Online conference intelligent management system and method based on intelligent office

Abstract

The invention belongs to the technical field of online conference management, and particularly relates to an online conference intelligent management system and method based on intelligent office. The method can automatically synchronize and integrate conference information from a mailbox, a calendar and an instant messaging tool, accurately extract conference time, participants and core issues, effectively avoid the problem of information omission or untimely synchronization, and can automatically generate a dynamically sorted conference list by comprehensively calculating conference priority scores, so that the conference efficiency is improved. According to the method, users are helped to quickly identify and preferentially process important conferences, in addition, accurate grouping of the participants is realized by optimizing a grouping strategy and identifying the matching degree of the participants and the conference topics, the deviation degree of the topics can be monitored in real time in the conference proceeding process, a prompt is given out in time when the deviation degree exceeds a preset threshold value, and the user experience is improved. And meanwhile, the access authority and the document access authority can be dynamically allocated according to the grouping result of the participants, so that the security and controllability of the conference information are ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of online conference management, and specifically relates to an online conference intelligent management system and method based on smart office. Background Art

[0002] With the continuous development of information technology, the way of holding meetings has also undergone various changes, gradually shifting from traditional face-to-face meetings to online meetings. Especially in the context of the popularization of remote work, the efficiency and convenience of online meetings have become increasingly prominent. However, online meeting management still faces many challenges, such as untimely information synchronization, difficulty in controlling deviations from the agenda, and unclear authority allocation, which seriously affect the efficiency and quality of meetings. Therefore, for the management of online meetings, existing technologies need to be optimized and innovated.

[0003] In the existing technology, although some systems have attempted to improve the efficiency of meeting organization through automated tools, they are mostly limited to single function implementation and lack an overall solution. They fail to effectively integrate multi-dimensional requirements such as information synchronization, agenda monitoring and authority management, resulting in obvious limitations in actual applications, making it difficult to fully meet the needs of efficient meeting management. Based on this, the present invention proposes a comprehensive online meeting intelligent management method to solve the above problems. Summary of the Invention

[0004] The purpose of the present invention is to provide an online conference intelligent management system and method based on smart office, which can automatically integrate and manage conference information and realize efficient organization and intelligent monitoring of meetings.

[0005] The technical solutions adopted by the present invention are as follows: An intelligent management method for online meetings based on intelligent office, comprising: Synchronize meeting information from email, calendar, and instant messaging tools, and identify and extract meeting time, participants, and core topics from meeting information; The meeting priority score is calculated based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics. A dynamically sorted meeting list is generated based on the meeting priority score. Identify the matching degree between participants and meeting topics, obtain the correlation matching degree, and optimize the grouping of participants based on the correlation matching degree; Monitor the deviation of the meeting agenda in real time during the meeting. When the deviation exceeds the preset deviation threshold, issue a reminder signal and re-execute the optimized grouping after confirmation by the participants. The access rights and document access rights of the participants after the optimized grouping are dynamically allocated, and the scope of shared documents is determined by the participants with upper-level permissions in the same group, and the document access rights of the participants with lower-level permissions are revoked after the meeting.

[0006] In a preferred embodiment, the steps of synchronizing meeting information in mailboxes, calendars, and instant messaging tools, and identifying and extracting meeting time, participants, and core topics from the meeting information, include: Through the preset API interface, real-time collection of meeting invitation emails in the mailbox, schedule events in the calendar, and group announcements in instant messaging tools; Identify time information in the meeting text content, convert it into a unified time format for recording, and extract the list of participants; Using natural language processing, keywords are extracted from meeting topics and agenda descriptions to construct topic semantic vectors. Similarity calculations are performed based on the topic semantic vectors to screen out core topics.

[0007] In a preferred embodiment, when there are differences in the same meeting information in the mailbox, calendar, and instant messaging tool, priority is given to determining whether the time information in the same meeting information is consistent. If they are inconsistent, the meeting information closest to the current time is selected as the benchmark; When the time information in the same meeting information is consistent, the list of participants and the topic description are further compared, and the meeting information with the highest information completeness is selected as the benchmark.

[0008] In a preferred embodiment, the step of comprehensively calculating the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics includes: Calculate the time interval between the meeting start time and the current time point, map the time interval to a preset time urgency score interval, and record the mapping result as the first evaluation indicator; Based on the preset participant rank weight table and the current participant list, calculate the rank weight score of each participant and record the total score as the second evaluation indicator; Taking the real-time evaluation node as the end point, reversely construct the sample period and compare the keyword overlap between the participants' work documents and the meeting topics during the sample period, and record it as the third evaluation indicator; The first evaluation indicator, the second evaluation indicator, and the third evaluation indicator are superimposed and calculated according to a preset proportion parameter, and the superimposed calculation result is output as a conference priority score.

