Promotion activity generation method, computing device and computer storage medium

Abstract

The present invention discloses a promotion activity generation method, a computing device and a computer storage medium. The method includes: calculating a first user viscosity index value within a currently corresponding first time window; matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, identifying a target second user viscosity index value that matches the first user viscosity index value; identifying a target second time window according to the target second user viscosity index value; and generating a currently corresponding promotion activity based on historical promotion activity information corresponding to the target second time window. This solution can realize the automatic generation of promotion activities, reduce the generation cost of promotion activities, and improve the generation efficiency of promotion activities. In addition, the promotion activities generated by this solution have a high degree of matching with the current actual situation, which is conducive to improving the user retention rate and user activity of the application platform, improving the user experience and avoiding the waste of promotion resources.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a promotion activity generation method, a computing device and a computer storage medium. Background Art

[0002] In order to improve the user retention rate of the application platform and attract users, many application platforms will provide users with corresponding promotion activities. At present, the existing technology usually uses manual configuration to generate promotion activities.

[0003] However, during the implementation process, the inventors found that the prior art has the following defects: the method of manually generating promotional activities is very inefficient and costly, and is not suitable for large-scale application and implementation; and the method of manually generating promotional activities requires the configuration of the activity content in advance, and cannot be adjusted in time according to changes in actual conditions, and cannot achieve the optimal configuration. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a promotion activity generation method, a computing device and a computer storage medium that overcome the above problems or at least partially solve the above problems.

[0005] According to one aspect of the present invention, a promotion activity generation method is provided, comprising:

[0006] Calculate the first user viscosity index value within the current corresponding first time window;

[0007] Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value;

[0008] identifying a target second time window according to the target second user viscosity index value;

[0009] Based on the historical promotion activity information corresponding to the target second time window, a current corresponding promotion activity is generated.

[0010] According to another aspect of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus;

[0011] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the following operations:

[0012] Calculate the first user viscosity index value within the current corresponding first time window;

[0013] Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value;

[0014] identifying a target second time window according to the target second user viscosity index value;

[0015] Based on the historical promotion activity information corresponding to the target second time window, a current corresponding promotion activity is generated.

[0016] According to another aspect of the present invention, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables a processor to execute operations corresponding to the above-mentioned promotion activity generation method.

[0017] According to the promotion activity generation method, computing device and computer storage medium provided by the present invention. First, calculate the first user viscosity index value in the current corresponding first time window; further match the first user viscosity index value with the second user viscosity index value in any second time window stored in the historical database, and identify the target second user viscosity index value that matches the first user viscosity index value; identify the target second time window according to the target second user viscosity index value; finally, based on the historical promotion activity information corresponding to the target second time window, generate the current corresponding promotion activity. This solution can realize the automatic generation of promotion activities, reduce the generation cost of promotion activities, and improve the generation efficiency of promotion activities. In addition, the promotion activities generated by this solution have a high degree of match with the current actual situation, which is conducive to improving the user retention rate and user activity of the application platform, improving user experience and avoiding waste of promotion resources.

[0018] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0020] Figure 1 A schematic diagram of a process of generating a promotion activity according to Embodiment 1 of the present invention is shown;

[0021] Figure 2A schematic diagram showing a flow chart of a promotion activity generation method provided according to Embodiment 2 of the present invention;

[0022] Figure 3 A schematic diagram of the structure of a computing device provided according to a fourth embodiment of the present invention is shown. DETAILED DESCRIPTION

[0023] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0024] Embodiment 1

[0025] Figure 1 The flowchart of a promotion activity generation method provided according to the first embodiment of the present invention is shown. The promotion activity generation method provided in this embodiment can be applied to a variety of application platforms, such as video platforms and e-book platforms.

[0026] like Figure 1 As shown, the method includes:

[0027] Step S110: Calculate the first user viscosity index value within the current corresponding first time window.

[0028] In order to automatically generate promotional activities that match the current actual situation, this embodiment first obtains the current corresponding user viscosity index value, where the user viscosity index value is a specific value of the user viscosity index. The user viscosity index can reflect the degree of user dependence on the application platform and can reflect the user's satisfaction with the application platform. Among them, the user viscosity index may include retention rate and / or activity, etc.

