Method, device, computer equipment and readable storage medium for calculating association activity

Abstract

The present application relates to a method, device, computer equipment and computer-readable storage medium for calculating association activity, wherein the method includes: a data acquisition step for acquiring a detailed data, wherein the detailed data represents detailed information of multiple element association pairs within a target time range; an association activity model construction step for analyzing the association activity frequency and the association activity decay of each element association pair in the detailed data within a time period, and constructing an association activity calculation model; an association activity scoring step for calculating the detailed data using the association activity calculation model to obtain the association activity score of each element association pair, wherein the association activity score is used to evaluate the credibility of the association relationship. The present application proposes an association activity calculation model, which takes into account the relationship between the credibility of the association relationship and its association activity decay, and improves the accuracy of the association credibility evaluation.

Description

Technical Field

[0001] The present application relates to the field of Internet technology, and in particular to a method, device, computer equipment, and computer-readable storage medium for calculating association activity. Background Art

[0002] The problem of entity ID association is a problem of connecting the underlying data IDs, providing technical support for connecting the real identity and virtual identity in business scenarios. Existing technologies generally use the number of associations to reflect the credibility of the association, for example, the more times, the more credible the association. The above-mentioned judgment of credibility based on the number of associations is direct and easy to calculate, but the actual situation is that the credibility of the association is highly correlated with the activity within a time range. For example: a person’s current mobile phone number has been active frequently in the past month, but the total number of associations is not as good as the previous account. In this case, the active and frequent association relationship in the recent period should be more credible. Therefore, simply considering the number of associations to judge the credibility of the association and the actual situation cannot accurately judge the credibility of the association. Summary of the invention

[0003] The embodiments of the present application provide a method, apparatus, computer device and computer-readable storage medium for calculating association activity. The present application proposes an association activity calculation model for evaluating association credibility. The model considers the relationship between the credibility of the association relationship and its association activity decay, thereby improving the accuracy of the association credibility evaluation.

[0004] In a first aspect, an embodiment of the present application provides a method for calculating association activity, the method comprising:

[0005] A data acquisition step, for acquiring detailed data, wherein the detailed data represents detailed information of multiple element associations within a target time range;

[0006] The step of constructing an association activity model is used to analyze the association activity frequency and the association activity decay of each element association pair in each time period of the detailed data, and to construct an association activity calculation model;

[0007] The step of scoring the association activity is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each of the element association pairs.

[0008] Through the above steps, the association activity calculation model is constructed to realize the evaluation of the credibility of the association relationship. The calculation model simultaneously considers the association activity frequency and the association activity decay within a time range, improves the accuracy of the association activity judgment, and provides a better credibility evaluation method.

[0009] In some embodiments, the step of building the association activity model further includes:

[0010] An association active frequency acquisition step, for calculating the association active frequency in each time period according to the association times of each element association pair in the detailed data;

[0011] A time decay coefficient acquisition step, for calculating a time decay coefficient according to the associated active decay conditions of the element association pairs in different time periods in the detailed data;

[0012] The step of acquiring an association activity model is used to construct the association activity calculation model according to the association activity frequency and the time decay coefficient.

[0013] In some embodiments, in the association activity model construction step, the association activity calculation model is expressed as:

[0014]

[0015] Among them, the φ i It is used to represent the time attenuation coefficient of the i-th time period, the W i It is used to represent the association activity frequency of the i-th time period, where n is the total number of time periods within the target time range, and n is a positive integer.

[0016] In some embodiments, the time decay coefficient is obtained by calculating the associated active frequency with a time period as a period, and the time decay coefficient is further expressed as:

[0017]

[0018] Wherein, θ is a constant, Δt represents the period length from the time period to the current time, γ represents the attenuation intensity, and the γ is determined according to the detailed data, μ t A hyperparameter representing the decay position.

[0019] In some embodiments, the association active frequency is used to count the active frequency of element association pairs in each time period, and the association active frequency is further expressed as:

[0020]

[0021] The TotalCounter is used to indicate the number of associations of element association pairs within the time period, and T is used to indicate the length of time within the time period.

[0022] In some embodiments, 1≤θ≤100, -10≤μ t ≤50, 1≤γ≤100.

[0023] In some embodiments, the association activity score is output after being packaged as an object, and the output data format is a List collection and / or a Json data structure.

[0024] In a second aspect, an embodiment of the present application provides a device for calculating association activity, including:

[0025] A data acquisition module, used to acquire detailed data, wherein the detailed data represents detailed information of multiple element associations within a target time range;

[0026] A correlation activity model building module is used to analyze the correlation activity frequency and correlation activity decay of each element correlation pair in each time period of the detailed data, and to build a correlation activity calculation model;

[0027] The association activity scoring module is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each element association pair.

