A business resource package pre-embedding method based on business maturity, medium and equipment

Abstract

This invention relates to the field of resource package pre-embedding decision-making, and in particular to a method, medium, and device for pre-embedding business resource packages based on business maturity. The method divides the protection period for new businesses into two stages: In the first stage, relevant business indicators are collected, their growth trends are calculated, and maturity evaluation factors characterizing activity levels are generated. Based on this, the inflection point time of protection intensity decay in the second stage is dynamically determined; the higher the activity level, the earlier the inflection point. In the second stage, a reverse S-shaped decay function is used to allow highly active businesses to exit manual protection as early as possible and participate in scoring based on real data, while low-activity businesses receive a longer protection period to observe their future potential. Finally, the protection factor is combined with multi-dimensional scoring such as user volume, resource package size, page depth, and business performance to comprehensively determine whether to pre-embedding. This solution achieves precise and adaptive support for different new businesses under a fixed total protection duration, avoiding distortion in the evaluation of high-value businesses and premature elimination of potential businesses.

Description

Technical Field

[0001] This invention relates to the field of resource package pre-embedding decision-making, and in particular to a method, medium, and device for pre-embedding business resource packages based on business maturity. Background Technology

[0002] In the mobile internet application ecosystem, to improve page loading speed and user experience, business logic is often encapsulated into lightweight dynamic resource packages (such as Weex packages) and pre-embedded in the application installation package. However, due to limitations in terminal device storage space and strict restrictions on installation package size imposed by application markets, it is impossible to integrate all business resource packages indiscriminately into the installation package. Precise selection based on business value is necessary. For newly launched businesses, their historical operational data is sparse, and key metrics (such as user visits and conversion rates) are not yet stable. Directly applying static scoring models for mature businesses can easily lead to their exclusion from the pre-embedded list due to poor short-term performance, causing high-potential businesses to lose crucial exposure opportunities. Therefore, a "new business protection factor" is typically introduced as a temporary weighting item to prevent them from being misjudged as low-value businesses due to poor short-term performance.

[0003] Current technologies generally employ a fixed-duration protection strategy, assigning a gradually decaying scoring weighting factor (i.e., a "new business protection factor") to a new business during the first N days after its launch, and then immediately canceling the protection after the period expires. While this method is simple to implement, it does not consider the actual differences in activity levels among different businesses in the initial launch phase. This approach has a dual drawback: on the one hand, high-activity businesses have accumulated sufficient effective data such as user visits and conversions during the initial protection phase, and their true value is sufficient to support their inclusion in the pre-planned sequence. However, due to the continuous impact of the artificially added protection factor, their scores are unnecessarily inflated, failing to truly reflect their market competitiveness. On the other hand, low-activity businesses, although potentially possessing later growth potential, lack sufficient support within the critical observation window due to the premature decay of the protection factor to an ineffective level, leading to the premature elimination of potential businesses.

[0004] Existing technologies lack a mechanism that can adaptively adjust the protection decay rate based on early activity levels, making it difficult to balance the dual needs of "timely release of high-value business" and "extended observation of low-activity business". Summary of the Invention

[0005] To address one of the aforementioned technical problems, the present invention adopts the following technical solution:

[0006] According to one aspect of the present invention, a method for pre-embedding business resource packages based on business maturity is provided, comprising:

[0007] The protection period for new businesses is divided into a first phase and a second phase.

[0008] At the end of the first phase, a business maturity evaluation factor g is generated based on the business indicator data collected during the first phase. avg and based on g avg Determine the inflection point time t0 of the decay function in the second stage, where t0 is related to g avg Inversely proportional; g avg Used to characterize the activity level of new businesses; t0 is the relative duration with respect to the start time of the second phase. ;

[0009] In the second phase, based on t0 and the initial protection factor P2 for the new business in the second phase, the new business protection factor P corresponding to the current online time t of the new business is generated. new (t); P new (t) satisfies the following condition:

[0010] ;

[0011] in, Let t0 be the minimum distance from its boundary value. , t∈(T obs T end ], T obs T is the end time of the first phase. end The end time of the protection period L is the preset saturation boundary of the decay function, L=6 or 7; This represents the natural exponential function with base e;

[0012] Based on the new business protection factor and other pre-embedded scoring factors, determine whether to pre-embed the Weex resource package corresponding to the new business.