[0029] In the process of obtaining the current corresponding user viscosity index value, the first user viscosity index value corresponding to the current is calculated, and the first user viscosity index value is the user viscosity index value within the first time window. Among them, the interval between the end point of the first time window and the current time is less than the preset time interval. In other words, the user viscosity index value within the most recent period of time from the current time is obtained in this embodiment.

[0030] Optionally, in the process of calculating the current corresponding first user viscosity index value, user records of the application platform within the first time window may be extracted from the data cache or the recent database, and the user records include at least one of the following records: application startup records, application registration records, and recharge records, etc. And further based on the user records of the application platform within the first time window, the first user viscosity index value within the first time window is calculated.

[0031] Step S120: Match the first user viscosity index value with a second user viscosity index value within any second time window stored in the history database, and identify a target second user viscosity index value that matches the first user viscosity index value.

[0032] This embodiment pre-stores the second user viscosity index values ​​in multiple second time windows in the historical database. Each second time window has a corresponding historical promotion activity, which is an already implemented promotion activity. In addition, the end point of the second time window is earlier than the end point of the first time window.

[0033] Optionally, in order to facilitate the matching of subsequent data, the length of the first time window in this embodiment is the same as the length of the second time window. For example, if the current time is December 1, the first time window can be November 24 to November 30, and the second time window can be October 24 to October 30 and September 24 to September 30. That is, the length of the first time window and the second time window are both one week. In the actual implementation process, those skilled in the art can set the length of the second time window and the second time window according to actual business needs, and this embodiment does not limit this.

[0034] After obtaining the first user viscosity index value in step S110, the first user viscosity index value is matched with any second user viscosity index value. If a second user viscosity index value matches the first user viscosity index value, the second user viscosity index value is determined to be the target second user viscosity index value.

[0035] Step S130: Identify a target second time window according to the target second user stickiness index value.

[0036] If the target second user viscosity index value matches the first user viscosity index value, it indicates that the user viscosity characteristics in the second time window corresponding to the target user viscosity index value are highly similar to the user viscosity characteristics in the first time window, and thus the second time window corresponding to the target second user viscosity index value is determined as the target second time window.

[0037] Step S140: Generate the current corresponding promotion activity based on the historical promotion activity information corresponding to the target second time window.

[0038] Since the user viscosity characteristics in the target second time window are highly similar to the user viscosity characteristics in the first time window, the historical promotion activity information corresponding to the target second time window can be obtained, and based on the historical promotion activity information corresponding to the target second time window, the current corresponding promotion activity is automatically generated.

[0039] It can be seen that this embodiment first calculates the first user viscosity index value within the first time window to obtain the current user viscosity characteristics; then matches the first user viscosity index value with the second user viscosity index value within any second time window stored in the historical database to identify the target second user viscosity index value that matches the first user viscosity index value, and then determines the target second time window that matches the current user viscosity characteristics, and finally generates the current corresponding promotion activity according to the historical promotion activity information corresponding to the target second time window. By adopting this scheme, the automatic generation of promotion activities can be realized, thereby reducing the generation cost of promotion activities and improving the generation efficiency of promotion activities. In addition, this scheme generates the current promotion activity based on the promotion activity information in the historical period with high similarity to the current user viscosity characteristics, so that the generated promotion activity has a high degree of matching with the current actual situation, which is conducive to improving the user retention rate and user activity of the application platform; further, because the promotion activity has a high degree of matching with the current actual situation, it further avoids the waste of promotion resources and is conducive to improving the user experience.

[0040] Embodiment 2

[0041] Figure 2 The flowchart of a promotion activity generation method provided by the second embodiment of the present invention is shown. In order to better understand the present invention, this embodiment takes the application of the e-book platform as an example to specifically illustrate the implementation process of the promotion activity generation method provided by the embodiment of the present invention.

[0042] like Figure 2 As shown, the method includes:

[0043] Step S210: Calculate the first user viscosity index value within the current corresponding first time window.

