A message delivery method based on chatbot service

Abstract

Embodiments of the present application disclose a message delivery method based on Chatbot service, which is used to solve the problem of low message delivery efficiency caused by unreasonable resource allocation. The method comprises the following steps: obtaining a message delivery task, wherein the message delivery task comprises information of a to-be-delivered message, and the message delivery task is generated by a Chatbot service; obtaining a weighting rule of the Chatbot service, wherein the weighting rule is determined based on historical service parameters of the Chatbot service; determining a queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message; inserting the to-be-delivered message into a matched channel queue based on the message delivery task, and allocating a queue resource to the channel queue, wherein the queue resource is used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue weighting value.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication, and in particular to a message delivery method based on Chatbot service. BACKGROUND

[0002] Chatbot function can be used to provide interactive functions such as message transmission and information search for users on a platform. In order to provide rich and diverse message content, a rich media file message can be delivered to users based on Chatbot function.

[0003] In the scenario of delivering messages based on Chatbot function, in the case of large amount of message delivery, the channel queue for delivering messages may be overloaded, and the high load of the channel may cause message loss. Moreover, the queue resources may be grabbed by multiple channel queues, causing unreasonable resource allocation, low resource utilization, further low message delivery efficiency, and frequent message delivery exceptions.

[0004] How to solve the problem of low message delivery efficiency caused by unreasonable resource allocation is a technical problem to be solved by the present application. SUMMARY

[0005] The purpose of the embodiments of the present application is to provide a message delivery method based on Chatbot service, to solve the problem of low message delivery efficiency caused by unreasonable resource allocation.

[0006] In a first aspect, a message delivery method based on Chatbot service is provided, comprising:

[0007] Obtaining a message delivery task, the message delivery task comprising information of a to-be-delivered message, the message delivery task being generated by a Chatbot service;

[0008] Obtaining a weighting rule of the Chatbot service, the weighting rule being determined based on historical service parameters of the Chatbot service;

[0009] Determining a queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message;

[0010] Inserting the to-be-delivered message into a matched channel queue based on the message delivery task, and allocating a queue resource to the channel queue, the queue resource being used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue weighting value.

[0011] In a second aspect, a message delivery device based on Chatbot service is provided, comprising:

[0012] The first obtaining module obtains a message delivery task, the message delivery task comprising information of a to-be-delivered message, and the message delivery task being generated by a Chatbot service;

[0013] The second obtaining module obtains a weighting rule of the Chatbot service, the weighting rule being determined based on historical service parameters of the Chatbot service;

[0014] The determining module determines a queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message;

[0015] The control module inserts the to-be-delivered message into a matched channel queue based on the message delivery task, and allocates a queue resource to the channel queue, the queue resource being used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue weighting value.

[0016] In a third aspect, an electronic device is provided, which includes a processor, a memory, and a computer program stored in the memory and executable in the processor, and when the computer program is executed by the processor, the steps of the method according to the first aspect are implemented.

[0017] In a fourth aspect, a computer readable storage medium is provided, which stores a computer program, and when the computer program is executed by a processor, the steps of the method according to the first aspect are implemented.

[0018] In a fifth aspect, a computer program product is provided, which includes a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform some or all of the steps of the method according to the first aspect.

[0019] In the embodiment of the present application, first, a message delivery task generated by the Chatbot service is obtained, and the message delivery task includes information of a to-be-delivered message. Then, the empowerment rule of the Chatbot service is obtained, which is determined based on historical service parameters of the Chatbot service. Next, the queue empowerment value of the message delivery task is determined based on the empowerment rule and the information of the to-be-delivered message. Subsequently, the to-be-delivered message is inserted into a matched channel queue based on the message delivery task, and a queue resource is allocated to the channel queue, which is used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue empowerment value. The scheme provided in the embodiment of the present application can determine the queue empowerment value of the Chatbot service for the message delivery task based on the empowerment rule, so as to ensure that the queue empowerment value can objectively and effectively express the weight of the message delivery task. Furthermore, the delivery rate of the channel queue is controlled by means of allocating the queue resource, so as to ensure that the delivery rate corresponds to the queue empowerment value. Thus, the to-be-delivered message is controlled to be delivered at a delivery rate corresponding to the queue empowerment value, and the queue resource is allocated based on the queue empowerment value during the delivery process, so as to ensure rational use of the queue resource and effectively improve the overall efficiency of message delivery. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

[0021] Figure 1 is one of flow diagrams of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0022] Figure 2a is another flow diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0023] Figure 2b is a third flow diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0024] Figure 3 is a fourth flow diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0025] Figure 4a is a fifth flow diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0026] Figure 4b is a four-dimensional user preference determination diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0027] Figure 5aFIG. 6 is a flowchart of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0028] Figure 5b FIG. 7 is a flowchart of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0029] Figure 6 FIG. 8 is a flowchart of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0030] Figure 7 FIG. 9 is a flowchart of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0031] Figure 8 FIG. 10 is a message queue configuration diagram of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0032] Figure 9 FIG. 11 is a flowchart of a message delivery method based on a Chatbot service according to an embodiment of the present application;

[0033] Figure 10 FIG. 12 is a structural diagram of a message delivery device based on a Chatbot service according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of the present application. The figure numbers in the present application are only used to distinguish each step in the scheme, and are not used to limit the execution order of each step, which is subject to the description in the specification.