[0028] Through the above structure, the device constructs the association activity calculation model to realize the evaluation of the credibility of the association relationship. The calculation model simultaneously considers the association activity frequency and the association activity attenuation within the time range, improves the accuracy of the association activity judgment, and provides a better credibility evaluation method.

[0029] In some embodiments, the association activity model building module further includes:

[0030] An association active frequency acquisition module, used to calculate the association active frequency in each time period according to the association times of each element association pair in the detailed data;

[0031] A time decay coefficient acquisition module, used for calculating a time decay coefficient according to the associated active decay conditions of the element association pairs in different time periods in the detailed data;

[0032] The associated activity model acquisition module is used to construct the associated activity calculation model according to the associated activity frequency and the time decay coefficient.

[0033] In some embodiments, in the association activity model construction module, the association activity calculation model is expressed as:

[0034]

[0035] Among them, the φ i It is used to represent the time attenuation coefficient of the i-th time period, the W iIt is used to represent the association activity frequency of the i-th time period, where n is the total number of time periods within the target time range, and n is a positive integer.

[0036] In some embodiments, the time decay coefficient is obtained by calculating the associated active frequency with a time period as a period, and the time decay coefficient is further expressed as:

[0037]

[0038] Wherein, θ is a constant, Δt represents the period length from the time period to the current time, γ represents the attenuation intensity, and the γ is determined according to the detailed data, μ t A hyperparameter representing the decay position.

[0039] In some embodiments, the association active frequency is used to count the active frequency of element association pairs in each time period, and the association active frequency is further expressed as:

[0040]

[0041] The TotalCounter is used to indicate the number of associations of element association pairs within the time period, and T is used to indicate the length of time within the time period.

[0042] In some embodiments, 1≤θ≤100, -10≤μ t ≤50, 1≤γ≤100.

[0043] In some embodiments, the association activity score is output after being packaged as an object, and the output data format is a List collection and / or a Json data structure.

[0044] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for calculating the associated activity as described in the first aspect above is implemented.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for calculating the associated activity as described in the first aspect above.

[0046] Compared with the related art, the association activity calculation method, apparatus, computer device and computer-readable storage medium provided in the embodiments of the present application take into account that the credibility based on the association relationship is correlated with the activity within a time range. The embodiments of the present application characterize the credibility of the association relationship by constructing an association activity calculation model based on association time decay. The credibility reflects the activity of the association relationship and its changing trend over time, which greatly improves the accuracy of the evaluation credibility and provides users with better evaluation results.

[0047] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0049] Figure 1 is a flowchart of a method for calculating association activity according to an embodiment of the present application;

[0050] Figure 2 A schematic diagram of the attenuation coefficient of the method for calculating the association activity according to the preferred embodiment of the present application;

[0051] Figure 3 It is a schematic block diagram of the structure of an associated activity calculation device according to an embodiment of the present application.

[0052] in:

[0053] 1. Data acquisition module; 2. Related activity model construction module; 3. Related activity scoring module;

[0054] 21. Associated active frequency acquisition module; 22. Time decay coefficient acquisition module;

[0055] 23. Association activity model acquisition module. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0057] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0058] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0059] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0060] This embodiment provides a method for calculating association activity. Figure 1 is a flowchart of a method for calculating the associated activity according to an embodiment of the present application, with reference to Figure 1 As shown, the process includes the following steps:

[0061] Data acquisition step S1, for acquiring detailed data, the detailed data representing detailed information of multiple element associations within a target time range;

[0062] The association activity model building step S2 is used to analyze the association activity frequency and the association activity decay of each element association pair in each time period of the detailed data, and build an association activity calculation model;

[0063] The association activity scoring step S3 is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each element association pair. The association activity score is used to evaluate the credibility of the association relationship. The association activity score is output after object packaging, and the output data format is a List collection and / or a Json data structure.

[0064] The associated activity model building step S2 further includes:

[0065] The association active frequency acquisition step S201 is used to calculate the association active frequency in each time period according to the association times of each element association pair in the detailed data;

[0066] The time decay coefficient acquisition step S202 is used to calculate a time decay coefficient according to the associated activity decay of the element association pairs in different time periods in the detailed data;

[0067] The associated activity model acquisition step S203 is used to construct an associated activity calculation model according to the associated activity frequency and the time decay coefficient.

[0068] Through the above steps, an association activity calculation model is constructed to realize the evaluation of association credibility. The calculation model simultaneously considers the association activity frequency and the association activity decay within a time range, improves the accuracy of association activity judgment, and provides a better credibility evaluation method.