[0044] In a specific implementation process, user records of the e-book platform within a first time window are extracted, and the user records include: user application startup records, registration records, reading records, and / or comment records, etc. Then, the index value of the current user viscosity index is calculated according to the extracted user records within the first time window, that is, the first user viscosity index value is calculated.

[0045] In this embodiment, the user viscosity index may include at least one of the following indicators: retention rate, activity, reading rate, and comment rate, etc. If there are multiple user viscosity indicators, the first user viscosity index value includes the indicator values ​​corresponding to the multiple user viscosity indicators. Among them, the retention rate can be the ratio of the number of users who still start the application in the Nth statistical unit among the new users of the application in the first statistical unit to the number of new users in the first statistical unit; or, the retention rate can also be the ratio of the number of users who still start the application in the Nth statistical unit among the startup users of the application in the first statistical unit to the number of startup users in the first statistical unit; the activity is the ratio of the number of startup users of the application to the number of registered users of the application; the reading rate is the ratio of the number of reading users of the application to the number of startup users of the application; the comment rate is the ratio of the number of comment users of the application to the number of startup users of the application.

[0046] User stickiness can be reflected by retention rate, activity, reading rate and / or comment rate. In addition, user records can also include payment records and recharge records. The user stickiness index can also include reading payment rate and / or recharge rate. Among them, the reading payment rate is the ratio of the number of paying users to the number of reading users; the recharge rate is the ratio of the number of recharge users to the number of starting users.

[0047] Step S220: Match the first user viscosity index value with a second user viscosity index value within any second time window stored in the history database, and identify a target second user viscosity index value that matches the first user viscosity index value.

[0048] The user viscosity index may be single or multiple. In the matching process, the first user viscosity index value and the second user viscosity index value belonging to the same user viscosity index are matched to identify the target second user viscosity index value belonging to the user viscosity index. For example, the first retention rate index value belonging to the retention rate index is matched with the second retention rate index value of the second time window, and the first activity index value belonging to the activity index is matched with the second activity index value of the second time window.

[0049] Specifically, in the process of matching the first user viscosity index value with the corresponding second user viscosity index value, one or more combinations of the following matching methods may be adopted.

[0050] Matching method 1: Match based on the similarity of the indicator value range.

[0051] Specifically, the index value range corresponding to the first user viscosity index value is matched with the index value range corresponding to the second user viscosity index value; if the index value range corresponding to the first user viscosity index value and the index value range corresponding to the second user viscosity index value belong to the same preset index value range, the second user viscosity index value is determined to be the target second user viscosity index value. Wherein, one user viscosity index corresponds to one preset index value range, and the preset index value ranges corresponding to different user viscosity index values ​​may be the same or different.

[0052] For example, user stickiness indicators include activity indicators and recharge rate indicators. If the preset indicator value range corresponding to the activity indicator is 60%-100%, and the preset indicator value range corresponding to the recharge rate indicator is 0-20%, the first activity indicator value in the first time window is {63%, 65%, 70%}, and the first recharge rate indicator value is {16%, 13%, 14%}; the second activity indicator value in the second time window A is {69%, 62%, 70%}, and the second recharge rate indicator value is {23%, 13%, 14%}. It can be seen from this that the indicator value ranges corresponding to the first activity index value and the second activity index value are both 60%-100%, so it is determined that the second activity index value in the second time window A is the target second user stickiness index value belonging to the activity index; and the indicator value range corresponding to the first recharge rate index value is 0-20%, and the second recharge rate index value in the second time window A does not belong to 0-20%, so it is determined that the second recharge rate index value in the second time window A is not the target second user stickiness index value belonging to the recharge rate indicator.

[0053] Matching method 2: Match based on the similarity of indicator value change trends.

[0054] Specifically, the changing trend of the first user viscosity index value is matched with the changing trend of the second user viscosity index value; if the similarity between the changing trend of the first user viscosity index value and the changing trend of the second user viscosity index value is greater than a preset similarity threshold, the second user viscosity index value is determined to be the target second user viscosity index value.

[0055] For example, for the retention rate indicator, the change curve corresponding to the first retention rate indicator value can be matched with the change curve corresponding to the second retention rate indicator value in the second time window B. If the similarity between the two curves is greater than 80%, the second retention rate indicator value in the second time window B is determined to be the target second user viscosity indicator value belonging to the retention rate indicator.