[0013] According to a second aspect of the present invention, a non-transitory computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the above-described method for pre-embedding business resource packages based on business maturity.

[0014] According to a third aspect of the present invention, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for pre-embedding business resource packages based on business maturity.

[0015] This invention has at least one of the following beneficial effects:

[0016] First, in this invention, the protection period for new businesses is divided into a first phase and a second phase, and at the end of the first phase, a business maturity evaluation factor g is generated based on the collected business indicators. avgThis allows us to determine the inflection point time t0 of the second-stage decay function, and t0 is related to g. avg It is inversely proportional, and the size of t0 controls the timing of the rapid decay period of the new business protection factor in the second stage. Specifically, the smaller t0 is, the earlier the rapid decay period occurs, thus enabling dynamic adaptation of the protection strength for new businesses. For highly active businesses, its g avg For businesses with a larger value, the system automatically assigns a smaller t0, allowing them to enter the rapid decay range of the protection factor early in the second phase, quickly exiting the artificially inflated state, and thus returning to a fair scoring system based on real business data as soon as possible, avoiding interference from the protection factor in their competitiveness assessment; while for low-activity businesses, their g avg A smaller value corresponds to a larger t0, and the protection factor decays slowly in the second stage, maintaining a higher level for a longer period, providing a sufficient observation window to verify whether it has the potential for later explosive growth. This mechanism effectively overcomes the dual defects of the existing "one-size-fits-all" protection strategy, which leads to the distortion of high-value business assessment and the premature elimination of potential businesses.

[0017] Secondly, in the second stage of this invention, a reverse Sigmoid decay function with t0 as the inflection point and controlled by the saturation boundary L and the normalized distance Δ is used to generate the new business protection factor P. new (t), rather than a linear or step-like decay. This design allows the protection factor to exhibit a natural transition pattern over time: "slow decline in the initial stage, rapid decay in the middle stage (the appearance of the middle stage position is controlled by t0), and then stabilization in the later stage," which better reflects the actual life cycle of a business from cold start to stable operation. Compared to the drastic fluctuations in scores caused by abrupt cancellation of protection or uniform decay in existing technologies, this invention ensures the stability of the pre-embedded score through a smooth and continuous decay curve, avoiding the erroneous exclusion of high-potential businesses during critical growth stages due to a sudden drop in the protection factor, thereby improving the robustness and rationality of pre-embedded decisions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a method for pre-embedding business resource packages based on business maturity, provided in an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] As one possible embodiment of the present invention, such as Figure 1 As shown, a method for pre-embedding business resource packages based on business maturity is provided, including:

[0022] S100: Divide the protection period for new businesses into a first phase and a second phase.

[0023] In practical applications, new businesses often face challenges such as data sparsity and unstable user behavior in their initial launch phase. Directly incorporating them into a standard scoring system can easily lead to them being incorrectly classified as low-value businesses due to poor short-term metrics, thus losing crucial exposure opportunities. Therefore, a protection period (e.g., 30-90 days) is often set for new businesses. However, applying indiscriminate protection for an extended period may mask the true competitiveness of highly active businesses and interfere with the objectivity of pre-planning decisions. Therefore, it is necessary to divide the protection period into two clearly defined phases: the first phase serves as a data collection and preliminary assessment window, used to collect early operational metrics and generate maturity evaluations; the second phase serves as a dynamic protection execution window, adaptively adjusting the protection intensity based on the assessment results of the first phase. This two-phase division ensures necessary support for new businesses while providing a basis for differentiated control. In this embodiment, the first phase can be fixed at 8 days (T... obs =8), this duration is usually set to cover most businesses completing at least one full user behavior cycle (such as weekly active users), while avoiding excessively long observation periods that could lead to decision-making delays. It can be flexibly set according to this rule.

[0024] The method further includes the following after S100:

[0025] S110: In the first stage, according to the preset attenuation coefficient And the initial protection factor P1 for new businesses in the first phase, generating the new business protection factor P corresponding to the current online time t of the new business. new (t). P new (t) satisfies the following condition:

[0026] t∈[0,T] obs ], .

