactive scene, the configuration including at least one of a task description or a result presentation mode; a determination module 520, which is configured to determine an analysis result for the real-time interactive scene based on the configuration and data of the real-time interactive scene; and a presentation module 530, which is configured to provide the analysis result in a target result presentation mode.

[0102] In some embodiments, the task description includes at least one of the following: a selected preset task description, an input customized task description.

[0103] In some embodiments, the result presentation mode includes at least one of the following: a selected preset result presentation mode, an input customized result presentation mode.

[0104] In some embodiments, at least a portion of the configuration is generated based on a user's natural language input and a preset prompt template.

[0105] In some embodiments, the analysis result indicates at least one of the following: statistical information of the real-time interactive scene, content information of the real-time interactive scene.

[0106] In some embodiments, the determination module 520 is further configured to: determine at least one analysis dimension based on the analysis configuration, the at least one analysis dimension including at least one of the interactive content dimension or the interactive entity dimension of the real-time interactive scene; and determine the analysis results based on the data of the real-time interactive scene and at least one analysis dimension using a machine learning model.

[0107] In some embodiments, the determination module 520 is also configured to: based on the configuration and the data of the real-time interactive scene, determine the analysis results including: for each analysis dimension of the at least one analysis dimension, using the machine learning model to determine the intermediate analysis results; and determine the analysis results based on the intermediate analysis results.

[0108] In some embodiments, the determination module 520 is further configured to: obtain keyword information for analyzing the real-time interactive scene based on the analysis configuration; and determine the analysis result based on the matching of the keyword information and the data of the real-time interactive scene.

[0109] In some embodiments, the data of the real-time interactive scene involves multiple standard time zones, and the determination module 520 is further configured to: determine time-related statistical items in the statistical information of the real-time interactive scene based on a reference time zone in the multiple standard time zones.

[0110] In some embodiments, the presentation module 530 is further configured to: provide one or more data items related to the analysis result in the data of the real-time interactive scene in association with the analysis result.

[0111] In some embodiments, the target result presentation mode is a result presentation mode included in the configuration, or is a pre-configured default result presentation mode.

[0112] In some embodiments, the device 500 also includes an authority determination module, which is configured to obtain an analysis request initiated by a user for a real-time interactive scene, the analysis request indicating a configuration; and determine the analysis results for the real-time interactive scene data based on determining that the user's authority meets the requirements.

[0113] In some embodiments, the result presentation mode indicates that the analysis result is presented in at least one of the following: session, form, document, email, application notification.

[0114] The units included in the device 500 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the units in the device 500 can be implemented at least in part by one or more hardware logic components. As an example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0115] Figure 6 1 shows a block diagram of an electronic device 600 in which one or more embodiments of the present disclosure may be implemented. It should be understood that Figure 6 The electronic device 600 shown is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. Figure 6 The electronic device 600 shown can be used to implement Figure 1 The component operation platform 110.

[0116] like Figure 6As shown, the electronic device 600 is in the form of a general electronic device. The components of the electronic device 600 may include, but are not limited to, one or more processors or processing units 610, a memory 620, a storage device 630, one or more communication units 640, one or more input devices 650, and one or more output devices 660. The processing unit 610 may be an actual or virtual processor and is capable of performing various processes according to a program stored in the memory 620. In a multi-processor system, multiple processing units execute computer executable instructions in parallel to improve the parallel processing capability of the electronic device 600.

[0117] The electronic device 600 typically includes a plurality of computer storage media. Such media may be any accessible media that is accessible to the electronic device 600, including but not limited to volatile and non-volatile media, removable and non-removable media. The memory 620 may be a volatile memory (e.g., registers, caches, random access memory (RAM)), a non-volatile memory (e.g., a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. The storage device 630 may be a removable or non-removable medium, and may include a machine-readable medium, such as a flash drive, a disk, or any other medium, which may be capable of being used to store information and / or data and may be accessed within the electronic device 600.

[0118] The electronic device 600 may further include additional removable / non-removable, volatile / non-volatile storage media. Figure 6 As shown in , a disk drive for reading or writing from a removable, non-volatile disk (e.g., a "floppy disk") and an optical drive for reading or writing from a removable, non-volatile optical disk may be provided. In these cases, each drive may be connected to the bus (not shown) by one or more data media interfaces. The memory 620 may include a computer program product 625 having one or more program modules that are configured to perform various methods or actions of various embodiments of the present disclosure.

[0119] The communication unit 640 implements communication with other electronic devices through a communication medium. Additionally, the functions of the components of the electronic device 600 can be implemented with a single computing cluster or multiple computing machines that can communicate through a communication connection. Therefore, the electronic device 600 can operate in a networked environment using a logical connection with one or more other servers, a network personal computer (PC), or another network node.