[0056] Step S230: Identify a target second time window according to the target second user viscosity index value.

[0057] If there is one user viscosity index, the second time window corresponding to the target second user viscosity index value is determined as the target second time window. For example, if the user viscosity index is the retention rate, the second retention rate index value in the second time window B and the second retention rate index value in the second time window C are determined as the target second user viscosity index value through step S220, and the second time window B and the second time window C are used as the target second time window.

[0058] If there are multiple user viscosity indicators, then when the second time window includes multiple target second user viscosity indicator values, and each target second user viscosity indicator value included belongs to each user viscosity indicator respectively, the second time window is determined to be the target second time window. For example, if the user viscosity indicator is an activity indicator and a recharge rate indicator, it is determined through step S220 that only the second activity indicator value in the second time window A is the target second user viscosity indicator value belonging to the activity indicator, then it is determined that the second time window A is not the target second time window; if it is determined through step S220 that the second activity indicator value in the second time window D is the target second user viscosity indicator value belonging to the activity indicator, and the second recharge rate indicator value in the second time window D is the target second user viscosity indicator value belonging to the recharge rate indicator, then the second time window D is determined to be the target second time window.

[0059] Step S240: Determine whether there are multiple target second time windows; if so, execute step S250; if not, execute step S280.

[0060] Step S250: Calculate a historical promotion activity reference value corresponding to any target second time window.

[0061] If there are multiple target second time windows, the historical promotion activity reference value corresponding to any target second time window is calculated respectively.

[0062] Specifically, the historical promotion activity reference value corresponding to any target second time window can be calculated based on the interval between the current time and / or the historical promotion activity effect evaluation value corresponding to the target second time window. The interval between the second time window and the current time can be the interval between the starting point or the end point of the second time window and the current time; and the historical promotion activity effect evaluation value corresponding to the second time window can be determined based on the input-output ratio of the promotion activity, the customer acquisition rate, etc.

[0063] Among them, the higher the historical promotion activity effect evaluation value corresponding to the target second time window, the better the promotion effect obtained by the historical promotion activity in the scenario of the user viscosity characteristics, the shorter the interval between the target second time window and the current time, and the more the promotion activity in the second target time window conforms to the current situation. Therefore, in this embodiment, the historical promotion activity reference value corresponding to the target second time window is positively correlated with the historical promotion activity effect evaluation value corresponding to the target second time window, and / or, the historical promotion activity reference value corresponding to the target second time window is negatively correlated with the interval between the target second time window and the current time.

[0064] Step S260: Filtering out a revised target second time window from a plurality of target second time windows according to the historical promotion activity reference value corresponding to the target second time window.

[0065] The reference value of the historical promotion activity corresponding to the target second time window can reflect the reference value of the historical promotion activity corresponding to the target second time window for the current scenario. The higher the reference value of the historical promotion activity corresponding to the target second time window, the higher the reference value.

[0066] Thus, the modified target second time window can be selected from multiple target second time windows according to the historical promotion activity reference value corresponding to the target second time window. For example, the target second time window with the highest corresponding historical promotion activity reference value can be used as the modified target second time window, or the target second time window with a historical promotion activity reference value greater than a preset threshold can be used as the modified target second time window.

[0067] Step S270: Generate the current corresponding promotion activity according to the historical promotion activity information corresponding to the modified target second time window.

[0068] In the actual implementation process, the historical promotion activities corresponding to the second time window of the revised target can be adaptively adjusted to generate the current corresponding promotion activities. For example, the activity time of the historical promotion activities can be adjusted to generate the current corresponding promotion activities.

[0069] By implementing the above steps S250-S270, promotion activities can be generated from two dimensions: user stickiness characteristics and activity values ​​of historical promotion activities, thereby further improving the matching degree between the promotion activities and the current actual situation.

[0070] In another optional implementation, steps S250 to S270 may be replaced by: generating a current corresponding promotion activity based on the historical promotion activity information corresponding to the multiple target second time windows. In this implementation, multiple historical promotion activity information may be integrated to generate the current corresponding promotion activity. For example, the historical promotion activities corresponding to the multiple target second time windows are historical promotion activities X and Y, respectively, then the current promotion activity may be sending historical promotion activity X to user group Q and sending historical promotion activity Y to user group W.