[0027] The core objective of the first phase is to provide basic protection for new businesses while initiating data collection and initial observation. Since user behavior is sparse and key metrics (such as page views and conversion rates) are not yet stable in the early stages of a new business's launch, directly incorporating it into a conventional scoring system could easily lead to underestimation due to insufficient data. Therefore, a manually set initial protection factor for the new business needs to be introduced to enhance its initial scoring competitiveness. However, maintaining a constant protection level throughout the first phase would weaken the role of real business data in the scoring, hindering subsequent objective evaluation. Therefore, this embodiment sets a weak but continuously decreasing trend for the protection factor, allowing it to slowly decline over time, thereby gradually reducing the weight of human intervention and allowing the continuously accumulating business data to play an increasingly important role in the pre-set scoring.

[0028] Considering that the first phase is usually short (e.g., 8 days) and the growth of business data is relatively slow, the decay rate coefficient... Set to a smaller value (e.g.) This ensures that the protective factor decays only at a gradual rate. For example, when P1=1.5, T obs When the value is 8, the protective factor on day 8 is P. new (t) = 1.5 × (1 − 0.01 × 8) = 1.38, with an attenuation range of only 8%, which reflects the control logic of decreasing over time while avoiding protection failure due to excessively rapid attenuation. Furthermore, constraints... P was guaranteed new (t) is always greater than zero to prevent negative protection or scoring anomalies. This design ensures that new businesses receive the necessary support while laying the foundation for a smooth transition to the second phase of dynamic evaluation.

[0029] S200: At the end of the first phase, a business maturity evaluation factor g is generated based on the business indicator data collected during the first phase. avg and based on g avg Determine the inflection point time t0 of the decay function in the second stage, where t0 is related to g avg Inversely proportional. g avg Used to characterize the activity level of new business. t0 is the relative duration compared to the start time of the second phase. .

[0030] This step aims to address the dual shortcomings of rigid protection strategies in existing technologies: highly active businesses are overprotected and their true value cannot be assessed, while the potential of inactive businesses is mistakenly suppressed due to insufficient protection. To achieve this goal, it is necessary to establish an indicator that can quantify the early growth trend of a business and dynamically adjust the pace of subsequent protection accordingly. avgThis comprehensive evaluation factor was designed for this purpose. User traffic, revenue or conversion performance, and return on investment were chosen as basic indicators because these three comprehensively characterize business health from three dimensions: "user scale," "commercial value," and "operational efficiency," respectively. Furthermore, all three are high-frequency, quantifiable, and highly resistant to fraud data sources. Additionally, due to the short duration of the first phase (typically 8 days), to avoid evaluation bias caused by overlapping sliding windows, this embodiment directly calculates the trend of changes based on the daily collected indicator sequences.

[0031] Specifically, business metrics include at least two of the following: user visits, revenue or conversion performance, and return on investment.

[0032] g avg Generate according to the following steps:

[0033] S201: For each type of indicator, using its daily observations during the first phase as input, a linear regression model is fitted using the least squares method to obtain the trend slope b corresponding to each type of indicator. u ,b r ,b roi b u ,b r ,b roi These are the trend slopes for user visits, revenue or conversion performance, and return on investment, used to characterize the growth rate of various business indicators.

[0034] S202: According to b u ,b r ,b roi Generate g avg g avg The following conditions must be met:

[0035] .

[0036] in, These are the preset weight coefficients for the corresponding indicators, and they satisfy... .

[0037] In the initial stages of business launch, the primary task is to verify user willingness to use the service (i.e., "user scale"), followed by monetization capabilities (revenue / conversion), and finally, return on investment (ROI). Therefore, assigning a slope to the user traffic trend is crucial. 𝑢 Highest weight (e.g., w) 𝑢 =0.5), with revenue-related slopes being the second most common (e.g., w). r =0.3), with the lowest ROI weight (e.g., ROI = 0.3). =0.2). Through this weight allocation, g avg It can more accurately reflect whether a business has the key active characteristic of "user appeal" in its early stages.

[0038] This design fully utilizes the data from all 8 days of the first phase, effectively suppressing daily fluctuations and enabling g avg It more accurately reflects the inherent growth potential of the business, that is, it can reflect the level of activity of the business.

[0039] In addition, t0 satisfies the following relationship:

[0040] .

[0041] Where d is the preset benchmark inflection point.

