Group chat message intelligent regulation and control method, device and equipment and storage medium
By calculating the popularity value of group chat messages based on multi-dimensional interaction metrics and user behavior data, and dynamically adjusting the reminder strategy, the problem of important message blocking in the traditional group chat do-not-disturb mode is solved, achieving accurate filtering and personalized reminders, and improving user experience and communication efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CETC CYBERSPACE SECURITY TECH CO LTD
- Filing Date
- 2026-02-27
- Publication Date
- 2026-05-15
AI Technical Summary
Traditional group chat do-not-disturb mode lacks intelligent filtering, resulting in the complete blocking of important messages and an inability to dynamically adjust reminder strategies based on real-time interactions, leading to a poor user experience.
Based on multi-dimensional interaction metrics and user historical behavior data, the initial popularity value and relevance coefficient of group chat messages are calculated, the reminder threshold is dynamically adjusted, reminders are only given for important messages, and the reminder strategy is optimized based on user feedback.
It enables precise layered filtering of group chat messages, avoiding interference from irrelevant information, ensuring that key information is not missed, and improving user experience and communication efficiency.
Smart Images
Figure CN122053554A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of instant messaging technology, and in particular to a method, apparatus, device, and storage medium for intelligent control of group chat messages. Background Technology
[0002] With the popularization of instant messaging applications, the number of groups users join is increasing day by day. To avoid information overload, users usually set the Do Not Disturb mode for non-important groups. However, the traditional Do Not Disturb mode has the following problems: (1) All or nothing mode, either receive all messages or completely block them, lacking intelligent filtering; (2) Missing important messages: may miss messages that are highly relevant to the user, such as being @mentioned or discussing topics related to the user; (3) Lack of dynamic adjustment, unable to dynamically adjust the reminder strategy according to the real-time interaction situation; (4) Poor user experience, users need to manually switch the Do Not Disturb setting frequently.
[0003] As can be seen from the above, how to prevent important messages from being completely blocked by Do Not Disturb mode is a problem that urgently needs to be solved. Summary of the Invention
[0004] In view of this, the purpose of this invention is to provide a method, apparatus, device, and storage medium for intelligent control of group chat messages, capable of preventing important messages from being completely blocked by the Do Not Disturb mode. The specific solution is as follows: Firstly, this application provides a method for intelligent control of group chat messages, including: Obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message. A corresponding content relevance database is established based on user historical behavior data. The relevance coefficient corresponding to the target group chat message is determined using the content relevance database. The target popularity value is determined based on the initial popularity value and the relevance coefficient. Determine whether the target popularity value is greater than the target alert threshold; the target alert threshold is a threshold determined based on the user's historical behavior data; If the target popularity value is greater than the target reminder threshold, the target group chat message is reminded to the user's terminal, and target feedback information is determined based on the user's response to the target group chat message. The target reminder threshold is then adjusted using the target feedback information.
[0005] Optionally, before determining the indicator weights corresponding to the target group chat message based on multi-dimensional interaction indicators, the method further includes: Determine the target notification mode selected by the user; If the target notification mode is the first mode, then after the target condition is triggered, the target number of target messages will be notified to the user terminal, and then the group chat do-not-disturb mode will be restored; the target condition is that there are messages containing the user terminal's nickname in the group chat; the target messages include target group chat messages; If the target notification model is the second mode, then the step of determining the indicator weight corresponding to the target group chat message based on multi-dimensional interactive indicators is triggered.
[0006] Optionally, the method for constructing the multi-dimensional interaction indicators includes: The interaction scenario in the target group chat message containing the user's nickname is determined as the first interaction indicator, and the interaction scenario in the target group chat message in which the target user replies to the user is determined as the second interaction indicator; the target user is other users in the group chat besides the user. The interaction scenario in the target group chat message where the target user references the user's historical group chat message is determined as the third interaction indicator, and the interaction scenario in the target group chat message where the user's target keyword is present is determined as the fourth interaction indicator. The group activity level corresponding to the target group chat message is determined as the fifth interaction indicator. A multi-dimensional interaction indicator is constructed based on the first interaction indicator, the second interaction indicator, the third interaction indicator, the fourth interaction indicator, and the fifth interaction indicator.