[0071] Step S280: Generate the current corresponding promotion activity according to the historical promotion activity information corresponding to the single target second time window.

[0072] In addition, after the current corresponding promotion activity is generated, after a preset time period, the user stickiness index value within the preset time period can be calculated, and / or the historical promotion activity effect evaluation value of the generated promotion activity can be calculated, and the calculation results can be stored in the historical database. In this way, the historical database is continuously expanded to provide a basis for the generation of subsequent promotion activities.

[0073] It can be seen that the present embodiment can match the first user viscosity index value with the second user viscosity index value based on the similarity of the index value range and / or based on the similarity of the index value change trend, so as to accurately identify the target second user viscosity index value, and then improve the recognition accuracy of the target second time window; furthermore, when the present embodiment determines that there are multiple target second time windows, it calculates the historical promotion activity reference value corresponding to the target second time window, and then obtains the corrected target second time window according to the historical promotion activity reference value, and finally automatically generates the current corresponding promotion activity according to the corrected historical promotion activity information corresponding to the target second time window, so as to generate the current promotion activity from two dimensions of user viscosity characteristics and activity value of historical promotion activities, so as to further improve the matching degree between the current promotion activity and the current actual situation, which is beneficial to improve the user retention rate and user activity of the application platform, avoid the waste of promotion resources and improve the user experience, and further improve the generation efficiency of promotion activities and reduce the generation cost of promotion activities.

[0074] Embodiment 3

[0075] According to a third embodiment of the present invention, a non-volatile computer storage medium is provided, wherein the computer storage medium stores at least one executable instruction, and the computer executable instruction can execute the promotion activity generation method in any of the above method embodiments.

[0076] The executable instructions may be specifically used to cause the processor to perform the following operations:

[0077] Calculate the first user viscosity index value within the current corresponding first time window;

[0078] Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value;

[0079] identifying a target second time window according to the target second user viscosity index value;

[0080] Based on the historical promotion activity information corresponding to the target second time window, a current corresponding promotion activity is generated.

[0081] In an optional implementation, the user stickiness index includes at least one of the following indicators:

[0082] Retention rate, activity, reading rate, and comment rate.

[0083] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0084] If there are multiple user viscosity indicators, the first user viscosity indicator value and the second user viscosity indicator value belonging to the same user viscosity indicator are matched to identify a target second user viscosity indicator value belonging to the user viscosity indicator.

[0085] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0086] If the second time window includes multiple target second user viscosity index values, and each target second user viscosity index value included belongs to each user viscosity index respectively, then the second time window is determined to be the target second time window.

[0087] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0088] Matching the index value range corresponding to the first user viscosity index value with the index value range corresponding to the second user viscosity index value;

[0089] If the index value range corresponding to the first user viscosity index value and the index value range corresponding to the second user viscosity index value belong to the same preset index value range, the second user viscosity index value is determined to be the target second user viscosity index value.

[0090] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0091] Matching a change trend of the first user viscosity index value with a change trend of the second user viscosity index value;

[0092] If the similarity between the change trend of the first user viscosity index value and the change trend of the second user viscosity index value is greater than a preset similarity threshold, the second user viscosity index value is determined to be the target second user viscosity index value.

[0093] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0094] Based on the historical promotion activity information corresponding to the multiple target second time windows, a current corresponding promotion activity is generated.

[0095] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0096] Calculate the historical promotion activity reference value corresponding to the second time window of any target;

[0097] According to the historical promotion activity reference value corresponding to the target second time window, a revised target second time window is selected from multiple target second time windows;

[0098] According to the historical promotion activity information corresponding to the second time window of the revised target, a current corresponding promotion activity is generated.

[0099] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0100] According to the interval between any target second time window and the current time and / or the historical promotion activity effect evaluation value, the historical promotion activity reference value corresponding to the target second time window is calculated.