[0035] In some message delivery application scenarios, 5G (5th Generation Mobile Communication Technology) messages can be delivered to users based on Chatbot functions. Delivering 5G messages often involves transmission through a 5G message MAAP (Messaging as a Platform), and the message delivery rate and channel flow control are both based on the rate limit of the MAAP itself. In the application scenario of message delivery, various platforms lack systematic and intelligent flow control in the upper layer of delivery, and the platform mechanism is often based on the basic division of channel queues, and different channel queues are distinguished according to account types for differentiated delivery, which is difficult to effectively manage and control message pushing.

[0036] For example, in actual application scenarios, the public platform of 5G message issuing is usually difficult to realize message flow control, especially unable to realize message flow control for different scenarios and different channel queues. If only based on the control of 5G message MAAP itself, the division of the basic channel queue is often performed, which may cause message backlog, message loss and other consequences. In addition, it may also cause different resource utilization rates of channels, and some single-channel loads are too large. Due to the above problems in the related art, it is difficult to realize a delivery scheme driven by data, and it is difficult to drive a higher delivery conversion rate.

[0037] In order to solve the problems existing in the related art, the embodiments of the present application provide a message delivery method based on Chatbot service. The method can be applied to the scene of delivering various messages. In the embodiments of the present application, the application scene of delivering 5G messages is taken as an example for description. The scheme provided by the embodiments of the present application can be executed by a 5G message unified platform, or can also be executed by other electronic devices in communication connection with the 5G message unified platform.

[0038] As shown in Figure 1 The scheme includes the following steps:

[0039] S11: Obtain a message delivery task, wherein the message delivery task includes information of a to-be-delivered message, and the message delivery task is generated by a Chatbot service.

[0040] The Chatbot in the embodiments of the present application can specifically refer to a 5G message application number, which can provide a plurality of application functions such as message transmission, information retrieval, interactive dialogue, etc. for 5G users. The Chatbot service can be a service function provided by a 5G message unified platform. The Chatbot service platform (Chatbot Service Platform) can provide a plurality of message service functions for users according to actual application scenarios.

[0041] The message delivery task in this step is generated by the Chatbot service. The Chatbot service can generate corresponding message delivery tasks according to a plurality of information such as message content to be delivered, delivery target user, message type, etc. The message delivery task includes information of a delivered message, which can specifically include specific content of a to-be-delivered message, target user identifier of a to-be-delivered message, and other key information for executing message delivery.

[0042] The message delivery task can be used to implement batch delivery of messages, i.e., to implement the message group sending function. For example, if the actual application requires delivery of 5G messages with the same message content to multiple target users, the message delivery task can include the message content to be delivered and the identification of multiple target users to perform 5G message group sending to multiple users.

[0043] S12: Obtain the empowerment rule of the Chatbot service, which is determined based on historical service parameters of the Chatbot service.

[0044] In this step, based on the message delivery task obtained in the above step, the empowerment rule of the Chatbot service generating the task is obtained. Optionally, the message delivery task can carry the identification of the Chatbot service generating the task, and then the empowerment rule of the Chatbot service is queried according to the identification.

[0045] The empowerment rule of the Chatbot service can be stored in correspondence with the identification of the Chatbot service, and the corresponding empowerment rule can be quickly and accurately called according to the identification of the Chatbot service.

[0046] The empowerment rule of any Chatbot service is determined according to the historical service parameters of the Chatbot service. For example, if the Chatbot service is used to deliver messages to users in one direction, the empowerment rule can be related to the conversion click rate of the delivered messages. If the Chatbot service is used to deliver messages to users and interact with users, the empowerment rule can be related to the amount of user interaction. The empowerment rule can be determined based on the historical data of the Chatbot service, or it can be flexibly set by technicians according to the actual application requirements of the Chatbot service.

[0047] Optionally, the empowerment rule of the Chatbot service can be updated based on a certain period of statistics. For example, every week, the relevant information of the Chatbot service in the past week is counted, and then the latest empowerment rule of the Chatbot is determined by summarizing. Subsequently, the original empowerment rule of the Chatbot can be overwritten with the latest empowerment rule, or the latest empowerment rule can be combined with the original empowerment rule to obtain a combined empowerment rule.

[0048] Specifically, the empowerment rule can include multiple empowerment indicators and the corresponding weight values or the calculation method of the weight variable values of each empowerment indicator. The empowerment rule is used to calculate the empowerment value of the message delivery task queue of the corresponding Chatbot service.

[0049] Optionally, if the functions of multiple Chatbot services in the platform are basically the same, the same weighting rule can be used to calculate the queue weighting value of the message delivery task of the multiple Chatbot services.

[0050] S13: Determine the queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message.

[0051] In this step, the queue weighting value of the message delivery task is determined based on the weighting rule obtained above. Specifically, if the information of the to-be-delivered message contains the weighting indicators specified by the weighting rule, the queue weighting value of the message delivery task can be directly calculated according to the information of the to-be-delivered message. If the information of the to-be-delivered message does not contain the weighting indicators specified by the weighting rule, the data information corresponding to the weighting indicators can be further obtained according to the information of the to-be-delivered message, so as to determine the queue weighting value.

[0052] In the 5G message unified platform, each Chatbot can be regarded as the smallest unit of message sending, and each Chatbot has a configuration of belonging to a different queue. After the Chatbot initiates a task, the present scheme can perform weighting configuration on different Chatbots, and the higher the queue weighting value is, the higher the proportion of the resources that can be occupied and consumed in the subsequent delivery of the corresponding queue.