[0069] In some embodiments, in the association activity model construction step S2, the association activity calculation model is represented by the following formula (1):

[0070]

[0071] Among them, φ i Used to represent the time decay coefficient of the i-th time period, W i It is used to indicate the association activity frequency of the i-th time period, where n is the total number of time periods in the target time range and is a positive integer.

[0072] In some embodiments, the time decay coefficient is obtained by calculating the associated active frequency with a time period as a period, and the time decay coefficient is expressed by the following formula (2):

[0073]

[0074] Among them, θ is a constant, Δt represents the period length from the current time, γ represents the attenuation intensity, γ is determined according to the detailed data, μ t Represents the hyperparameter of the attenuation position. Specifically, θ, μ in this embodiment t The ranges of γ are 1≤θ≤100, -10≤μ t ≤50, 1≤γ≤100, γ is adjustable. The larger γ is, the gentler the attenuation slope is.

[0075] In some embodiments, the association active frequency is used to count the active frequency of element association pairs in each time period, and the association active frequency is further expressed as:

[0076]

[0077] Among them, TotalCounter is used to indicate the number of associations of feature association pairs within the time period, and T is used to indicate the length of time within the time period.

[0078] The embodiments of the present application are described and illustrated below through preferred embodiments.

[0079] First, the associated detailed data is obtained through step S1. The associated detailed data of this embodiment is within a time range of 6 months, calculated with weeks as the time period length. Examples of element associated detailed information are shown in the following table:

[0080] Serial number Subject(A element) Object (B element) TotalCounter(Number of occurrences) StatTime 1 A1 B1 100 20200913 2 A1 B2 80 20200913 3 A1 B3 30 20200913 4 A1 B4 200 20200913 5 A1 B1 60 20200914 6 A1 B2 50 20200914 7 A1 B3 10 20200914 8 A1 B4 70 20200914 …… …… …… …… ……

[0081] In the table, element A and element B are element association pairs, and the number of occurrences is the number of times the association pair appears during the statistical time.

[0082] Based on the association details data in the above table, a correlation activity calculation model is constructed through step S2.

[0083] Specifically, first, in step S201, the association active frequency is calculated according to the association times of each element association pair of the detailed data. For example, but not limitation, the association times of the association pairs A1 and B1 in a one-week period of this embodiment are calculated, and the association times and the time period length obtained by statistics are substituted into formula (3) to obtain the association active frequency. T is 7 days. If the number of days for which actual data statistics are collected is less than 7 days, the actual number of days can be used for calculation.

[0084] Then, the time attenuation coefficient is calculated in step S202. The weekly time period is used as the statistical basis, and the difference between the number of times and the current time is calculated based on the most recent collection time of each week as the time point. An example is shown in the following table:

[0085]

[0086]

[0087] In the table, the number of associations of feature association pair A1 and B1 in this week is 10 times, the number of associations in the first week from the current time is 20 times, the number of associations in the second week from the current time is 15 times, and so on. The number of associations in half a year is calculated in sequence and brought into formula (2) to calculate the attenuation coefficient of the Δtth week. Figure 2 Schematic diagram of the attenuation coefficient of the method for calculating the association activity according to the preferred embodiment of the present application, in which the horizontal axis represents the Δt week and the vertical axis represents the attenuation coefficient. Figure 2 As shown in the figure, the attenuation coefficient of the current week is 1, and the attenuation coefficient decreases rapidly between the 10th and 15th weeks, and accordingly, the number of associations decays rapidly. Figure 2 As shown, formula (2) can accurately represent the change of the correlation relationship over time;

[0088] Finally, the association activity frequency and its attenuation coefficient obtained in the above steps S201 and S202 are substituted into formula (1) to calculate the association activity score of the element association pair. The specific data output example is shown in the following table:

[0089] Serial number A element B factor Activity 1 A1 B1 100 2 A1 B2 90 3 A1 B3 80 4 A1 B4 60 …… …… …… ……

[0090] The above content can be packaged into an object to wrap a single content, and finally a List collection or Json data is given to complete the evaluation of the associated credibility according to the activity score.

[0091] It should be noted that the steps shown in the above process or the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here. For example, Figure 1 Step S201 and step S202 can be interchanged or performed simultaneously.