[0007] Optionally, the step of acquiring the target group chat message to be reminded, determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and determining the initial popularity value corresponding to the target group chat message using the indicator weight includes: Obtain the target group chat messages to be reminded, and assign corresponding weights to each interaction indicator in the multi-dimensional interaction indicators based on the importance of the indicators; The indicator weights corresponding to the target group chat message are determined using the weights, and the initial popularity value corresponding to the target group chat message is determined based on the indicator weights.
[0008] Optionally, the step of establishing a corresponding content relevance database based on user historical behavior data, and using the content relevance database to determine the relevance coefficient corresponding to the target group chat message, includes: User historical behavior data is constructed based on the user's target keywords, topics of interest, and historical viewing or replying behavior data from the user's terminal. A corresponding content relevance database is established using the user's historical behavior data, and the relevance coefficient corresponding to the target group chat message is determined based on the content relevance database.
[0009] Optionally, determining the target popularity value based on the initial popularity value and in combination with the correlation coefficient includes: The time decay coefficient is determined based on the occurrence time of the target group chat message and using a preset time decay factor. The target heat value is determined based on the initial heat value, combined with the time decay coefficient and the correlation coefficient.
[0010] Optionally, if the target popularity value is greater than the target reminder threshold, then the user is reminded of the target group chat message, and target feedback information is determined based on the user's response to the target group chat message, and the target reminder threshold is adjusted using the target feedback information, including: If the target popularity value is greater than the target reminder threshold, then the user terminal is reminded of the target group chat message, and the user terminal's response behavior to the target group chat message is determined. If the behavior involves the user adjusting the group chat do-not-disturb mode, then the corresponding explicit feedback information is determined. If the behavior is that the user ignores, views, or replies to the target group chat message, then the corresponding implicit feedback information is determined. Target feedback information is constructed based on the explicit feedback information and the implicit feedback information, and the target reminder threshold is adjusted using the target feedback information and the adaptive adjustment factor.
[0011] Secondly, this application provides a group chat message intelligent control device, comprising: The initial popularity value determination module is used to obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message. The target popularity value determination module is used to establish a corresponding content relevance database based on user historical behavior data, use the content relevance database to determine the relevance coefficient corresponding to the target group chat message, and determine the target popularity value based on the initial popularity value and the relevance coefficient. A popularity value determination module is used to determine whether the target popularity value is greater than a target alert threshold; the target alert threshold is a threshold determined based on the user's historical behavior data; The threshold adjustment module is used to remind the user of the target group chat message if the target popularity value is greater than the target reminder threshold, and to determine the target feedback information based on the user's response to the target group chat message, and to adjust the target reminder threshold using the target feedback information.
[0012] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is used to execute the computer program to implement the aforementioned intelligent control method for group chat messages.
[0013] Fourthly, this application provides a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned intelligent control method for group chat messages.
[0014] This application acquires target group chat messages to be reminded, determines the indicator weights corresponding to the target group chat messages based on multi-dimensional interaction indicators, and uses the indicator weights to determine the initial popularity value of the target group chat messages; establishes a corresponding content relevance database based on user historical behavior data, uses the content relevance database to determine the relevance coefficients corresponding to the target group chat messages, and determines the target popularity value based on the initial popularity value and the relevance coefficients; determines whether the target popularity value is greater than a target reminder threshold; the target reminder threshold is a threshold determined based on the user historical behavior data; if the target popularity value is greater than the target reminder threshold, the user is reminded of the target group chat messages, and target feedback information is determined based on the user's response to the target group chat messages, and the target reminder threshold is adjusted using the target feedback information.