[0009] In a preferred embodiment, the step of generating a dynamically sorted conference list based on conference priority scores includes: Establish an initial sorting queue based on the meeting priority score, where the meeting priority score is positively correlated with the sorting rank; Real-time monitoring of new meeting information and parameter changes of existing meetings. When updates to meeting time, participants, or topic keywords are detected, the meeting priority score recalculation mechanism is triggered. If there is no new meeting information and the existing meeting information has not changed, the initial sorting queue will be directly output as the current meeting list; When the conference priority score recalculation mechanism is executed, the changed item in the parameter change event is identified, and the first evaluation indicator, the second evaluation indicator, or the third evaluation indicator is adjusted according to the changed item, and then the conference priority score is recalculated; The initial sorting queue is updated according to the recalculated conference priority scores, and the updated initial sorting queue is output as the current conference list.

[0010] In a preferred embodiment, the steps of identifying the matching degree between the conference participants and the conference topics, obtaining the correlation matching degree, and optimizing the grouping of the conference participants based on the correlation matching degree include: Collect participants' historical work documents, project participation records, and role tag information in real time, and extract keywords related to the meeting topics through natural language processing; Vectorize the domain keywords and the conference topic keywords to obtain a first feature vector corresponding to the domain keywords and a second feature vector corresponding to the conference topic keywords; Calculate the similarity between the first eigenvector and the second eigenvector to generate a preliminary matching score; The attendance frequency of participants in similar meetings within the preset period and the duration of the current meeting are added as adjustment coefficients to modify the preliminary matching score and obtain the comprehensive correlation matching degree. Preset the grouping threshold, compare the comprehensive correlation matching degree with the grouping threshold, and match each participant to the corresponding group; Among them, the grouping groups were preset into three groups, including the core group, the conventional group, and the observation group; The core group corresponds to the highest grouping threshold, and the observation group corresponds to the lowest grouping threshold.

[0011] In a preferred embodiment, the method of monitoring the deviation of the conference agenda in real time during the conference, and issuing a reminder signal when the deviation exceeds a preset deviation threshold, and re-performing the step of optimizing the grouping after confirmation by the participants, includes: Capture the voice data in the meeting in real time and convert it into text data. Extract the actual keywords in the text data, compare them with the preset topic keywords, calculate the topic deviation ratio, and record it as the topic deviation degree. If the topic deviation is lower than the deviation threshold, the current grouping remains unchanged; If the deviation of the topic reaches or exceeds the deviation threshold, a reminder signal will be immediately sent to the core group. After confirmation by the core group members, it will indicate that the meeting topic needs to be changed, and the matching degree identification between participants and meeting topics and the optimized grouping process of participants will be re-executed; If the core group members have not confirmed, the deviation of the agenda will be continuously monitored and the current grouping status will be maintained until the core group members confirm or the meeting ends.

[0012] In a preferred solution, the step of dynamically allocating access rights and document access rights of the participants after the optimized grouping includes: Establish an authority level matrix based on optimized grouping, mapping the core group, regular group, and observation group to high, medium, and low authority levels respectively; According to the grouping results of the participants, the corresponding permission levels are automatically associated, and the documents that are only accessible to the core group are filtered out from the document access list that matches the permission level and marked as documents to be shared; The document to be shared is pushed to the core group members, and a query is issued to ask whether to share it. After the core group members confirm sharing, the sharing scope definition process is triggered, and the core group members specify the sharing objects and sharing scope; Among them, when there are multiple core group members, after any core group member completes the sharing confirmation, it will be automatically synchronized to all core group members, and the document sharing operation will be performed after all core group members have confirmed.

[0013] The present invention also provides an intelligent online conference management system based on smart office, using the above-mentioned intelligent online conference management method based on smart office, including: Initialization module, used to synchronize meeting information from mailboxes, calendars, and instant messaging tools, and identify and extract meeting time, participants, and core topics from meeting information; The list generation module is used to comprehensively calculate the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics, and generate a dynamically sorted meeting list based on the meeting priority score; The grouping module is used to identify the matching degree between participants and meeting topics, obtain the correlation matching degree, and optimize the grouping of participants based on the correlation matching degree; The meeting monitoring module is used to monitor the deviation of the meeting agenda in real time during the meeting. When the deviation exceeds the preset deviation threshold, it will issue a reminder signal and re-execute the optimized grouping after the participants confirm. The permission allocation module is used to dynamically allocate the access rights and document access rights of participants after optimized grouping. The scope of shared documents is determined by the participants with upper-level permissions in the same group, and the document access rights of the participants with lower-level permissions are revoked after the meeting.

[0014] And, an electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned intelligent management method for online meetings based on smart office.