[0120] The input device 650 may be one or more input devices, such as a mouse, a keyboard, a tracking ball, etc. The output device 660 may be one or more output devices, such as a display, a speaker, a printer, etc. The electronic device 600 may also communicate with one or more external devices (not shown) through the communication unit 640 as needed, such as a storage device, a display device, etc., communicate with one or more devices that allow a user to interact with the electronic device 600, or communicate with any device that allows the electronic device 600 to communicate with one or more other electronic devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface (not shown).

[0121] According to an exemplary implementation of the present disclosure, a computer-readable storage medium is provided, on which computer-executable instructions are stored, wherein the computer-executable instructions are executed by a processor to implement the method described above. According to an exemplary implementation of the present disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, and the computer-executable instructions are executed by a processor to implement the method described above.

[0122] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices, equipment, and computer program products implemented according to the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0123] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0124] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer, other programmable data processing apparatus, or other device implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0125] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple implementations of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of a module, program segment or instruction includes one or more executable instructions for realizing the logical function of the specification. In some implementations as replacements, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be realized by a special hardware-based system that performs the function or action of the specification, or can be realized by a combination of special hardware and computer instructions.

[0126] The above descriptions of various implementations of the present disclosure are exemplary, non-exhaustive, and not limited to the disclosed implementations. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described implementations. The selection of terms used herein is intended to best explain the principles of the implementations, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the various implementations disclosed herein.

Claims

1. An information processing method, comprising: Acquire a configuration for analyzing a real-time interactive scenario, the configuration comprising at least one of a task description or a result presentation mode; Determine an analysis result for the real-time interactive scenario based on the configuration and the data of the real-time interactive scenario; as well as The analysis results are provided in a targeted results presentation mode.

2. The method according to claim 1, wherein the task description includes at least one of the following: Description of the selected preset task, The custom task description you entered.

3. The method according to claim 1 or 2, wherein the result presentation mode comprises at least one of the following: The selected preset result presentation mode, The custom result presentation mode entered. The method of claim 1 , wherein at least a portion of the configuration is generated based on a user's natural language input and a preset prompt template.

5. The method of claim 1, wherein the analysis result indicates at least one of the following: Statistical information of the real-time interactive scene, Content information of the real-time interactive scene.

6. The method according to claim 1, wherein determining the analysis result based on the configuration and the data of the real-time interactive scene comprises: Based on the configuration, determining at least one analysis dimension, the at least one analysis dimension comprising at least one of an interactive content dimension or an interactive entity dimension of the real-time interactive scene; as well as The analysis result is determined by using a machine learning model based on the data of the real-time interactive scenario and the at least one analysis dimension.

7. The method according to claim 6, wherein determining the analysis result based on the configuration and the data of the real-time interactive scene comprises: For each analysis dimension of the at least one analysis dimension, determining an intermediate analysis result using the machine learning model; as well as Based on the intermediate analysis result, the analysis result is determined.

8. The method according to claim 5 or 6, wherein determining the analysis result based on the configuration and the real-time interactive scene data comprises: Based on the configuration, obtaining keyword information for analyzing the real-time interactive scene; as well as The analysis result is determined based on the matching of the keyword information and the data of the real-time interactive scene.

9. The method according to claim 5 or 6, wherein the data of the real-time interactive scene involves multiple standard time zones, and based on the configuration and the data of the real-time interactive scene, determining the analysis result comprises: Based on a reference time zone among the multiple standard time zones, a statistical item related to time in the statistical information of the real-time interactive scene is determined.

10. The method according to claim 1, wherein providing the analysis results in a target result presentation mode comprises: One or more data items related to the analysis result in the data of the real-time interactive scene are provided in association with the analysis result.

11. The method according to claim 1 or 9, wherein the target result presentation mode is the result presentation mode included in the configuration, or is a pre-configured default result presentation mode.

12. The method according to claim 1, further comprising: Acquire an analysis request initiated by a user for the real-time interactive scenario, where the analysis request indicates the configuration; as well as Based on determining that the authority of the user meets the requirement, the analysis result for the real-time interactive scene data is determined.

13. The method according to claim 1, wherein the result presentation mode indicates presenting the analysis result in at least one of the following: Session, sheet, document, Email, or App notifications.

14. An apparatus for information processing, comprising: An acquisition module is configured to acquire a configuration for analyzing a real-time interactive scene, wherein the configuration includes at least one of a task description or a result presentation mode; A determination module, configured to determine an analysis result for the real-time interaction scenario based on the configuration and the data of the real-time interaction scenario; as well as The presentation module is configured to provide the analysis result in a target result presentation mode.

15. An electronic device, comprising: at least one processing unit; as well as At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 13 when executed by the at least one processing unit.

16. A computer-readable storage medium having a computer program stored thereon, wherein the computer program can be executed by a processor to implement the method according to any one of claims 1 to 12.

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