[0053] S14: Insert the to-be-delivered message into the matched channel queue based on the message delivery task, and allocate queue resources to the channel queue, wherein the queue resources are used to control the message delivery of the channel queue at a delivery rate corresponding to the queue weighting value.

[0054] In this step, the to-be-delivered message is inserted into the matched channel queue, which can be specified in the message delivery task or matched with the Chatbot service that generates the message delivery task.

[0055] For the channel queue into which the to-be-delivered message is inserted, queue resources are allocated to the channel queue in this step to control the message delivery rate of the channel queue. Specifically, the amount of queue resources allocated to the channel queue is positively correlated with the size of the queue weighting value.

[0056] Optionally, on the basis of allocating queue resources according to the queue weighting value, parameter configuration can also be performed on the channel queue to control the message delivery rate of the channel queue by port configuration rate limiting.

[0057] In the scenario of mass sending of 5G messages, further interaction with the user can also be performed according to the feedback operation of the user on the delivered 5G message, so as to meet the personalized interaction needs of the user and improve the conversion efficiency of message delivery.

[0058] In addition, in addition to the group sending scenario, the Chatbot can also provide required service functions for various application scenarios such as real-time triggering and user interaction.

[0059] Optionally, the to-be-delivered message is a 5G message, and the Chatbot service is a service provided by a 5G message unified platform; and the queue resource is used to control the message delivery rate of the channel queue according to the queue weighting value, so as to perform message delivery to users through the 5G message processing platform and the 5G message center.

[0060] The scheme provided by the embodiments of the present application can determine the queue weighting value according to the weighting rule of the Chatbot service of the message delivery task, so as to ensure that the queue weighting value can objectively and effectively express the weight of the message delivery task. Then, the delivery rate of the channel queue is controlled by allocating the queue resource, so as to ensure that the delivery rate corresponds to the queue weighting value. Thus, the to-be-delivered message is delivered at the delivery rate corresponding to the queue weighting value, and the queue resource is allocated based on the queue weighting value during the delivery process, so as to ensure the rational use of the queue resource and effectively improve the overall efficiency of message delivery. The scheme can be used to implement message delivery management on the basic channel queue of the public platform for 5G message distribution, implement full-closed-loop scheduling logic, and be conducive to implementing 5G message composite message pushing and management control based on data calculation and index model driving.

[0061] Based on the scheme provided in the above embodiments, optionally, the information of the to-be-delivered message includes a plurality of to-be-delivered user identifiers. The plurality of to-be-delivered user identifiers in one message delivery task can represent which users the to-be-delivered message needs to be delivered to.

[0062] As shown in the above step S14, that is, before the to-be-delivered message is inserted into the matched channel queue based on the message delivery task and the queue resource is allocated to the channel queue, the following steps are further included: Figure 2a

[0063] S21: Obtain user preference information of a plurality of to-be-delivered users based on the plurality of to-be-delivered user identifiers.

[0064] The user identifier is, for example, an identifier such as identity information or a mobile phone number that can distinguish different users. In this step, the corresponding user preference information obtained based on the user identifier can be user preference information statistically summarized based on user historical preference behaviors, which is used to represent the behavior preferences of the user. The above user identifier and the associated user preference information are all information authorized by the user.

[0065] ​The user preference information can be actively filled in by the user, for example, including favorite tags manually selected by the user. Alternatively, the user preference information can be a keyword tag summarized according to user historical browsing information. Optionally, the user preference information includes at least one of a user portrait, a user historical preference behavior, and user social circle information.

[0066] In actual application, the user preference information can include a large amount of user data, and in this step, the user preference information of the four categories can be obtained in a targeted manner according to the user's activity, search, interaction, and payment conversion. In actual application, the user preference information can also be determined comprehensively in combination with multi-dimensional information such as a user portrait and user social circle information, so as to improve the matching degree of the user preference information and the real preference of the user.

[0067] S22: performing sorting on the plurality of to-be-delivered user identifiers based on the matching degree of the user preference information and the to-be-delivered message.

[0068] In this step, the user preference information of each user is matched with the to-be-delivered message respectively, so as to judge the matching degree of the to-be-delivered message and the user preference, and then the user identifiers are sorted according to the matching degree. The obtained sorting result can represent the preference matching order of the user corresponding to the user identifier to the to-be-delivered message.

[0069] In the step S14, inserting the to-be-delivered message into the matched channel queue based on the message delivery task includes:

[0070] S23: inserting the to-be-delivered message into the matched channel queue based on the sorting result of the plurality of to-be-delivered user identifiers, so as to indicate the channel queue to sequentially deliver the to-be-delivered message to a plurality of to-be-delivered users in the order of the sorting result.

[0071] In this step, the to-be-delivered message is inserted into the channel queue in order based on the above sorting result, so as to perform the message delivery task in order. The user identifiers in the sorting result and the to-be-delivered message are sequentially inserted into the channel queue in the order from high to low according to the matching degree, so that the channel queue delivers the to-be-delivered message to the user with high preference matching degree preferentially.

[0072] Next, the present scheme will be further described through an example. Figure 2b

[0073] Taking a 5G message unified platform as an example, if there are a plurality of message delivery tasks of Chatbot services in the platform, then the queue weighting values of the plurality of message delivery tasks of Chatbot services are calculated first.