[0015] The technical effects achieved by the present invention are: The present invention realizes efficient organization and intelligent monitoring of conference information by integrating multi-dimensional requirements such as information synchronization, topic monitoring and authority allocation in the conference management process. It can automatically synchronize and integrate conference information from mailboxes, calendars and instant messaging tools, accurately extract meeting time, participants and core topics, and effectively avoid the problem of missing information or untimely synchronization. At the same time, by comprehensively calculating the conference priority score, it can automatically generate a dynamically sorted conference list to help users quickly identify and prioritize important meetings, thereby improving the flexibility and efficiency of conference management. In addition, the present invention also optimizes the grouping strategy to identify the matching degree between participants and conference topics, realizes accurate grouping of participants, ensures the pertinence and effectiveness of conference discussions, and can monitor the deviation of topics in real time during the meeting, and issue reminders in time when the deviation exceeds the preset threshold, effectively avoiding the problem of low meeting efficiency caused by topic deviation. At the same time, it can dynamically allocate access rights and document access rights according to the grouping results of participants, ensuring the security and controllability of conference information. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flow chart of the method of the present invention; Figure 2 It is a schematic diagram of the system modules of the present invention; Figure 3 It is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive of other embodiments.

[0020] Furthermore, the present invention is described in detail with reference to schematic diagrams. For ease of illustration, when describing the embodiments of the present invention, cross-sectional views illustrating device structures may be partially enlarged and not to scale. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of protection of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0021] See also Figure 1 As shown, the present invention provides an online conference intelligent management method based on smart office, including: S1. Synchronize meeting information from mailboxes, calendars, and instant messaging tools, and identify and extract meeting times, participants, and core topics from the meeting information. In step S1, with the continuous development of information technology, the way of meeting is also constantly evolving. Online meetings have gradually become mainstream due to their convenience and efficiency. In this embodiment, the meeting information in the mailbox, calendar and instant messaging tools is first synchronized and integrated, and the meeting time, participants and core topics are extracted from the meeting information. This can effectively avoid omissions or duplications caused by information dispersion and ensure the accuracy and completeness of the meeting information. The steps of synchronizing the meeting information in the mailbox, calendar and instant messaging tools, and identifying and extracting the meeting time, participants and core topics in the meeting information include: Through the preset API interface, real-time collection of meeting invitation emails in the mailbox, schedule events in the calendar, and group announcements in instant messaging tools; Identify time information in the meeting text content, convert it into a unified time format for recording, and extract the list of participants; Using natural language processing, we extract keywords from meeting topics and agenda descriptions, construct topic semantic vectors, and perform similarity calculations based on topic semantic vectors to identify core topics. Specifically, when determining the meeting time, participants and core topics in the meeting information, it will first use the pre-set API interface to achieve data exchange with mailboxes, calendars and instant messaging tools to ensure the real-time and synchronization of meeting information. For meeting invitation emails in the mailbox, it will intelligently identify the email subject, body and attachments, and extract the specific time of the meeting, the list of participants and the core topics of the meeting. For schedule events in the calendar, it will parse the title, description and participant information of the schedule, and also extract the key meeting elements. For group announcements of instant messaging tools, it will use natural language processing technology to understand the announcement content and identify information points related to the meeting. When extracting the meeting time, it can intelligently identify and convert different formats. Time expressions, such as "tomorrow afternoon at 3 o'clock" or "May 15, 2023, 10:00 am", are uniformly converted into a standard time format to facilitate subsequent time management and priority sorting. At the same time, the list of participants will be cleaned and deduplicated to ensure the accuracy and redundancy of the list. When screening core topics, natural language processing technology is used to conduct in-depth analysis of meeting topics and agenda descriptions, extract keywords, and construct topic semantic vectors. By calculating the similarity between different topic semantic vectors, the most critical and core topics can be intelligently identified, providing strong support for subsequent meeting management and optimized grouping. The similarity calculation method can be used to use cosine similarity or Pearson similarity coefficient to ensure the efficiency of meeting preparation.

[0022] In addition, when there are discrepancies between the same meeting information in the mailbox, calendar, and instant messaging tool, priority will be given to determining whether the time information in the same meeting information is consistent. If there is any inconsistency, the meeting information closest to the current time will be used as the benchmark; When the time information in the same meeting information is consistent, the list of participants and topic descriptions are further compared, and the meeting information with the highest information completeness is selected as the benchmark; In the above, the same meeting information received in the mailbox, calendar and instant messaging tools may still be inconsistent. In this case, the time information of the same meeting information in different sources will be extracted first and compared accordingly. If the time information is inconsistent, the version closest to the current time will be selected as the benchmark to ensure the timeliness of the meeting arrangement; if the time information is consistent, the level of detail of the description of the participants and topics will be further compared, and the version with the most detailed information will be selected as the final basis, so as to ensure the accuracy and completeness of the meeting information, avoid meeting arrangement errors caused by information bias, and improve meeting efficiency and participant experience.