[0015] As can be seen from the above, this application calculates initial popularity based on multi-dimensional interaction indicators and weights, which can assign high weights to messages that are directly relevant to users, achieving preliminary and accurate stratification of group chat messages and avoiding treating all messages equally. The content relevance database established based on users' historical behavior can match corresponding relevance coefficients to topics of interest for different users, making the target popularity value more aligned with users' personalized needs. The target reminder threshold is determined based on users' historical behavior, enabling dynamic intelligent filtering and breaking the traditional all-or-nothing message pattern. Only messages important to users will trigger reminders, reducing interference from irrelevant information. In this way, adjusting the threshold based on user response feedback can form a closed-loop optimization, increasingly conforming to user habits, ensuring that key information is not missed, and significantly improving user experience and communication efficiency. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0017] Figure 1 This application discloses a flowchart of a group chat message intelligent control method. Figure 2 This is a schematic diagram of a group chat message intelligent control framework disclosed in this application; Figure 3 This application discloses a flowchart of a specific intelligent control method for group chat messages; Figure 4 This is a schematic diagram of the structure of a group chat message intelligent control device disclosed in this application; Figure 5 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Currently, traditional do-not-disturb modes lack intelligent filtering, either receiving all messages or completely blocking them, and may miss highly relevant messages, such as mentions or discussions about the user. Furthermore, they cannot dynamically adjust notification strategies based on real-time interaction, resulting in a poor user experience. To address this, this application provides an intelligent group chat message control method that adjusts thresholds based on user response feedback, creating a closed-loop optimization that increasingly aligns with user habits, ensuring no key information is missed, and significantly improving user experience and communication efficiency.
[0020] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a method for intelligent control of group chat messages, including: Step S11: Obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message.
[0021] In this embodiment, group chat messages are controlled based on the target notification method selected by the user. If the target notification mode is the first mode, a fixed target number of group chat messages are notified after a message directly @ing the user appears. The target number can be set according to the actual situation. If the target notification mode is the second mode, the step of determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators is triggered. Specifically, before determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, the method further includes: determining the target notification mode selected by the user; if the target notification mode is the first mode, the target number of target messages are notified to the user after the target condition is triggered, and then the group chat do-not-disturb mode is restored; the target condition is that there is a message containing the user's nickname in the group chat; the target message includes the target group chat message; if the target notification mode is the second mode, the step of determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators is triggered.
[0022] Understandably, the interaction scenario of directly mentioning the user's nickname is determined as the first interaction indicator, which has the highest weight. The interaction scenario of indirectly mentioning the user's nickname is determined as the second interaction indicator, such as replying to a message directly mentioned by the user. The interaction scenario of referencing the user's previous statements is determined as the third interaction indicator. The interaction scenario of containing the user's commonly used keywords in the target group chat message is determined as the fourth interaction indicator. The group activity corresponding to the target group chat message is determined as the fifth interaction indicator. The group activity is determined based on the number of speakers and message frequency in the group to which the target group chat message belongs. In one specific implementation, the weight of the first interaction indicator is 40%, the weight of the second interaction indicator is 20%, the weights of the third and fourth interaction indicators are both 15%, and the weight of the fifth interaction indicator is 10%. The weight allocation can also be adjusted based on the actual situation.
[0023] Specifically, the method for constructing the multi-dimensional interaction metrics includes: determining an interaction scenario in the target group chat message containing the user's nickname as a first interaction metric; determining an interaction scenario in the target group chat message containing a target user replying to the user as a second interaction metric; the target user being other users in the group chat besides the user; determining an interaction scenario in the target group chat message containing a target user referencing the user's historical group chat messages as a third interaction metric; determining an interaction scenario in the target group chat message containing the user's target keywords as a fourth interaction metric; determining the group activity corresponding to the target group chat message as a fifth interaction metric; and constructing a multi-dimensional interaction metric based on the first, second, third, fourth, and fifth interaction metrics.
[0024] In this embodiment, the indicator weight of the target group chat message is determined based on the weights corresponding to each interaction indicator. In one specific implementation, if the target group chat message contains a target keyword and directly @ the user's nickname, and the group activity level of the group is greater than the target activity level threshold, then the corresponding initial popularity value is 100×40%+0×20%+0×15%+100×15%+100×10%=65 points. Specifically, the step of obtaining the target group chat message to be reminded, determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and determining the initial popularity value corresponding to the target group chat message using the indicator weights includes: obtaining the target group chat message to be reminded, assigning corresponding weights to each interaction indicator in the multi-dimensional interaction indicators based on indicator importance; determining the indicator weight corresponding to the target group chat message using each of the weights, and determining the initial popularity value corresponding to the target group chat message based on the indicator weights.