[0101] In an optional embodiment, the historical promotion activity reference value corresponding to the target second time window is positively correlated with the historical promotion activity effect evaluation value corresponding to the target second time window, and / or the historical promotion activity reference value corresponding to the target second time window is negatively correlated with the interval between the target second time window and the current time.

[0102] In an optional implementation, the executable instructions may be specifically used to cause the processor to perform the following operations:

[0103] The target second time window with the highest reference value of historical promotion activities is used as the revised target second time window.

[0104] In an optional implementation, the interval between the end point of the first time window and the current time is less than a preset time interval.

[0105] In an optional implementation, the length of the first time window is the same as the length of the second time window.

[0106] It can be seen that this embodiment generates the current promotion activity based on the promotion activity information in the historical period with high similarity to the current user viscosity characteristics, so that the generated promotion activity has a high degree of match with the current actual situation, which is beneficial to improving the user retention rate and user activity of the application platform; furthermore, since the promotion activity has a high degree of match with the current actual situation, it further avoids the waste of promotion resources and is beneficial to the improvement of user experience.

[0107] Embodiment 4

[0108] Figure 3 A schematic diagram of the structure of a computing device provided according to Embodiment 4 of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0109] like Figure 3 As shown, the computing device may include: a processor (processor) 302 , a communication interface (Communications Interface) 304 , a memory (memory) 306 , and a communication bus 308 .

[0110] The processor 302, the communication interface 304, and the memory 306 communicate with each other via the communication bus 308. The communication interface 304 is used to communicate with other devices such as client or other server network elements. The processor 302 is used to execute the program 310, which can specifically execute the relevant steps in the above method embodiment.

[0111] Specifically, the program 310 may include program codes, which include computer operation instructions.

[0112] The processor 302 may be a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. The one or more processors included in the computing device may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0113] The memory 306 is used to store the program 310. The memory 306 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0114] The program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0115] Calculate the first user viscosity index value within the current corresponding first time window;

[0116] Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value;

[0117] identifying a target second time window according to the target second user viscosity index value;

[0118] Based on the historical promotion activity information corresponding to the target second time window, a current corresponding promotion activity is generated.

[0119] In an optional implementation, the user stickiness index includes at least one of the following indicators:

[0120] Retention rate, activity, reading rate, and comment rate.

[0121] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0122] If there are multiple user viscosity indicators, the first user viscosity indicator value and the second user viscosity indicator value belonging to the same user viscosity indicator are matched to identify a target second user viscosity indicator value belonging to the user viscosity indicator.

[0123] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0124] If the second time window includes multiple target second user viscosity index values, and each target second user viscosity index value included belongs to each user viscosity index respectively, then the second time window is determined to be the target second time window.

[0125] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0126] Matching the index value range corresponding to the first user viscosity index value with the index value range corresponding to the second user viscosity index value;

[0127] If the index value range corresponding to the first user viscosity index value and the index value range corresponding to the second user viscosity index value belong to the same preset index value range, the second user viscosity index value is determined to be the target second user viscosity index value.

[0128] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0129] Matching a change trend of the first user viscosity index value with a change trend of the second user viscosity index value;

[0130] If the similarity between the change trend of the first user viscosity index value and the change trend of the second user viscosity index value is greater than a preset similarity threshold, the second user viscosity index value is determined to be the target second user viscosity index value.

[0131] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0132] Based on the historical promotion activity information corresponding to the multiple target second time windows, a current corresponding promotion activity is generated.

[0133] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0134] Calculate the historical promotion activity reference value corresponding to the second time window of any target;

[0135] According to the historical promotion activity reference value corresponding to the target second time window, a revised target second time window is selected from multiple target second time windows;

[0136] According to the historical promotion activity information corresponding to the second time window of the revised target, a current corresponding promotion activity is generated.

[0137] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0138] According to the interval between any target second time window and the current time and / or the historical promotion activity effect evaluation value, the historical promotion activity reference value corresponding to the target second time window is calculated.

[0139] In an optional embodiment, the historical promotion activity reference value corresponding to the target second time window is positively correlated with the historical promotion activity effect evaluation value corresponding to the target second time window, and / or the historical promotion activity reference value corresponding to the target second time window is negatively correlated with the interval between the target second time window and the current time.