[0023] S2. Calculate the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics, and generate a dynamically sorted meeting list based on the meeting priority score; In step S2, when generating the meeting list, the meeting priority score will be comprehensively calculated based on factors such as the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics. Based on this meeting priority score, all pending meetings will be dynamically sorted to generate a meeting priority list with real-time updating function. The step of comprehensively calculating the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics includes: Calculate the time interval between the meeting start time and the current time point, map the time interval to a preset time urgency score interval, and record the mapping result as the first evaluation indicator; Based on the preset participant rank weight table and the current participant list, calculate the rank weight score of each participant and record the total score as the second evaluation indicator; Taking the real-time evaluation node as the end point, reversely construct the sample period and compare the keyword overlap between the participants' work documents and the meeting topics during the sample period, and record it as the third evaluation indicator; The first evaluation indicator, the second evaluation indicator, and the third evaluation indicator are superimposed and calculated according to a preset proportional parameter, and the superimposed calculation result is output as a conference priority score; Specifically, when calculating the meeting priority score, the time interval between the meeting start time and the current time point will be calculated first, and the time interval will be mapped according to the preset time urgency score interval, and the mapping result will be recorded as the first evaluation indicator. The time urgency score interval can be set according to the actual situation. For example, the closer to the meeting start time, the higher the time urgency score. Then, based on the preset participant rank weight table, the rank weight table records the weight coefficients corresponding to personnel of different ranks. Combined with the current list of participants, the rank weight score of each participant can be calculated, and the rank weight scores are summed up as the first evaluation indicator. The second evaluation indicator, in addition, in order to evaluate the relevance of the topic, the real-time evaluation node will be used as the end point to reversely construct a sample period. The sample period is a time window, such as the past week or month. Then, the keyword overlap between the work documents of the participants and the meeting topics during the sample period is compared. The keyword overlap can reflect the degree of relevance between the participants and the meeting topics. Finally, it is recorded as the third evaluation indicator. Finally, the first evaluation indicator, the second evaluation indicator and the third evaluation indicator are weighted and summed according to the preset proportion parameters to obtain the meeting priority score. The higher the meeting priority score, the higher the priority of the meeting and the more priority it needs to be arranged.

[0024] Secondly, the steps for generating a dynamically sorted meeting list based on the meeting priority scores include: Establish an initial sorting queue based on the meeting priority score, where the meeting priority score is positively correlated with the sorting rank; Real-time monitoring of new meeting information and parameter changes of existing meetings. When updates to meeting time, participants, or topic keywords are detected, the meeting priority score recalculation mechanism is triggered. If there is no new meeting information and the existing meeting information has not changed, the initial sorting queue will be directly output as the current meeting list; When the conference priority score recalculation mechanism is executed, the changed item in the parameter change event is identified, and the first evaluation indicator, the second evaluation indicator, or the third evaluation indicator is adjusted according to the changed item, and then the conference priority score is recalculated; Update the initial sorting queue based on the recalculated conference priority score, and output the updated initial sorting queue as the current conference list; Specifically, when generating a meeting list, an initial sorting queue based on the meeting priority score will be established first. The higher the meeting priority score, the higher the meeting ranking in the queue will be, so as to ensure that high-priority meetings can be displayed first. Subsequently, new meeting information and parameter change events of existing meetings will be monitored in real time. Parameter change events may include adjustments to meeting time, changes in participants, or updates to topic keywords. Once a change event is detected, the meeting priority score recalculation mechanism will be immediately triggered to re-evaluate the affected meetings. During the recalculation process, the specific change items in the parameter change event will be identified, and the first evaluation indicator, the second evaluation indicator, or the third evaluation indicator will be adjusted accordingly based on the change items. After the adjustment is completed, the meeting priority score will be recalculated, and the initial sorting queue will be updated based on the new meeting priority score result. Finally, the updated sorting queue will be output as the current meeting list, so as to ensure the dynamic and real-time nature of the meeting list, so that participants can obtain the latest and most accurate meeting information at any time, thereby improving the efficiency and effectiveness of meeting management. S3. Identify the matching degree between the participants and the meeting topics, obtain the correlation matching degree, and optimize the grouping of the participants based on the correlation matching degree; In step S3, before the meeting is executed, the matching degree between the participants and the meeting topic is first identified to obtain the correlation matching degree. Based on the correlation matching degree, the participants are optimized and grouped to ensure that each participant can participate in the discussion of topics related to their professional field or interests, thereby improving the pertinence and effectiveness of the meeting. The steps of identifying the matching degree between the participants and the meeting topic, obtaining the correlation matching degree, and optimizing the grouping of the participants based on the correlation matching degree include: Collect participants' historical work documents, project participation records, and role tag information in real time, and extract keywords related to the meeting topics through natural language processing; Vectorize the domain keywords and the conference topic keywords to obtain a first feature vector corresponding to the domain keywords and a second feature vector corresponding to the conference topic keywords; Calculate the similarity between the first eigenvector and the second eigenvector to generate a preliminary matching score; The attendance frequency of participants in similar meetings within the preset period and the duration of the current meeting are added as adjustment coefficients to modify the preliminary matching score and obtain the comprehensive correlation matching degree. Preset the grouping threshold, compare the comprehensive correlation matching degree with the grouping threshold, and match each participant to the corresponding group; Among them, the grouping groups were preset into three groups, including the core group, the conventional group, and the observation group; The core group corresponds to the highest grouping threshold, and the observation group corresponds to the lowest grouping threshold; Specifically, when optimizing the grouping of participants, the participants' historical work documents, project participation records, and role label information are first collected to reflect the participants' professional fields, past experiences, and interest preferences. Then, domain keywords related to the conference topics are extracted through natural language processing technology. Domain keywords are the basis for judging the degree of matching between participants and conference topics. Then, the domain keywords and the keywords of the conference topics are vectorized to obtain the first eigenvector and the second eigenvector. The vectorized representation can convert text information into numerical form, which is convenient for subsequent similarity calculation. By calculating the similarity of the first eigenvector and the second eigenvector, a preliminary matching score can be generated. The matching score can reflect the closeness of the association between the participants and the conference topics. In addition, the attendance frequency of participants in the same type of meetings within the preset period and the duration of the current meeting agenda are added as adjustment coefficients to correct the preliminary matching score and obtain a more accurate comprehensive correlation matching degree. Attendance frequency can reflect the participants' familiarity with similar topics, while the duration of the agenda is related to the time participants can devote, both of which will affect the final grouping results. Finally, a grouping threshold will be preset, and the comprehensive correlation matching degree will be compared with the grouping threshold. Based on the comparison results, the participants will be matched to the corresponding groups. In this embodiment, the grouping groups are preset into three groups, including a core group, a regular group, and an observation group. The core group has the highest grouping threshold, which means that only participants who are highly relevant to the meeting topic will be included in the core group and play a decision-making role in the meeting. The regular group has a moderate grouping threshold, which includes participants who have a certain degree of relevance to the meeting topic and provide useful suggestions and opinions in the meeting. The observation group has the lowest grouping threshold and is mainly composed of participants with a low degree of relevance to the meeting topic. They participate in the meeting with the purpose of understanding the meeting topic and knowledge in related fields through observation and learning. Through this optimized grouping mechanism, not only the meeting efficiency is improved, but also it ensures that each participant can clearly define his or her own role.