[0025] Step S12: Establish a corresponding content relevance database based on user historical behavior data, use the content relevance database to determine the relevance coefficient corresponding to the target group chat message, and determine the target popularity value based on the initial popularity value and the relevance coefficient.
[0026] In this embodiment, the system collects frequently discussed topics, historical message types viewed / replied, and areas of interest from the user's device, and organizes this data into a content relevance database. For example, if the user frequently replies to messages related to "product operations," the system will mark "product operations" as a highly relevant topic in the content relevance database. The system then compares the target group chat message with the content relevance database and determines the relevance coefficient based on the comparison results. For example, a relevance coefficient greater than 1 indicates high relevance, and less than 1 indicates low relevance. Specifically, establishing a corresponding content relevance database based on user historical behavior data and determining the relevance coefficient corresponding to the target group chat message using the content relevance database includes: constructing user historical behavior data based on the user's target keywords, topics of interest, and historical message viewing or reply behavior data; establishing a corresponding content relevance database using the user historical behavior data; and determining the relevance coefficient corresponding to the target group chat message based on the content relevance database.
[0027] It is understandable that a preset time decay factor is set, meaning the popularity of the target group chat message will decrease over time. For example, the preset time decay factor for a newly sent target group chat message is 1, and the preset time decay factor is 0.9 after one minute. The decay rate corresponding to the preset time decay factor can be set according to the actual situation. The target popularity value is obtained by multiplying the initial popularity value, the time decay factor, and the relevance coefficient. Specifically, determining the target popularity value based on the initial popularity value and the relevance coefficient includes: determining the time decay factor based on the appearance time of the target group chat message and using the preset time decay factor; and determining the target popularity value based on the initial popularity value and the time decay factor and the relevance coefficient.
[0028] Step S13: Determine whether the target popularity value is greater than the target reminder threshold; the target reminder threshold is a threshold determined based on the user's historical behavior data.
[0029] In this embodiment, after obtaining the target popularity value, it is determined whether the target popularity value is greater than the target reminder threshold; the target reminder threshold is a dynamically adjusted threshold. First, a basic reminder threshold is set, and the basic reminder threshold is adjusted using the user's historical behavior data and an adaptive adjustment factor to obtain the target reminder threshold.
[0030] Step S14: If the target popularity value is greater than the target reminder threshold, then the user terminal is reminded of the target group chat message, and the target feedback information is determined based on the user terminal's response to the target group chat message. The target reminder threshold is then adjusted using the target feedback information.
[0031] In this embodiment, if the target popularity value is greater than the target reminder threshold, the user is reminded of the target group chat message, and then the target feedback information for the target group chat message is determined. If the user manually adjusts the group chat message reminder, corresponding explicit feedback information is obtained. The viewing time and response data of the target group chat message received by the user are determined as implicit feedback information, wherein the explicit feedback information takes precedence over the implicit feedback information. The target reminder threshold is adjusted based on the target feedback information including the explicit and implicit feedback information, combined with an adaptive adjustment factor. For example, if the user repeatedly ignores the interaction scenario corresponding to the second interaction indicator, the target reminder threshold for the relevant group chat message is increased, and the weight corresponding to the second interaction indicator is decreased.
[0032] Specifically, if the target popularity value is greater than the target reminder threshold, the user is reminded of the target group chat message. Target feedback information is determined based on the user's response to the target group chat message, and the target reminder threshold is adjusted using this feedback information. This includes: if the target popularity value is greater than the target reminder threshold, the user is reminded of the target group chat message, and the user's response to the target group chat message is determined; if the response is that the user adjusts the group chat to a do-not-disturb mode, corresponding explicit feedback information is determined; if the response is that the user ignores, views, or replies to the target group chat message, corresponding implicit feedback information is determined; target feedback information is constructed based on the explicit and implicit feedback information, and the target reminder threshold is adjusted using the target feedback information and an adaptive adjustment factor.