[0074] ​Then, the message delivery task with the maximum queue weighting value is selected for priority processing, and other message delivery tasks are sorted according to queue weighting values, so that multiple message delivery tasks are queued and waiting for processing.

[0075] For the message delivery task with the maximum queue weighting value, in the queue issuing stage, the preference value of the user terminal (C-end) user in the four aspects of activity, search, interaction, and payment conversion is matched. The preference value can represent the user portrait of the corresponding user in the preference aspect.

[0076] Based on the user preference, the user portrait with the highest matching degree is determined. The messages are delivered in order from high to low according to the preference matching degree until the ordered delivery to multiple users is completed.

[0077] Through the scheme provided by the embodiments of the present application, the to-be-delivered message can be preferentially delivered to the user with a high preference matching degree according to the user preference information. On the one hand, the ordered delivery can reduce the system load in the application scenario of mass message delivery, improve the success rate of delivering messages to multiple users, and complete the message delivery task in order. On the other hand, preferentially delivering to the user with a high preference matching degree can improve the conversion efficiency of the delivered message. If the conversion rate of the message is lower than expected after being delivered to the user with a high matching degree, the subsequent delivery of the message can be suspended according to the actual demand. Or, the message content is adjusted and then delivered.

[0078] Based on the scheme provided by the above embodiments, optionally, the weighting rule includes a weighting coefficient of multiple index parameters, wherein the index parameters include at least one of a user activity index, a search volume index, an interaction volume index, and a revenue index, and a user complaint index and / or a fault frequency index.

[0079] As shown in the above step S13, the queue weighting value of the message delivery task is determined based on the weighting rule and the information of the to-be-delivered message, which includes: Figure 3

[0080] S31: Based on the weighting rule, the multiple index parameters of the Chatbot service are weighted and summed according to the corresponding weighting coefficients to determine the queue weighting value of the message delivery task.

[0081] In the embodiments of the present application, the weighting rule includes a weighting coefficient of multiple index parameters. The index parameters include at least one positive incentive index parameter and at least one negative management index parameter. Through the weighting rule, the weighting calculation rule can be formulated for the two types of index parameters, respectively, to improve the objectivity and effectiveness of determining the queue weighting value from the positive and negative aspects. ​

[0082] Optionally, the upper limit of the weight can be set for the positive incentive and the negative management respectively by the weighting rule. The weight of each item is refined and split according to the index, and the weight value is calculated according to the index, which can effectively improve the flexibility of determining the queue weighting value.

[0083] For example, the weighting rule in the embodiment of the application is shown in the following table:

[0084]

[0085]

[0086] In terms of weight category, the present scheme is divided into two categories: positive incentive and negative management, which can objectively measure the value contribution of Chatbot to the platform.

[0087] In terms of weight upper limit and sub-index weight proportion, the present scheme can be adjusted according to the importance of each index in different periods, improving flexibility.

[0088] For each index parameter, the above active index can reflect the contribution of Chatbot's active users to the whole platform. The search index can reflect the attention degree of Chatbot in the search layer. The interaction index can reflect the contribution of Chatbot in improving user interaction and platform interactivity. The conversion index can reflect the contribution of Chatbot to the whole platform in income improvement. The complaint index can reflect the pressure degree of Chatbot in user complaints. The fault index can reflect the stability of the experience provided by Chatbot to users.

[0089] Based on the above multiple index parameters, i.e. the corresponding weighting coefficients, the data value calculated by the Chatbot weighting formula is the queue weighting value. The queue weighting value determined by the present scheme can objectively and accurately reflect the importance of Chatbot, and further reflect the importance of the message delivery task of the Chatbot to the whole platform. Then, according to the queue weighting value, the queue resource is allocated to the channel queue, which can reasonably allocate the queue resource to the Chatbot with higher contribution degree, thereby improving the overall message delivery effectiveness of the platform.

[0090] Based on the scheme provided in the above embodiment, the positive incentive index parameter can include multiple index parameters. For example, the positive incentive index parameter can include active, search, interaction, and paid conversion, and the index codes of the four index parameters are p1, p2, p3, and p4 respectively.

[0091] Among them, for example, Figure 4aAs shown, before the above step S22, that is, before the sorting of the plurality of to-be-delivered user identifiers based on the matching degree of the user preference information and the to-be-delivered message, further comprising:

[0092] S41: determining a multi-dimensional preference feature of the to-be-delivered message based on a plurality of index parameters in the positive incentive index parameter.

[0093] In this step, the multi-dimensional preference feature is determined based on the plurality of index parameters. For example, the preference values of the plurality of users corresponding to the to-be-delivered message in the aspects of activity, search, interaction, and payment conversion are matched with the preference values of the message delivery task of the Chatbot in the four aspects. Thus, when delivering, the user corresponding to the high preference value is preferentially delivered.

[0094] Next, a message delivery Chatbot is taken as an example for description.

[0095] Suppose that the message delivery Chatbot initiates a delivery task of 500,000 users at 9:00 am, and the index values of p1 / p2 / p3 / p4 / n1 / n2 of the chatbot are 0.05 / 0.52 / 0.03 / 0.16 / 0.03 / 0.01 respectively calculated by any of the above embodiments of the application. The queue weighting value of the message delivery task of the Chatbot is calculated to be 72 by the assignment formula.

[0096] At this time, it is further determined whether the queue weighting value is the maximum value in all tasks. If it is the maximum value, it is preferentially processed, and if it is not the maximum value, it is queued for processing.