[0140] In an optional implementation, the program 310 may be specifically configured to enable the processor 302 to perform the following operations:

[0141] The target second time window with the highest reference value of historical promotion activities is used as the revised target second time window.

[0142] In an optional implementation, the interval between the end point of the first time window and the current time is less than a preset time interval.

[0143] In an optional implementation, the length of the first time window is the same as the length of the second time window.

[0144] It can be seen that this embodiment generates the current promotion activity based on the promotion activity information in the historical period with high similarity to the current user viscosity characteristics, so that the generated promotion activity has a high degree of match with the current actual situation, which is beneficial to improving the user retention rate and user activity of the application platform; furthermore, since the promotion activity has a high degree of match with the current actual situation, it further avoids the waste of promotion resources and is beneficial to the improvement of user experience.

[0145] The algorithm or display provided herein is not inherently related to any particular computer, virtual system or other equipment. Various general purpose systems can also be used together with the teachings based on this. According to the above description, it is obvious to construct the structure required for this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the description made to specific languages ​​above is for disclosing the best mode of the present invention.

[0146] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0147] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, the various features of the embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting the following intention: that the claimed invention requires more features than the features explicitly recited in each claim. More specifically, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Therefore, the claims that follow the specific embodiment are hereby expressly incorporated into the specific embodiment, with each claim itself serving as a separate embodiment of the present invention.

[0148] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition they may be divided into a plurality of submodules or subunits or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive, all features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed in this manner may be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0149] In addition, those skilled in the art will appreciate that, although some embodiments herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present invention and form different embodiments. For example, in the claims below, any one of the claimed embodiments may be used in any combination.

[0150] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all functions of some or all components according to embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., computer program and computer program product) for executing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0151] It should be noted that the above embodiments illustrate the present invention rather than limit it, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets shall not be construed as a limitation on the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising a number of different elements and by means of a suitably programmed computer. In a unit claim that lists a number of devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be understood as limitations on the order of execution.

Claims

1. A method for generating a promotion activity, comprising: Calculate the first user viscosity index value within the current corresponding first time window; Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value; wherein the user viscosity index value is a specific value of a user viscosity index, and the user viscosity index can reflect the degree of user dependence on the application platform; identifying a target second time window according to the target second user viscosity index value; Calculate a historical promotion activity reference value corresponding to any target second time window according to the interval between any target second time window and the current time and the historical promotion activity effect evaluation value; select a modified target second time window from multiple target second time windows according to the historical promotion activity reference value corresponding to the target second time window; wherein the historical promotion activity reference value corresponding to the target second time window is positively correlated to the historical promotion activity effect evaluation value corresponding to the target second time window, and / or the historical promotion activity reference value corresponding to the target second time window is negatively correlated to the interval between the target second time window and the current time; Based on the historical promotion activity information corresponding to the modified target second time window, the current corresponding promotion activity is automatically generated.

2. The method according to claim 1, wherein: User stickiness indicators include at least one of the following indicators: Retention rate, activity, reading rate, and comment rate.

3. The method according to claim 2, wherein: If there are multiple user stickiness indicators; Then the step of matching the first user viscosity index value with a second user viscosity index value within any second time window stored in the history database and identifying a target second user viscosity index value matching the first user viscosity index value further includes: The first user viscosity index value and the second user viscosity index value belonging to the same user viscosity index are matched to identify a target second user viscosity index value belonging to the user viscosity index.

4. The method according to claim 3, wherein: The identifying the target second time window according to the target second user viscosity index value further includes: If the second time window includes multiple target second user viscosity index values, and each target second user viscosity index value included belongs to each user viscosity index respectively, then the second time window is determined to be the target second time window.

5. The method according to any one of claims 1 to 4, wherein: The matching of the first user viscosity index value with a second user viscosity index value within any second time window stored in the history database to identify a target second user viscosity index value matching the first user viscosity index value further includes: Matching the index value range corresponding to the first user viscosity index value with the index value range corresponding to the second user viscosity index value; If the index value range corresponding to the first user viscosity index value and the index value range corresponding to the second user viscosity index value belong to the same preset index value range, the second user viscosity index value is determined to be the target second user viscosity index value.