[0025] S4. Real-time monitoring of the deviation of the agenda items during the meeting. When the deviation exceeds the preset deviation threshold, a reminder signal is issued, and after confirmation by the participants, the optimized grouping is re-executed. In step S4, during the meeting, the topic deviation of the meeting topic will be monitored in real time. When the topic deviation exceeds the preset deviation threshold, a reminder signal will be immediately issued to prompt the participants whether to switch topics. After the participants confirm, the optimized grouping will be re-executed to ensure the smooth progress of the meeting. The steps of monitoring the topic deviation of the meeting topic in real time during the meeting, issuing a reminder signal when the topic deviation exceeds the preset deviation threshold, and re-executing the optimized grouping after the participants confirm include: Capture the voice data in the meeting in real time and convert it into text data. Extract the actual keywords in the text data, compare them with the preset topic keywords, calculate the topic deviation ratio, and record it as the topic deviation degree. If the topic deviation is lower than the deviation threshold, the current grouping remains unchanged; If the deviation of the topic reaches or exceeds the deviation threshold, a reminder signal will be immediately sent to the core group. After confirmation by the core group members, it will indicate that the meeting topic needs to be changed, and the matching degree identification between participants and meeting topics and the optimized grouping process of participants will be re-executed; If the core group members have not confirmed, the deviation of the topic will be continuously monitored and the current grouping status will be maintained until the core group members confirm or the meeting ends; Specifically, in the process of executing the optimized grouping, the voice data in the meeting will be captured in real time, and the voice data will be accurately converted into text data through voice recognition technology. Speech recognition can specifically adopt the deep neural network model commonly used in existing technologies, such as recurrent neural network (RNN) or long short-term memory network (LSTM). Then, the actual keywords in the text data will be extracted, and the actual keywords will be compared with the preset topic keywords. Through this comparison process, the topic deviation ratio can be calculated. The topic deviation ratio is recorded as the topic deviation degree, which is used to measure the degree of deviation between the current discussion content and the preset topic. The topic deviation degree will then be compared with the preset deviation threshold. When the topic deviation degree is lower than this threshold, it indicates that the meeting is still proceeding smoothly. At this time, the current grouping will be maintained unchanged to continue to support the smooth progress of the meeting. However, once the topic deviation degree reaches or exceeds the preset If the deviation threshold is exceeded, the reminder mechanism will be triggered immediately, and a striking reminder signal will be sent to the core group members. This reminder signal is intended to attract the attention of the core group members, so that they can judge whether the meeting theme needs to be changed. The change of the meeting theme is conducive to the subsequent retrieval or call of meeting records, thereby improving the efficiency of the meeting. If the core group members confirm after receiving the reminder, it indicates that the meeting needs to adjust its direction. At this time, the matching identification process between participants and meeting topics will be re-executed. The re-matching process will be based on the new discussion focus to ensure that each participant can be assigned to the topic discussion group most relevant to his or her professional field or interest. Subsequently, the grouping will be optimized again to support the efficient progress of the meeting with the new group configuration. If the core group members do not confirm after receiving the reminder, they will continue to monitor the deviation of the topic while keeping the current group status unchanged until the core group members confirm or the meeting ends naturally.