[0042] This formula establishes g through nonlinear mapping. avg The inverse relationship with t0 means that the higher the business activity, the earlier the protection attenuation starts. The parameter d controls the maximum possible value of t0 (when g...). avg When t = 0, t0 = d), and its specific value can be set according to the maximum observation window length allowed in the actual business scenario. For example, in scenarios with strict constraints on the installation package volume and a need for rapid convergence of pre-embedded decisions, d can be set to a smaller value (such as 10); in scenarios that encourage innovation and allow for a longer observation period, d can be appropriately increased (such as 20). This design makes the protection strategy highly configurable and adaptable to different scenarios.

[0043] S300: In the second phase, based on t0 and the initial protection factor P2 for the new business in the second phase, generate the new business protection factor P corresponding to the current online time t of the new business. new (t). P new (t) satisfies the following condition:

[0044] .

[0045] in, Let t0 be the minimum distance from its boundary value. , t∈(T obs T end ], T obs T is the end time of the first phase. end The end time of the protection period L is the preset saturation boundary of the decay function, L=6 or 7. This represents the natural exponential function with base e.

[0046] The function used in this step is essentially a reverse Sigmoid decay function (i.e., a monotonically decreasing Sigmoid curve). Its core function is to control the timing of the protective factor's exit from human intervention by adjusting the position of the decay inflection point t0, given a fixed total duration in the second stage. Since the length T of the second stage...end -T obs Typically set to a fixed value (e.g., 82 days), the system cannot adapt to different business needs by extending or shortening the protection period. Therefore, the duration of "strong protection" must be dynamically adjusted within a fixed window. This function operates on t−T... obs When t=0, the output is close to P2, maintaining a high protection level; when t−T obs As the function approaches and exceeds t0, its value decreases rapidly; as t−T obs When ≫t0, P new When (t) approaches 1, the protection state is completely exited. This design allows the protection strength to decay smoothly over time, avoiding the sudden change in score caused by step cancellation. At the same time, it ensures that highly active businesses can get rid of artificial enhancements earlier during the protection period, while low-active businesses retain protection support for a longer period of time to observe whether they have the potential for future growth.

[0047] The role of L is to scale the normalized time offset to ensure that the input to the inverse Sigmoid function always falls within its sensitive response range. Standard Sigmoid function When x∈[−6,6] or [−7,7], the output value can smoothly change from near 0 to near 1; if the input exceeds this range, the function will quickly saturate and lose its discriminative power. In this embodiment, the time offset term... The range of values ​​for is [−1, 1] (from...) To ensure this, a coefficient L needs to be introduced to linearly map it to [−L,L]. When L=6 or 7, the function input exactly covers the effective working interval of the Sigmoid, making P0... new (t) can achieve a complete, smooth, and unsaturated decay process from near P2 to near 0 throughout the entire second stage. If L is not set, or if the value of L is too small, the function output variation range is too narrow and cannot effectively distinguish the protection strength; if L is too large, it is easy to cause the function to jump near the inflection point and lose smoothness.

[0048] The introduction of Δ ensures the symmetry and predictability of the decay behavior. Since t0 is the relative time (in days) within the second stage, its value ranges from [0, T]. end -T obs If a fixed scale is used directly, the attenuation curve will be truncated when t0 is near the endpoint of the interval, resulting in distortion of the protection behavior for high-activity or low-activity services. By making... The system automatically constructs an effective attenuation range centered on t0, ensuring that the protection factor can fully exhibit the attenuation characteristics of "high-rapid decrease-stable" regardless of the value of t0.

[0049] For example:

[0050] Assume the second phase lasts a total of 82 days (T) obs =8,T end =90), P2=1.38, L=6, d=15.

[0051] Highly active business A: g avg =10→t0=15 / (1+10)≈1.36 days, corresponding to .

[0052] Starting from day 9, it will be approximately day 10 (t=T) obs +1.36) entered the rapid decay zone, on day 15. This essentially eliminates the artificial protection of new businesses, allowing their subsequent ratings to be primarily determined by real business data.

[0053] Low-activity business B: g avg =0.2→t0=15 / (1+0.2)=12.5 days, corresponding to .

[0054] Its protective factor on day 20 It remained above 1.2 until around day 30 when it significantly decreased, thus obtaining a strong protection window of more than three weeks to observe whether a user growth inflection point appeared in the later part of the protection period.