[0097] In the above step S22, the sorting of the plurality of to-be-delivered user identifiers based on the matching degree of the user preference information and the to-be-delivered message comprises:

[0098] S42: determining the matching degree of the multi-dimensional preference feature of the to-be-delivered message and the user preference information of each to-be-delivered user.

[0099] In the case where the queue weighting value is the maximum value, the index values of p1, p2, p3, and p4 are further determined. For example, the p2 (search index) value calculated by the Chatbot in the above step is the highest, and it can be determined that the Chatbot is more popular in search recommendation.

[0100] Further, referring to Figure 4bThe figure is a four-dimensional user preference determination schematic diagram. According to the pre-stored user portrait, the four positive dimensions of activity, search, interaction and payment conversion are valued (for example, the maximum value is 100), the behavior preference of the delivery user is determined, and the user with the highest search preference is screened out in the background. Further, the user identification of the preferred search user is recorded for priority message delivery.

[0101] S43: The plurality of to-be-delivered user identifications are sorted in descending order of the matching degree.

[0102] In this step, the message is delivered to the recorded preferred search user in the message queue, and the delivery order is in descending order of the search preference value.

[0103] In the application scenario of delivering 5G messages, after the task is completed in the delivery of the 5G message unified platform CSP (Chatbot Service Platform), it can be transmitted to the MaaP platform and the 5GMC (5G Message Center) in turn, and the channel delivery is performed according to different message types, so as to realize the ordered delivery of user messages.

[0104] Based on the scheme provided in the above embodiment, optionally, the information of the to-be-delivered message includes a message type, such as Figure 5a As shown in the figure, the method further includes:

[0105] S51: Based on the monitoring mechanism corresponding to the message type of the to-be-delivered message, the index parameter of the channel queue is monitored.

[0106] In actual application, multiple different types of messages may need to be issued in the channel queue. With the issuance of different message types in the channel queue, the corresponding queue can perform real-time monitoring and alarm on related parameters. The monitoring and alarm mechanism can realize visual monitoring, automatic alarm and notification for the message delivery sending process in different fallback form channel queues for 5G messages. In actual application, the performance addition, deletion and modification tools of the channel queue can be used to perform operation adjustment in time as needed, so as to avoid various abnormal situations such as channel message backlog and loss, and comprehensively improve the delivery efficiency of different message types, and ensure the stable and efficient operation of the channel.

[0107] Optionally, the index parameter of the channel queue includes at least one of the undelivered message parameter, the delivered message parameter and the message delivery efficiency parameter.

[0108] Referring to Figure 5bIn the pre-stage before the exception triggering, multi-dimensional alarm rules including alarm level, monitoring object, monitoring time, alarm index, duration, notification mode, etc. can be flexibly set according to actual needs. The background can select corresponding indexes as monitoring objects in the built real-time monitoring data index system, and set threshold values and alarm conditions according to the rules, which are used to build the execution basis for real-time monitoring alarm.

[0109] S52: If the index parameter triggers the alarm condition of the monitoring mechanism, the control instruction corresponding to the alarm condition is issued to the channel queue, and the control instruction is used to control the interface performance parameter of the channel queue and / or the queue speed parameter of the channel queue.

[0110] In the in-stage of the exception triggering, the background periodically scans whether the monitoring index of the monitoring object reaches the threshold value. If the threshold value is not reached, the periodic scanning is continued, and if the threshold value is reached, the alarm is automatically triggered. For the triggered alarm, the platform modifies the channel interface performance value and the queue speed value through the system configuration parameters, and additionally can perform queue addition, queue disablement and other operations, so as to timely remove the performance bottleneck corresponding to the alarm index.

[0111] Next, the present scheme will be further described in combination with an example. The present example provides an optional monitoring index system. The real-time monitoring index system formed by the decomposition and combination of the global / channel / single queue / single Chatbot / fallback mode / message body type and other dimensions according to the channel backlog, channel effect and channel efficiency is shown in the following table:

[0112]

[0113]

[0114] Among them, the undelivered message parameter in the present example includes each parameter in the channel backlog index classification in the table, the delivered message parameter includes each parameter in the channel effect index classification in the table, and the message delivery efficiency parameter includes each parameter in the channel efficiency index classification in the table.

[0115] In the scheme provided by the present example, the monitoring scene of the monitoring mechanism can be divided according to different monitoring objects, monitoring times and monitoring indexes. The monitoring objects include the global, queue and single Chatbot dimensions. The monitoring times include, for example, all day, non-disturbance time and non-disturbance time. The monitoring index can be a single index in the table or the intersection of multiple flexibly selected indexes. According to the actual business needs, different monitoring scenes can be flexibly established.

[0116] The monitoring alarm mechanism can further comprise a do-not-disturb mechanism, wherein the Chatbot is prohibited from performing the group message operation by the CSP during a do-not-disturb time period, and the CSP suspends delivery to the access layer. If the current time reaches the do-not-disturb start time point, and there are still messages in the queue or the message task is still being sent, the CSP can suspend these unfinished tasks and keep them in the queue. Once the do-not-disturb time ends, the tasks kept in the queue are started.

[0117] Based on the above-mentioned embodiments, the scheme can be further improved as follows: Figure 6 As shown in the above step S52, that is, after the control instruction corresponding to the alarm condition is issued to the channel queue, the following steps are further included:

[0118] S61: If the index parameter of the channel queue returns to the alarm condition that does not trigger the monitoring mechanism, the control instruction is removed from the channel queue.