[0026] S5. Dynamically allocate access rights and document access rights to the optimized grouped participants. Participants with higher-level permissions in the same group determine the scope of shared documents, and reclaim document access rights from participants with lower-level permissions after the meeting. In step S5, after the optimized grouping, the access rights and document access rights of the participants will be dynamically allocated. The participants with upper-level permissions in the same group will determine the scope of shared documents to ensure that the participants can obtain the required meeting materials in a timely manner. After the meeting, the document access rights of the participants with lower-level permissions will be automatically revoked to ensure the security of the meeting materials. The step of dynamically allocating the access rights and document access rights of the participants after the optimized grouping includes: Establish an authority level matrix based on optimized grouping, mapping the core group, regular group, and observation group to high, medium, and low authority levels respectively; According to the grouping results of the participants, the corresponding permission levels are automatically associated, and the documents that are only accessible to the core group are filtered out from the document access list that matches the permission level and marked as documents to be shared; The document to be shared is pushed to the core group members, and a query is issued to ask whether to share it. After the core group members confirm sharing, the sharing scope definition process is triggered, and the core group members specify the sharing objects and sharing scope; Among them, when there are multiple core group members, after any core group member completes the sharing confirmation, it will be automatically synchronized to all core group members, and the document sharing operation will be performed after all core group members have confirmed.

[0027] Specifically, when allocating document access rights, a permission level matrix based on optimized grouping is first established. The permission level matrix maps the core group, regular group, and observation group to three different permission levels: high, medium, and low. This is used to distinguish the differences in the access rights of participants in different groups to conference materials. Subsequently, based on the grouping results of the participants, the corresponding permission level is automatically associated with the participant, and documents matching the permission level are screened from the preset document access list. During this process, documents accessible only to the core group are marked as documents to be shared and used as the objects of subsequent sharing operations. The documents to be shared are then automatically pushed to the members of the core group and a query is issued asking whether they agree to implement document sharing. Once the core group members confirm sharing, the sharing scope demarcation process is triggered, and the core group members specify the specific sharing objects and sharing scope to ensure that the document can be circulated within the appropriate scope. In addition, it should be noted that when there are multiple core group members, a synchronization mechanism is implemented to ensure that the sharing confirmation of any core group member is automatically synchronized to all core group members. The document sharing operation is only executed after all core group members confirm, thereby ensuring the comprehensiveness and consistency of decision-making.

[0028] See also Figure 2 , an online conference intelligent management system based on smart office, using the above-mentioned online conference intelligent management method based on smart office, including: Initialization module, used to synchronize meeting information from mailboxes, calendars, and instant messaging tools, and identify and extract meeting time, participants, and core topics from meeting information; The list generation module is used to comprehensively calculate the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics, and generate a dynamically sorted meeting list based on the meeting priority score; The grouping module is used to identify the matching degree between participants and meeting topics, obtain the correlation matching degree, and optimize the grouping of participants based on the correlation matching degree; The meeting monitoring module is used to monitor the deviation of the meeting agenda in real time during the meeting. When the deviation exceeds the preset deviation threshold, it will issue a reminder signal and re-execute the optimized grouping after the participants confirm. The permission allocation module is used to dynamically allocate the access rights and document access rights of participants after optimized grouping. The scope of shared documents is determined by the participants with upper-level permissions in the same group, and the document access rights of the participants with lower-level permissions are revoked after the meeting.