[0055] Thus, with the same total protection duration, the system enables precise and adaptive protection strategies for services with different growth characteristics.

[0056] S400: Based on the new business protection factor and other pre-embedded scoring factors, determine whether to pre-embed the Weex resource package corresponding to the new business.

[0057] Specifically, other pre-embedded scoring factors include user volume weight factor, resource package volume penalty factor, page level depth weight factor, and business performance coefficient.

[0058] The S400 includes:

[0059] S401: Standardize the raw scoring data for each dimension to generate the pre-embedded scoring factors for each dimension.

[0060] Standardization processes include:

[0061] Normalize the maximum value of user access volume and business performance data.

[0062] Minimum normalization or reverse mapping is performed on the resource package volume and page hierarchy depth to unify the value range of all factors to the interval [0,1].

[0063] Because the original data dimensions and orders of magnitude differ significantly across dimensions (e.g., user numbers can reach millions, while package size is only in the MB range), direct weighting would lead to high-dimensional metrics dominating the scoring results. Therefore, standardization is necessary: ​​positive metrics (the larger the better, such as UV and GMV) should be normalized to their maximum value. For negative metrics (the smaller the better, such as package size and page depth), use inverse mapping. This process ensures that all factors fall within the [0,1] interval, guaranteeing that the weight allocation is meaningful.

[0064] S402: Generate a comprehensive pre-embedded score P based on the new business protection factor and other pre-embedded scoring factors in other dimensions.

[0065] P satisfies the following condition:

[0066] .

[0067] in, The normalized user volume weighting factor. The normalized business performance coefficient, This represents the normalized resource package volume. The page hierarchy depth is the normalized value, and w1 to w5 are the preset weight coefficients for the corresponding factors. The preset weight coefficients satisfy: .

[0068] This weighting constraint reflects the core logic of new business evaluation: during the protection period, artificial protection factors should dominate to compensate for insufficient early data; as protection factors diminish, actual business performance gradually becomes the basis for decision-making. w5 is the highest, ensuring that high-potential businesses are not underestimated due to initial data scarcity; w1 and w4 are next, emphasizing user experience; w2 and w3 are lower, avoiding premature pursuit of commercial value or excessive penalties for functional completeness. The specific values ​​of each weight can be flexibly configured according to product strategy; for example, w5 can be increased during the exploration phase, and w1 can be increased during the maturity phase.

[0069] S403: If the comprehensive pre-embedded score P is greater than or equal to the preset threshold P th If so, the Weex resource package corresponding to the new business will be included in the pre-installed list.

[0070] S404: If the comprehensive pre-embedded score P is less than the preset threshold P th If so, the new service is marked as a non-pre-embedded resource.

[0071] Among them, P th =0.8.

[0072] Threshold P thUsed to define the boundaries of pre-embedded qualifications, its value can be set according to actual needs such as installation package volume budget and business priority. For example, when resources are tight, P can be increased. th Entry requirements should be tightened; however, they can be appropriately lowered when innovation is encouraged. It is worth noting that for highly active businesses, their P... new (t) decays rapidly to near 0 in the early part of the second stage, at which point P is mainly composed of F user If the P / E ratio remains ≥0.8, supported by real-world metrics, it indicates independent competitiveness; however, for low-activity businesses, P... new If (t) remains above 1 for an extended period, the P-value can be temporarily increased to retain the opportunity for observation. If P < 0.8 at the end of the protection period, then the device should be rationally eliminated. Thus, the entire mechanism achieves the goals of dynamic protection, objective evaluation, and precise screening.

[0073] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0074] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0075] In an exemplary embodiment of this disclosure, an electronic device capable of implementing the above-described method is also provided.

[0076] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as “circuit,” “module,” or “system.”

[0077] An electronic device according to this embodiment of the invention. The electronic device is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the invention.

[0078] Electronic devices are manifested in the form of general-purpose computing devices. Components of an electronic device may include, but are not limited to: at least one processor, at least one memory, and buses connecting different system components (including memory and processor).

[0079] The memory stores program code that can be executed by a processor, causing the processor to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of the present invention.