[0119] Referring to the flowchart shown in Figure 5b After the exception is repaired, the monitoring index returns to the normal threshold due to the effect of the related channel queue configuration adjustment in the post-stage. Then, the alarm is removed, and the background can continue to scan the monitoring object and repeat the above process to form a closed loop, thereby fully guaranteeing the stability of the system operation.

[0120] Next, the monitoring alarm mechanism in the present scheme will be further described with reference to an example. Referring to Figure 7 The monitoring alarm mechanism can be flexibly configured to meet the needs of different service functions.

[0121] First, the message channel queue alarm rule is set. In the alarm configuration, the alarm details can be displayed through the alarm list to show the brief key focus content. In the alarm details, the alarm rule identifier, rule name, alarm level (such as ordinary / serious), monitoring object (full platform / single queue / single Chatbot), monitoring time, alarm index (monitoring index / worry time), notification method (email / sms, etc.), notification user, rule description, creator, and creation time can be included. The above-mentioned alarm indexes can be flexibly set by adding, editing, and deleting.

[0122] If the current time is not in the alarm rule monitoring time, the monitoring object is scanned, and it is determined whether the monitoring object is in the alarm state. The monitoring object in the alarm state is contacted for alarm, and the worry time is cleared if it exists.

[0123] If the current time is in the alarm rule monitoring time, the alarm index of the monitoring object is scanned, and it is determined whether the monitoring object is in the alarm state or normal state according to the pre-set alarm rule.

[0124] If in the normal state, further determine whether the monitoring object meets the monitoring index, which is used to determine whether to use the worry time monitoring for the monitoring object. If the monitoring index is met, further determine whether the worry time is met. Wherein, the worry time is met refers to the length of time from the last worry time zero to the current time is greater than the length of the preset worry time. If it is met, it indicates that the time length from the last worry time zero is too long, and the relevant personnel need to be prompted to clear the worry time.

[0125] If in the normal state, and the monitoring object does not meet the monitoring index, then clear the worry time.

[0126] If the monitoring object is in the alarm state, further determine whether the monitoring object meets the monitoring index, if the monitoring index is not met, the alarm is removed, and the alarm duration is not accumulated. If the monitoring index is met, the alarm is removed, and the alarm duration is continuously accumulated.

[0127] Based on the above rules, the alarm monitoring of the monitoring object is performed, and the worry time is used to perform monitoring on the monitoring object that meets the monitoring index through periodic scanning. Through the worry time, the relevant personnel can more comprehensively understand the state of each monitoring object and the monitoring alarm situation.

[0128] Based on the above alarm rules, real-time monitoring can be performed on multiple channel queues in the system platform. The display device can display the number of different levels of alarms, the list of alarms in progress and the list of historical alarms in real time. Among them, the list of alarms in progress can specifically include the time, level, rule identifier, alarm object, monitoring index current value, duration and other information of the current alarm. In addition, after contacting the alarm, the alarm that has been removed can be included in the historical alarm.

[0129] Next, the message queue configuration of the present scheme will be further described in combination with the message queue configuration schematic diagram shown in Figure 8

[0130] In the present application example, the message queue configuration can be realized from multiple aspects such as channel queue management, subscription number queue management, do-not-disturb configuration, message sending configuration, etc., so as to meet the application configuration requirements in multiple aspects in actual application.

[0131] Among them, in the channel queue management, multiple queue operations can be performed through queue configuration, including queue viewing, queue adding, queue modifying, queue deleting, etc. In the channel queue master control, the upstream and downstream platform interface performance can be configured to realize flexible channel queue master control.

[0132] Among them, in the subscription number queue management, the subscription number rate and the related parameters of the queue to which the subscription number belongs can be configured.

[0133] ​In the do-not-disturb configuration, a global do-not-disturb time period can be configured, and a do-not-disturb exemption list can be configured for special needs, and each item in the list is not subject to the do-not-disturb time limit. In the message sending configuration, a group message blacklist can be configured to ensure the overall stability and security of the group message.

[0134] Through the message queue configuration, the three channels of group sending, real-time triggering and interaction can be realized, and multiple composite queues can be configured under the group sending channel to support message delivery of different types and scenes. The scheme can initialize the channel queue according to the upper and lower limit values of the platform concurrency performance and the actual message delivery demand, and support channel queue management (such as channel performance and queue speed details, modification, adding queue, disabling queue), Chatbot queue management (Chatbot queue details, switching, Chatbot rate modification), do-not-disturb configuration, termination and other functions.

[0135] The scheme is based on a 5G message delivery platform with multiple composite message types, applies index models to queue weighting and message pushing, and has channel monitoring and early warning management control, which can assist in adjusting message delivery and allocating channel queues to meet the multi-faceted needs of actual applications. In different sending scenarios, the 5G message multiple types can realize message flow optimization in Chatbot server to user end and user end to user end scenarios. The scheme optimizes the use and delivery efficiency of the queue by combining user data and Chatbot weighting, and further optimizes the message delivery process through the queue monitoring and alarm adjustment mechanism to ensure message delivery stability. In addition, the scheme is universal and can be widely used in the optimization processing of various message flows in the communication field.

[0136] Next, the scheme will be described in combination with Figure 9 The flow of the scheme will be further described.