[0029] In the above, the initialization module is responsible for synchronizing and integrating information from different platforms, such as meeting data in mailboxes, calendars, and instant messaging tools, and synchronously identifying key elements in meeting information, such as the specific time of the meeting, the list of participants, and the core topics of the meeting, so as to ensure the comprehensiveness and accuracy of the meeting information and lay the foundation for subsequent management processes. The list generation module is responsible for comprehensively evaluating the time urgency of the meeting, the importance of the participants, and the relevance of the topics based on the comprehensive integration of meeting information, and calculating the priority score of each meeting based on this. The meeting priority score can reflect the urgency and importance of the meeting. Then, based on the calculated meeting priority score, the meetings are dynamically sorted to generate a real-time updated meeting list. Participants can quickly understand the upcoming meetings and the priority order of the meetings through this list, so as to reasonably arrange their time and schedule and improve the efficiency of participating in the meeting. The grouping module is based on the participants People are grouped according to the matching degree between people and topics, ensuring that each member participates in the most relevant topics to improve the participation and discussion quality of the meeting. The grouping module can not only realize intelligent grouping, but also dynamically adjust the group configuration according to the actual progress of the meeting to cope with possible changes in topics, ensuring the flexibility and adaptability of the meeting. The meeting monitoring module can monitor the deviation of the meeting topic in real time. Once it is found that the meeting content deviates significantly from the preset topic, it will immediately send a reminder to the core group members to avoid the meeting from deviating from the topic and ensure the focus and efficiency of the meeting. The authority allocation module is responsible for managing the access rights of participants during the meeting. By dynamically allocating access rights, it ensures that participants can obtain the required meeting materials in a timely manner. At the same time, after the meeting, the authority allocation module will automatically reclaim the document access rights of participants with lower-level permissions, which not only improves the security of meeting materials, but also effectively prevents the leakage of meeting information.

[0030] See also Figure 3 , an electronic device, the electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the above-mentioned online meeting intelligent management method based on smart office.

[0031] In the above, the processor of the electronic device can be of various types, such as CPU, GPU, etc., to support efficient parallel processing and data calculation. The memory can be RAM, ROM, Flash memory, hard disk or solid-state drive, etc., for storing computer programs and meeting-related data to ensure data persistence and fast access. The processor executes the computer program in the memory to realize the synchronization of meeting information, generation of meeting lists, intelligent grouping of participants, real-time monitoring of meeting topics, and dynamic allocation of participant permissions. In addition, it can also include an arithmetic unit, input devices and output devices, etc. The arithmetic unit can be ALU, FPU, etc., for performing complex mathematical and logical operations. Input devices such as keyboard, mouse, touch screen, etc. are convenient for users to input instructions and data. Output devices such as display, printer, etc. are used to display meeting information and results to ensure convenient operation and intuitive presentation of information.

[0032] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0033] The foregoing is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained herein shall, unless otherwise specified or limited, be implemented in accordance with conventional means in the art.

Claims

1. An intelligent management method for online meetings based on smart office, characterized by: include: Synchronize meeting information from email, calendar, and instant messaging tools, and identify and extract meeting time, participants, and core topics from meeting information; The meeting priority score is calculated based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics. A dynamically sorted meeting list is generated based on the meeting priority score. Identify the matching degree between participants and meeting topics, obtain the correlation matching degree, and optimize the grouping of participants based on the correlation matching degree; Monitor the deviation of the meeting agenda in real time during the meeting. When the deviation exceeds the preset deviation threshold, issue a reminder signal and re-execute the optimized grouping after confirmation by the participants. The access rights and document access rights of the participants after the optimized grouping are dynamically allocated, and the scope of shared documents is determined by the participants with upper-level permissions in the same group, and the document access rights of the participants with lower-level permissions are revoked after the meeting.

2. The method for intelligent management of online conferences based on smart office according to claim 1, characterized in that: The steps of synchronizing the meeting information of the mailbox, calendar, and instant messaging tool, and identifying and extracting the meeting time, participants, and core topics in the meeting information include: Through the preset API interface, real-time collection of meeting invitation emails in the mailbox, schedule events in the calendar, and group announcements in instant messaging tools; Identify time information in the meeting text content, convert it into a unified time format for recording, and extract the list of participants; Using natural language processing, keywords are extracted from meeting topics and agenda descriptions to construct topic semantic vectors. Similarity calculations are performed based on the topic semantic vectors to screen out core topics.

3. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: When there are discrepancies between the same meeting information in the mailbox, calendar, and instant messaging tool, priority is given to determining whether the time information in the same meeting information is consistent. If they are inconsistent, the meeting information closest to the current time is used as the benchmark; When the time information in the same meeting information is consistent, the list of participants and the topic description are further compared, and the meeting information with the highest information completeness is selected as the benchmark.

4. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: The step of comprehensively calculating the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics includes: Calculate the time interval between the meeting start time and the current time point, map the time interval to a preset time urgency score interval, and record the mapping result as the first evaluation indicator; Based on the preset participant rank weight table and the current participant list, calculate the rank weight score of each participant and record the total score as the second evaluation indicator; Taking the real-time evaluation node as the end point, reversely construct the sample period and compare the keyword overlap between the participants' work documents and the meeting topics during the sample period, and record it as the third evaluation indicator; The first evaluation indicator, the second evaluation indicator, and the third evaluation indicator are superimposed and calculated according to a preset proportion parameter, and the superimposed calculation result is output as a conference priority score.

5. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: The step of generating a dynamically sorted conference list based on conference priority scores includes: Establish an initial sorting queue based on the meeting priority score, where the meeting priority score is positively correlated with the sorting rank; Real-time monitoring of new meeting information and parameter changes of existing meetings. When updates to meeting time, participants, or topic keywords are detected, the meeting priority score recalculation mechanism is triggered. If there is no new meeting information and the existing meeting information has not changed, the initial sorting queue will be directly output as the current meeting list; When the conference priority score recalculation mechanism is executed, the changed item in the parameter change event is identified, and the first evaluation indicator, the second evaluation indicator, or the third evaluation indicator is adjusted according to the changed item, and then the conference priority score is recalculated; The initial sorting queue is updated according to the recalculated conference priority scores, and the updated initial sorting queue is output as the current conference list.

6. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: The steps of identifying the matching degree between the conference participants and the conference topics, obtaining the correlation matching degree, and optimizing the grouping of the conference participants based on the correlation matching degree include: Collect participants' historical work documents, project participation records, and role tag information in real time, and extract keywords related to the meeting topics through natural language processing; Vectorize the domain keywords and the conference topic keywords to obtain a first feature vector corresponding to the domain keywords and a second feature vector corresponding to the conference topic keywords; Calculate the similarity between the first eigenvector and the second eigenvector to generate a preliminary matching score; The attendance frequency of participants in similar meetings within the preset period and the duration of the current meeting are added as adjustment coefficients to modify the preliminary matching score and obtain the comprehensive correlation matching degree. Preset the grouping threshold, compare the comprehensive correlation matching degree with the grouping threshold, and match each participant to the corresponding group; Among them, the grouping groups were preset into three groups, including the core group, the conventional group, and the observation group; The core group has the highest grouping threshold, and the observation group has the lowest grouping threshold.

7. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: The method of monitoring the deviation of the meeting agenda in real time during the meeting, and sending a reminder signal when the deviation exceeds a preset deviation threshold, and re-performing the step of optimizing the grouping after confirmation by the participants, includes: Capture the voice data in the meeting in real time and convert it into text data. Extract the actual keywords in the text data, compare them with the preset topic keywords, calculate the topic deviation ratio, and record it as the topic deviation degree. If the topic deviation is lower than the deviation threshold, the current grouping remains unchanged; If the deviation of the topic reaches or exceeds the deviation threshold, a reminder signal will be immediately sent to the core group. After confirmation by the core group members, it will indicate that the meeting topic needs to be changed, and the matching degree identification between participants and meeting topics and the optimized grouping process of participants will be re-executed; If the core group members have not confirmed, the deviation of the agenda will be continuously monitored and the current grouping status will be maintained until the core group members confirm or the meeting ends.

8. The method for intelligent management of online conferences based on intelligent office according to claim 1, characterized in that: The step of dynamically allocating access rights and document access rights to the participants after the optimized grouping includes: Establish an authority level matrix based on optimized grouping, mapping the core group, regular group, and observation group to high, medium, and low authority levels respectively; According to the grouping results of the participants, the corresponding permission levels are automatically associated, and the documents that are only accessible to the core group are filtered out from the document access list that matches the permission level and marked as documents to be shared; The document to be shared is pushed to the core group members, and a query is issued to ask whether to share it. After the core group members confirm sharing, the sharing scope definition process is triggered, and the core group members specify the sharing objects and sharing scope; Among them, when there are multiple core group members, after any core group member completes the sharing confirmation, it will be automatically synchronized to all core group members, and the document sharing operation will be performed after all core group members have confirmed.

9. An online conference intelligent management system based on smart office, characterized by: The method for intelligent management of online meetings based on intelligent office according to any one of claims 1 to 8 comprises: Initialization module, used to synchronize meeting information from mailboxes, calendars, and instant messaging tools, and identify and extract meeting time, participants, and core topics from meeting information; The list generation module is used to comprehensively calculate the meeting priority score based on the time difference between the meeting start time and the current time, the importance level of the participants, and the relevance of the topics, and generate a dynamically sorted meeting list based on the meeting priority score; The grouping module is used to identify the matching degree between participants and meeting topics, obtain the correlation matching degree, and optimize the grouping of participants based on the correlation matching degree; The meeting monitoring module is used to monitor the deviation of the meeting agenda in real time during the meeting. When the deviation exceeds the preset deviation threshold, it will issue a reminder signal and re-execute the optimized grouping after the participants confirm. The permission allocation module is used to dynamically allocate the access rights and document access rights of participants after optimized grouping. The scope of shared documents is determined by the participants with upper-level permissions in the same group, and the document access rights of the participants with lower-level permissions are revoked after the meeting.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the online conference intelligent management method based on smart office as described in any one of claims 1 to 8.

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