[0080] The storage may include readable media in the form of volatile storage, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0081] The storage may also include programs / utilities having a set (at least one) of program modules, including but not limited to: an operating system, one or more applications, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0082] A bus can represent one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus that uses any of the various bus architectures.

[0083] The electronic device can also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication can be performed via input / output (I / O) interfaces. Furthermore, the electronic device can communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a bus. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0084] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention may also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0085] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0086] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0087] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0088] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0089] Furthermore, the accompanying drawings are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes shown in the above drawings do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0090] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0091] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for pre-embedding business resource packages based on business maturity, characterized in that, include: The protection period for new businesses is divided into a first phase and a second phase. At the end of the first phase, a business maturity evaluation factor g is generated based on the business indicator data collected during the first phase. avg and based on g avg Determine the inflection point time t0 of the decay function in the second stage, where t0 is related to g avg Inversely proportional; g avg Used to characterize the activity level of new businesses; t0 is the relative duration with respect to the start time of the second phase. ; In the second stage, based on t0 and the initial protection factor P2 for the new business in the second stage, the new business protection factor P corresponding to the current online time t of the new business is generated. new (t); P new (t) satisfies the following condition: ； in, Let t0 be the minimum distance from its boundary value. , t∈(T obs T end ], T obs T is the end time of the first phase. end The protection period ends at L, which is the preset saturation boundary of the decay function, where L = 6 or 7. This represents the natural exponential function with base e; Based on the new business protection factor and other pre-embedded scoring factors, determine whether to pre-embed the Weex resource package corresponding to the new business.

2. The method according to claim 1, characterized in that, The method further includes: In the first stage, according to the preset attenuation rate coefficient And the initial protection factor P1 for the new business in the first phase, generate the new business protection factor P corresponding to the current online time t of the new business. new (t); P new (t) satisfies the following condition: ;t∈[0,T obs ], 。 3. The method according to claim 1, characterized in that, g avg This is generated based on business metrics data collected during the first phase; the business metrics data includes at least two of the following: user visits, revenue or conversion performance, and return on investment. g avg Generate according to the following steps: For each type of indicator, using its daily observations during the first phase as input, a linear regression model is fitted using the least squares method to obtain the trend slope b corresponding to each type of indicator. u ,b r ,b roi b u ,b r ,b roi These are the trend slopes for user visits, revenue or conversion performance, and return on investment, respectively, used to characterize the growth rate of various business indicators. According to b u ,b r ,b roi Generate g avg g avg The following conditions must be met: ； in, These are the preset weight coefficients for the corresponding indicators, and they satisfy... .

4. The method according to claim 3, characterized in that, t0 satisfies the following relationship: ； Where d is the preset benchmark inflection point.

5. The method according to claim 1, characterized in that, The other pre-embedded scoring factors include user volume weight factor, resource package volume penalty factor, page level depth weight factor, and business performance coefficient. The overall pre-embedded score P satisfies the following conditions: ； in, The normalized user volume weighting factor. The normalized business performance coefficient, This represents the normalized resource package volume. The normalized page hierarchy depth is represented by w1 to w5, which are the preset weight coefficients for the corresponding factors.

6. The method according to claim 5, characterized in that, Before calculating the comprehensive pre-embedded score P, the method further includes: The original scoring data are standardized to generate pre-embedded scoring factors for each dimension; The standardization process includes: Normalize the maximum value of user access volume and business performance data; Minimum normalization or reverse mapping is performed on the resource package volume and page hierarchy depth to unify the value range of all factors to the interval [0,1].

7. The method according to claim 5 or 6, characterized in that, The preset weighting coefficients satisfy: .

8. The method according to claim 5, characterized in that, Based on the new business protection factor and other pre-embedded scoring factors, determine whether to pre-embed the Weex resource package corresponding to the new business, including: If the comprehensive pre-embedded score P is greater than or equal to the preset threshold P th If so, the Weex resource package corresponding to the new business will be included in the pre-embedded list; If the comprehensive pre-embedded score P is less than the preset threshold P th If so, the new service is marked as a non-pre-embedded resource; Among them, P th =0.

8.

9. A non-transitory computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for pre-embedding business resource packages based on business maturity as described in any one of claims 1 to 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements a method for pre-embedding business resource packages based on business maturity as described in any one of claims 1 to 8.

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