[0137] The scheme can be applied to a 5G message delivery platform that supports editing and delivering 5G messages, falling back to text messages, video messages, reading messages and other message types by Chatbot services. Among them, the Chatbot service initiates a message delivery task on the 5G message delivery platform, and the delivery task contains main information such as sending user number, sending content, and message type.

[0138] In the preprocessing module of the 5G message delivery platform, the user data in the delivery task is analyzed and Chatbot weighting is calculated, and a queue weighting value of the Chatbot delivery task is obtained after the module is processed.

[0139] 5G message delivery platform queue delivery module, according to the queue delivery weight in the above steps, the corresponding delivery rate is obtained in the corresponding channel to deliver the message, from top to bottom through the CSP of 5G message unified platform, MaaP platform, 5GMC.

[0140] In addition, the queue monitoring and alarm module runs synchronously, and monitors each channel queue based on the monitoring and alarm configuration of different message types. When the alarm value is reached, the channel adjustment mechanism is triggered to allocate channel resources to the queue resources in the queue delivery module, and to avoid delivery overload or slow delivery rate through rate adjustment. Finally, according to different message types, the message delivery is sent to the Chatbot delivery user group in different user mobile terminals.

[0141] In the scheme provided by the embodiments of the application, the pre-processing module can configure the weights of different Chatbots, and adjust the consumption proportion of the Chatbots in the delivery queue according to the weight values. The Chatbot weight is flexibly matched with the user portrait and behavior preference of the target user to be delivered in the task, so as to realize the delivery matching from B end to C end and improve the message delivery conversion rate. In addition, with the delivery of different message types in the channel queue, the scheme applies the corresponding queue monitoring and alarm mechanism, and can perform visual monitoring, automatic alarm and notification, channel queue performance addition, deletion and modification tools for timely operation and adjustment during the message delivery process, so as to relieve various abnormal situations such as channel message backlog and loss. In terms of monitoring and alarm, the monitoring scene can be divided according to different monitoring objects, monitoring time and monitoring indexes, and hierarchical automatic alarm is performed.

[0142] The scheme can maximize the use of message sending resources. In terms of the order of the message delivery queue, the message is delivered in order according to the weight mechanism and the user portrait and behavior preference, so that the message queue can more flexibly meet the needs of different business scenarios, and the model can also be flexibly adjusted and expanded according to business needs. In addition, the scheme is driven by an index model and is suitable for 5G message composite message pushing, and can realize management and control from the upstream to the downstream of message pushing.

[0143] In order to solve the problems in the related art, such as Figure 10 As shown in FIG. 1, the embodiments of the application also provide a message delivery device 100 based on Chatbot service, which comprises:

[0144] The first acquisition module 101 acquires a message delivery task, wherein the message delivery task comprises information of a message to be delivered, and the message delivery task is generated by a Chatbot service;

[0145] The second obtaining module 102 obtains the empowerment rule of the Chatbot service, wherein the empowerment rule is determined based on historical service parameters of the Chatbot service.

[0146] The determining module 103 determines a queue empowerment value of the message delivery task based on the empowerment rule and information of the message to be delivered.

[0147] The control module 104 inserts the message to be delivered into a matched channel queue based on the message delivery task, and allocates a queue resource to the channel queue, wherein the queue resource is used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue empowerment value.

[0148] The device provided in the embodiments of the present application can determine a queue empowerment value for the empowerment rule of the Chatbot service of the message delivery task, and ensure that the queue empowerment value can objectively and effectively express the weight of the message delivery task. Furthermore, the delivery rate of the channel queue is controlled by allocating a queue resource, and the delivery rate is ensured to correspond to the queue empowerment value. Thus, the message to be delivered is controlled to be delivered at a delivery rate corresponding to the queue empowerment value, and the queue resource is allocated based on the queue empowerment value during the delivery process, so as to ensure the rational use of the queue resource and effectively improve the overall efficiency of message delivery.

[0149] The modules in the device provided in the embodiments of the present application can also implement the method steps provided in the method embodiments. Alternatively, the device provided in the embodiments of the present application can also include other modules in addition to the above modules, to implement the method steps provided in the method embodiments. The device provided in the embodiments of the present application can achieve the technical effects achieved by the method embodiments.

[0150] Preferably, the embodiments of the present application further provide an electronic device, which includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the processes of the message delivery method embodiments based on the Chatbot service are implemented, and the same technical effects are achieved. To avoid repetition, details are not described here.

[0151] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processes of the message delivery method embodiments based on the Chatbot service are implemented, and the same technical effects are achieved. To avoid repetition, details are not described here. The computer readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0152] The embodiments of the present application also provide a computer program product. The computer program product includes a non-transitory computer readable storage medium storing a computer program. The computer program is operable to cause a computer to execute part or all of the steps of the message delivery method based on the Chatbot service and achieve the same technical effects. To avoid repetition, details are not described herein.

[0153] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. In addition, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code.