[0033] As can be seen from the above, this application calculates initial popularity based on multi-dimensional interaction indicators and weights, which can assign high weights to messages that are directly relevant to users, achieving preliminary and accurate stratification of group chat messages and avoiding treating all messages equally. The content relevance database established based on users' historical behavior can match corresponding relevance coefficients to topics of interest for different users, making the target popularity value more aligned with users' personalized needs. The target reminder threshold is determined based on users' historical behavior, enabling dynamic intelligent filtering and breaking the traditional all-or-nothing message pattern. Only messages important to users will trigger reminders, reducing interference from irrelevant information. In this way, adjusting the threshold based on user response feedback can form a closed-loop optimization, increasingly conforming to user habits, ensuring that key information is not missed, and significantly improving user experience and communication efficiency.
[0034] As can be seen from the above embodiments, this application provides message reminders based on the target popularity value corresponding to the target group chat message. Therefore, the process of providing message reminders based on the target popularity value corresponding to the target group chat message is described.
[0035] Combination Figure 2 and Figure 3 As shown in the figure, an embodiment of the present invention discloses a specific method for intelligent control of group chat messages, including: In this embodiment, the target group chat message to be reminded is obtained. The interaction scenario that directly mentions the user's nickname is determined as the first interaction indicator, the interaction scenario that indirectly mentions the user's nickname is determined as the second interaction indicator, the interaction scenario that references the user's previous speech is determined as the third interaction indicator, the interaction scenario that contains the user's commonly used keywords in the target group chat message is determined as the fourth interaction indicator, and the group activity corresponding to the target group chat message is determined as the fifth interaction indicator. The initial popularity value corresponding to the target group chat message is determined based on the weights corresponding to the above interaction indicators.
[0036] It is understandable that, when determining the target notification method selected by the user, if the target notification mode is the first mode (simple mode), then after a message directly @ing the user appears, a fixed target number of group chat messages will be notified; if the target notification model is the second mode (dynamic learning mode), then the relevance coefficient corresponding to the target group chat message is determined based on a content relevance database; the content relevance database is constructed based on user historical behavior data; based on the initial popularity value and combined with the time decay coefficient and the relevance coefficient, a target popularity value is determined, and it is determined whether the target popularity value is greater than the target notification threshold. If the threshold value exceeds the target notification threshold, the user is notified of the target group chat message, and the user's response behavior is determined. If the behavior is for the user to adjust the group chat to a do-not-disturb mode, explicit feedback is determined. If the behavior is for the user to ignore, view, or reply to the target group chat message, implicit feedback is determined. Target feedback information is constructed based on the explicit and implicit feedback information, and the target notification threshold is adjusted using the target feedback information and an adaptive adjustment factor to achieve dynamic adjustment of the target notification threshold.
[0037] As can be seen from the above, this application determines the initial popularity based on multi-dimensional interaction indicators, sets various reminder strategies to meet user needs, and can dynamically adjust the target reminder threshold according to user behavior data to achieve intelligent message filtering and reminders. In this way, important messages can be accurately identified, information overload can be avoided, and key information can be ensured not to be missed, significantly improving user experience and communication efficiency.
[0038] Accordingly, see Figure 4 As shown, this application also provides a group chat message intelligent control device, including: The initial popularity value determination module 11 is used to obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message. The target popularity value determination module 12 is used to establish a corresponding content relevance database based on user historical behavior data, use the content relevance database to determine the relevance coefficient corresponding to the target group chat message, and determine the target popularity value based on the initial popularity value and the relevance coefficient. The heat value judgment module 13 is used to determine whether the target heat value is greater than the target reminder threshold; the target reminder threshold is a threshold determined based on the user's historical behavior data; The threshold adjustment module 14 is used to remind the user terminal of the target group chat message if the target popularity value is greater than the target reminder threshold, and to determine the target feedback information based on the user terminal's response to the target group chat message, and to adjust the target reminder threshold using the target feedback information.
[0039] In some specific embodiments, the intelligent group chat message control device may further include: The reminder mode selection unit is used to determine the target reminder mode selected by the user. The message push unit is configured to, if the target reminder mode is the first mode, remind the user terminal of a target number of target messages after the target condition is triggered, and then restore the group chat do-not-disturb mode; the target condition is that there are messages containing the user terminal's nickname in the group chat; the target messages include target group chat messages; The weight determination unit is used to trigger the step of determining the indicator weights corresponding to the target group chat message based on multi-dimensional interactive indicators if the target reminder model is the second mode.