6. The method according to any one of claims 1 to 4, wherein: The matching of the first user viscosity index value with a second user viscosity index value within any second time window stored in the history database to identify a target second user viscosity index value matching the first user viscosity index value further includes: Matching a change trend of the first user viscosity index value with a change trend of the second user viscosity index value; If the similarity between the change trend of the first user viscosity index value and the change trend of the second user viscosity index value is greater than a preset similarity threshold, the second user viscosity index value is determined to be the target second user viscosity index value.

7. The method according to any one of claims 1 to 4, wherein: The step of selecting a modified target second time window from a plurality of target second time windows according to the historical promotion activity reference value corresponding to the target second time window further includes: The target second time window with the highest reference value of historical promotion activities is used as the revised target second time window.

8. The method according to any one of claims 1 to 4, wherein: The interval between the end point of the first time window and the current time is less than a preset time interval.

9. The method according to claim 8, wherein: The length of the first time window is the same as the length of the second time window.

10. A computing device comprising: A processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform the following operations: Calculate the first user viscosity index value within the current corresponding first time window; Matching the first user viscosity index value with a second user viscosity index value within any second time window stored in a historical database, and identifying a target second user viscosity index value that matches the first user viscosity index value; wherein the user viscosity index value is a specific value of a user viscosity index, and the user viscosity index can reflect the degree of user dependence on the application platform; identifying a target second time window according to the target second user viscosity index value; Calculate a historical promotion activity reference value corresponding to any target second time window according to the interval between any target second time window and the current time and the historical promotion activity effect evaluation value; select a modified target second time window from multiple target second time windows according to the historical promotion activity reference value corresponding to the target second time window; wherein the historical promotion activity reference value corresponding to the target second time window is positively correlated to the historical promotion activity effect evaluation value corresponding to the target second time window, and / or the historical promotion activity reference value corresponding to the target second time window is negatively correlated to the interval between the target second time window and the current time; Based on the historical promotion activity information corresponding to the modified target second time window, the current corresponding promotion activity is automatically generated.

11. The computing device of claim 10, wherein: User stickiness indicators include at least one of the following indicators: Retention rate, activity, reading rate, and comment rate.

12. The computing device of claim 11, wherein: The executable instructions cause the processor to perform the following operations: If there are multiple user viscosity indicators, the first user viscosity indicator value and the second user viscosity indicator value belonging to the same user viscosity indicator are matched to identify a target second user viscosity indicator value belonging to the user viscosity indicator.

13. The computing device of claim 12, wherein: The executable instructions cause the processor to perform the following operations: If the second time window includes multiple target second user viscosity index values, and each target second user viscosity index value included belongs to each user viscosity index respectively, then the second time window is determined to be the target second time window.

14. The computing device according to any one of claims 10 to 13, wherein: The executable instructions cause the processor to perform the following operations: Matching the index value range corresponding to the first user viscosity index value with the index value range corresponding to the second user viscosity index value; If the index value range corresponding to the first user viscosity index value and the index value range corresponding to the second user viscosity index value belong to the same preset index value range, the second user viscosity index value is determined to be the target second user viscosity index value.

15. The computing device according to any one of claims 10 to 13, wherein: The executable instructions cause the processor to perform the following operations: Matching a change trend of the first user viscosity index value with a change trend of the second user viscosity index value; If the similarity between the change trend of the first user viscosity index value and the change trend of the second user viscosity index value is greater than a preset similarity threshold, the second user viscosity index value is determined to be the target second user viscosity index value.

16. The computing device according to any one of claims 10 to 13, wherein: The executable instructions cause the processor to perform the following operations: The target second time window with the highest reference value of historical promotion activities is used as the revised target second time window.

17. The computing device according to any one of claims 10 to 13, wherein: The interval between the end point of the first time window and the current time is less than a preset time interval.

18. The computing device of claim 17, wherein: The length of the first time window is the same as the length of the second time window.

19. A computer storage medium, wherein at least one executable instruction is stored in the storage medium, and wherein the executable instruction enables a processor to execute operations corresponding to the promotion activity generation method according to any one of claims 1 to 9.

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