[0092] This embodiment also provides an associated activity calculation device, which is used to implement the above embodiments and preferred implementations. As used below, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0093] Figure 3 is a structural block diagram of an associated activity calculation device according to an embodiment of the present application, with reference to Figure 3 As shown, the device comprises:

[0094] Data acquisition module 1, used to acquire detailed data, the detailed data represents detailed information of multiple element associations within a target time range;

[0095] The association activity model building module 2 is used to analyze the association activity frequency and the association activity decay of each element association pair in each time period of the detailed data, and to build an association activity calculation model;

[0096] The association activity scoring module 3 is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each element association pair;

[0097] The associated activity model building module 2 further includes:

[0098] The association active frequency acquisition module 21 is used to calculate the association active frequency in each time period according to the association times of each element association pair in the detailed data;

[0099] A time decay coefficient acquisition module 22 is used to calculate a time decay coefficient according to the decay of the associated activity of the element association pairs in different time periods in the detailed data;

[0100] The associated activity model acquisition module 23 is used to construct an associated activity calculation model according to the associated activity frequency and the time decay coefficient.

[0101] Specifically, the above-mentioned association activity calculation model expression is as shown in the above-mentioned formula (1). Furthermore, the time decay coefficient and the association activity frequency are as shown in the above-mentioned formula (2) (3), which will not be repeated here.

[0102] Through the above structure, the device constructs an association activity calculation model to realize the evaluation of the credibility of the association relationship. The calculation model simultaneously considers the association activity frequency and the association activity attenuation within the time range, improves the accuracy of the association activity judgment, and provides a better credibility evaluation method.

[0103] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0104] In addition, combined Figure 1 The described method for calculating the associated activity of the embodiment of the present application can be implemented by a computer device, which includes a processor and a memory storing computer program instructions. Among them, the memory can be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor. The processor reads and executes the computer program instructions stored in the memory to implement any of the associated activity calculation methods in the above embodiments.

[0105] In addition, in combination with the associated activity calculation method in the above embodiment, the embodiment of the present application can provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any associated activity calculation method in the above embodiment is implemented.

[0106] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for calculating association activity, characterized in that: include: A data acquisition step, for acquiring detailed data, wherein the detailed data represents detailed information of multiple element associations within a target time range; The step of constructing an association activity model is used to analyze the association activity frequency and the association activity decay of each element association pair in each time period of the detailed data, and to construct an association activity calculation model; The step of scoring the association activity is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each element association pair. The step of constructing the association activity model further includes: The step of obtaining the association active frequency is used to calculate the association active frequency in each time period according to the association times of each element association pair in the detailed data. The association active frequency is used to count the active frequency of the element association pair in each time period. The association active frequency is further expressed as: ， Among them, the It is used to indicate the number of associations of element association pairs within the time period. T Used to indicate the length of time within the time period; The time decay coefficient acquisition step is used to calculate a time decay coefficient according to the association activity decay of the element association pairs in different time periods in the detailed data. The time decay coefficient is obtained by calculating the association activity frequency with the time period as a period. The time decay coefficient is further expressed as: ， in, is a constant, Indicates the length of the period from the current time. represents the attenuation strength, Determined based on the detailed data, A hyperparameter representing the decay position; The step of acquiring the association activity model is used to construct the association activity calculation model according to the association activity frequency and the time decay coefficient. The association activity calculation model is expressed as: ， Among them, the Used to indicate the i The time decay coefficient of the time period is Used to indicate the i The frequency of associated activity in each time period, n is the total number of time periods within the target time range, n Is a positive integer.

2. A device for calculating association activity, characterized in that: include: A data acquisition module, used to acquire detailed data, wherein the detailed data represents detailed information of multiple element associations within a target time range; A correlation activity model building module is used to analyze the correlation activity frequency and correlation activity decay of each element correlation pair in each time period of the detailed data, and to build a correlation activity calculation model; The association activity scoring module is used to calculate the detailed data using the association activity calculation model to obtain the association activity score of each element association pair. The association activity model construction module further includes: The association active frequency acquisition module is used to calculate the association active frequency in each time period according to the association times of each element association pair in the detailed data. The association active frequency is used to count the active frequency of the element association pair in each time period. The association active frequency is further expressed as: ， Among them, the It is used to indicate the number of associations of element association pairs within the time period. T Used to indicate the length of time within the time period; The time decay coefficient acquisition module is used to calculate a time decay coefficient according to the association activity decay of the element association pairs in different time periods in the detailed data. The time decay coefficient is obtained by calculating the association activity frequency with the time period as a period. The time decay coefficient is further expressed as: ， in, is a constant, Indicates the length of the period from the current time. represents the attenuation strength, Determined based on the detailed data, A hyperparameter representing the decay position; The association activity model acquisition module is used to construct the association activity calculation model according to the association activity frequency and the time decay coefficient. The association activity calculation model is expressed as: ， Among them, the Used to indicate the i The time decay coefficient of the time period is Used to indicate the i The frequency of associated activity in each time period, n is the total number of time periods within the target time range, n Is a positive integer.

3. A computer 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, the method for calculating the associated activity degree as claimed in claim 1 is implemented.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for calculating the associated activity as claimed in claim 1 is implemented.

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