[0040] In some specific implementations, the method for constructing the multi-dimensional interaction indicators may specifically include: The first interaction indicator determination unit is used to determine the interaction scenario in the target group chat message where the user's nickname is present as the first interaction indicator, and to determine the interaction scenario in the target group chat message where the target user replies to the user as the second interaction indicator; the target user is other users in the group chat besides the user. The third interaction indicator determination unit is used to determine the interaction scenario in the target group chat message where the target user references the user's historical group chat message as the third interaction indicator, and to determine the interaction scenario in the target group chat message where the user's target keyword is present as the fourth interaction indicator. A multi-dimensional indicator construction unit is used to determine the group activity level corresponding to the target group chat message as the fifth interaction indicator, and to construct a multi-dimensional interaction indicator based on the first interaction indicator, the second interaction indicator, the third interaction indicator, the fourth interaction indicator and the fifth interaction indicator.
[0041] In some specific embodiments, the initial heat value determination module 11 may specifically include: The weight allocation unit is used to obtain the target group chat message to be reminded and to assign corresponding weights to each interactive indicator in the multi-dimensional interactive indicators based on the importance of the indicators. The initial popularity value determination unit is used to determine the indicator weight corresponding to the target group chat message using the weights, and to determine the initial popularity value corresponding to the target group chat message based on the indicator weights.
[0042] In some specific embodiments, the target heat value determination module 12 may specifically include: The behavior data construction unit is used to construct user historical behavior data based on the user's target keywords, topics of interest, and historical viewed or replied messages. The relevance coefficient determination unit is used to establish a corresponding content relevance database using the user's historical behavior data, and to determine the relevance coefficient corresponding to the target group chat message based on the content relevance database.
[0043] In some specific embodiments, the target heat value determination module 12 may specifically include: The attenuation coefficient determination unit is used to determine the time attenuation coefficient based on the occurrence time of the target group chat message and using a preset time attenuation factor. The target heat value determination unit is used to determine the target heat value based on the initial heat value and in combination with the time decay coefficient and the correlation coefficient.
[0044] In some specific embodiments, the threshold adjustment module 14 may specifically include: The behavior determination unit is used to remind the user terminal of the target group chat message if the target popularity value is greater than the target reminder threshold, and to determine the behavior of the user terminal in response to the target group chat message. An explicit information determination unit is used to determine corresponding explicit feedback information if the behavior is that the user terminal adjusts the group chat do-not-disturb mode. An implicit information determination unit is used to determine the corresponding implicit feedback information if the behavior is that the user ignores, views, or replies to the target group chat message. The threshold adjustment unit is used to construct target feedback information based on the explicit feedback information and the implicit feedback information, and to adjust the target reminder threshold using the target feedback information and the adaptive adjustment factor.
[0045] Furthermore, embodiments of this application also disclose an electronic device, Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the intelligent control method for group chat messages disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be a computer.
[0046] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.
[0047] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.
[0048] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the group chat message intelligent control method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include a computer program capable of performing other specific tasks.
[0049] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned intelligent control method for group chat messages. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.
[0050] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.
[0051] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0052] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.
[0053] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0054] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for intelligent control of group chat messages, characterized in that, include: Obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message. A corresponding content relevance database is established based on user historical behavior data. The relevance coefficient corresponding to the target group chat message is determined using the content relevance database. The target popularity value is determined based on the initial popularity value and the relevance coefficient. Determine whether the target popularity value is greater than the target alert threshold; The target alert threshold is a threshold determined based on the user's historical behavior data; If the target popularity value is greater than the target reminder threshold, the target group chat message is reminded to the user's terminal, and target feedback information is determined based on the user's response to the target group chat message. The target reminder threshold is then adjusted using the target feedback information.
2. The intelligent control method for group chat messages according to claim 1, characterized in that, Before determining the indicator weights corresponding to the target group chat message based on multi-dimensional interaction indicators, the method further includes: Determine the target notification mode selected by the user; If the target notification mode is the first mode, then after the target condition is triggered, the target number of target messages will be notified to the user terminal, and then the group chat do-not-disturb mode will be restored; the target condition is that there are messages containing the user terminal's nickname in the group chat; the target messages include target group chat messages; If the target notification model is the second mode, then the step of determining the indicator weight corresponding to the target group chat message based on multi-dimensional interactive indicators is triggered.