[0154] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions, which are executed via the processor of the computer or other programmable data processing apparatus, generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure One The functions specified in a flow or multiple flows and / or blocks Figure One The functions specified in a flow or multiple flows and / or blocks

[0155] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction means, which implement the functions specified in the flowcharts and / or block diagrams. Figure One The functions specified in a flow or multiple flows and / or blocks Figure One The functions specified in a flow or multiple flows and / or blocks

[0156] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the functions specified in the flowcharts and / or block diagrams. Figure One The functions specified in a flow or multiple flows and / or blocks Figure One The functions specified in a flow or multiple flows and / or blocks

[0157] In one typical arrangement, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory. The memory can include non-persistent memory in the form of random access memory (RAM) and / or non-volatile memory such as read only memory (ROM) or flash memory, among others, in a computer readable medium. Memory is an example of computer readable media. Computer readable media includes permanent and non-permanent, movable and non-movable media that can implement information storage by any method or technology. Information can be computer readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital versatile disks (DVDs) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0158] It should also be noted that the terms "comprising," "including," and any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element. The term "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any implementation of the technology described herein that is not expressly described as "exemplary" or "preferred" is also to be considered exemplary and preferred. Those skilled in the art will readily recognize many modifications and variations of this application, which are intended to be included herein, as falling within the scope of the application. Therefore, it is intended that this application be limited only by the scope of the appended claims, all legal equivalents, and the full scope of equivalents, which are set out in the Description.

Claims

1. A message delivery method based on a Chatbot service, characterized by, The method comprises: obtaining a message delivery task, the message delivery task comprising information of a to-be-delivered message, the message delivery task being generated by a Chatbot service; obtaining a weighting rule of the Chatbot service, the weighting rule being determined based on historical service parameters of the Chatbot service; determining a queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message; inserting the to-be-delivered message into a matched channel queue based on the message delivery task, and assigning a queue resource to the channel queue, the queue resource being used to control the channel queue to perform message delivery at a delivery rate corresponding to the queue weighting value; wherein the weighting rule comprises weighted coefficients of multiple index parameters; wherein determining the queue weighting value of the message delivery task based on the weighting rule and the information of the to-be-delivered message comprises: performing weighted summation on multiple index parameters of the Chatbot service according to corresponding weighted coefficients based on the weighting rule, to determine the queue weighting value of the message delivery task.

2. The method of claim 1, wherein, The information of the to-be-delivered message comprises multiple to-be-delivered user identifiers; wherein, before inserting the to-be-delivered message into a matched channel queue based on the message delivery task, and assigning a queue resource to the channel queue, the method further comprises: obtaining user preference information of multiple to-be-delivered users based on the multiple to-be-delivered user identifiers; performing sorting on the multiple to-be-delivered user identifiers based on matching degrees of user preference information and the to-be-delivered message; wherein, inserting the to-be-delivered message into a matched channel queue based on the message delivery task comprises: inserting the to-be-delivered message into a matched channel queue based on the sorting result of the multiple to-be-delivered user identifiers, to indicate the channel queue to deliver the to-be-delivered message to multiple to-be-delivered users in turn according to the sorting result.

3. The method of claim 1, wherein, The index parameters comprise positive incentive index parameters and negative management index parameters of the Chatbot service, the positive incentive index parameters comprising at least one of user activity index, search volume index, interaction volume index, and revenue index, and the negative management index parameters comprising user complaint index and / or fault frequency index.

4. The method of claim 3, wherein, The positive incentive index parameters comprise multiple index parameters; wherein, before performing sorting on the multiple to-be-delivered user identifiers based on matching degrees of user preference information and the to-be-delivered message, the method further comprises: determining multi-dimensional preference features of the to-be-delivered message based on the multiple index parameters in the positive incentive index parameters; wherein, performing sorting on the multiple to-be-delivered user identifiers based on matching degrees of user preference information and the to-be-delivered message comprises: determining matching degrees of multi-dimensional preference features of the to-be-delivered message and user preference information of each to-be-delivered user; performing sorting on the multiple to-be-delivered user identifiers in order from high to low according to the matching degrees.

5. The method of claim 4, wherein, The user preference information comprises at least one of user portrait, user historical preference behavior, and social circle information of the user.

6. The method of claim 1, wherein, The to-be-delivered message is a 5G message, and the Chatbot service is a service provided by a 5G message unified platform. The queue resource is used to control the channel queue to perform message delivery to users through a 5G message processing platform and a 5G message center according to a delivery rate corresponding to the queue authorization value.

7. The method according to any one of claims 1 to 6, wherein The information of the to-be-delivered message includes a message type, and the method further includes: monitoring an index parameter of the channel queue based on a monitoring mechanism corresponding to the message type of the to-be-delivered message; if the index parameter triggers an alarm condition of the monitoring mechanism, issuing a control instruction corresponding to the alarm condition to the channel queue, the control instruction being used to control an interface performance parameter of the channel queue and / or a queue speed parameter of the channel queue.

8. The method of claim 7, wherein, The index parameter of the channel queue includes at least one of an undelivered message parameter, a delivered message parameter, and a message delivery efficiency parameter.

9. The method of claim 7, wherein, After issuing the control instruction corresponding to the alarm condition to the channel queue, the method further includes: if the index parameter of the channel queue returns to a state in which the alarm condition of the monitoring mechanism is not triggered, canceling the control instruction for the channel queue.

10. An electronic device, comprising: including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being executed by the processor to implement the steps of the method according to any one of claims 1 to 9.

11. A computer readable storage medium, characterized in that, The computer program is stored on the computer readable storage medium and is executable by the processor to implement the steps of the method according to any one of claims 1 to 9.

12. A computer program product, characterised in that, The computer program product includes a non-transitory computer readable storage medium storing a computer program, the computer program being operable to cause a computer to perform some or all of the steps of the method according to any one of claims 1 to 9.

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