3. The intelligent control method for group chat messages according to claim 2, characterized in that, The method for constructing the multi-dimensional interactive indicators includes: The interaction scenario in the target group chat message containing the user's nickname is determined as the first interaction indicator, and the interaction scenario in the target group chat message in which the target user replies to the user is determined as the second interaction indicator; the target user is other users in the group chat besides the user. The interaction scenario in the target group chat message where the target user references the user's historical group chat message is determined as the third interaction indicator, and the interaction scenario in the target group chat message where the user's target keyword is present is determined as the fourth interaction indicator. The group activity level corresponding to the target group chat message is determined as the fifth interaction indicator. A multi-dimensional interaction indicator is constructed based on the first interaction indicator, the second interaction indicator, the third interaction indicator, the fourth interaction indicator, and the fifth interaction indicator.
4. The intelligent control method for group chat messages according to claim 3, characterized in that, The process of acquiring the target group chat message to be reminded, determining the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and determining the initial popularity value corresponding to the target group chat message using the indicator weight includes: Obtain the target group chat messages to be reminded, and assign corresponding weights to each interaction indicator in the multi-dimensional interaction indicators based on the importance of the indicators; The indicator weights corresponding to the target group chat message are determined using the weights, and the initial popularity value corresponding to the target group chat message is determined based on the indicator weights.
5. The intelligent control method for group chat messages according to claim 3, characterized in that, The step of establishing a corresponding content relevance database based on user historical behavior data, and using the content relevance database to determine the relevance coefficient corresponding to the target group chat message, includes: User historical behavior data is constructed based on the user's target keywords, topics of interest, and historical viewing or replying behavior data from the user's terminal. A corresponding content relevance database is established using the user's historical behavior data, and the relevance coefficient corresponding to the target group chat message is determined based on the content relevance database.
6. The intelligent control method for group chat messages according to any one of claims 1 to 5, characterized in that, The process of determining the target popularity value based on the initial popularity value and in combination with the correlation coefficient includes: The time decay coefficient is determined based on the occurrence time of the target group chat message and using a preset time decay factor. The target heat value is determined based on the initial heat value, combined with the time decay coefficient and the correlation coefficient.
7. The intelligent control method for group chat messages according to claim 1, characterized in that, If the target popularity value is greater than the target reminder threshold, then the user is reminded of the target group chat message, and target feedback information is determined based on the user's response to the target group chat message. The target reminder threshold is then adjusted using the target feedback information, including: If the target popularity value is greater than the target reminder threshold, then the user terminal is reminded of the target group chat message, and the user terminal's response behavior to the target group chat message is determined. If the behavior involves the user adjusting the group chat do-not-disturb mode, then the corresponding explicit feedback information is determined. If the behavior is that the user ignores, views, or replies to the target group chat message, then the corresponding implicit feedback information is determined. Target feedback information is constructed based on the explicit feedback information and the implicit feedback information, and the target reminder threshold is adjusted using the target feedback information and the adaptive adjustment factor.
8. A group chat message intelligent control device, characterized in that, include: The initial popularity value determination module is used to obtain the target group chat message to be reminded, determine the indicator weight corresponding to the target group chat message based on multi-dimensional interaction indicators, and use the indicator weight to determine the initial popularity value corresponding to the target group chat message. The target popularity value determination module is used to establish a corresponding content relevance database based on user historical behavior data, use the content relevance database to determine the relevance coefficient corresponding to the target group chat message, and determine the target popularity value based on the initial popularity value and the relevance coefficient. The heat value judgment module is used to determine whether the target heat value is greater than the target reminder threshold; The target alert threshold is a threshold determined based on the user's historical behavior data; The threshold adjustment module is used to remind the user of the target group chat message if the target popularity value is greater than the target reminder threshold, and to determine the target feedback information based on the user's response to the target group chat message, and to adjust the target reminder threshold using the target feedback information.
9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor is configured to execute the computer program to implement the intelligent control method for group chat messages as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, Used to store a computer program, wherein the computer program, when executed by a processor, implements the intelligent control method for group chat messages as described in any one of claims 1 to 7.