A method, device, equipment and medium for judging similarity of data analysis indicators

Abstract

The present application discloses a method for judging the similarity of data analysis indicators, specifically, obtaining a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator. Then, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula. The first standard calculation formula and the second standard calculation formula have the same expression form, but the atomic indicators constituting the first standard calculation formula and the atomic indicators constituting the second standard calculation formula may be different. Then, the similarity between the first data analysis indicator and the second data analysis indicator is determined based on the first standard calculation formula and the second standard calculation formula. That is, the present application determines whether the two data analysis indicators are similar by comparing the two standard calculation formulas after converting the calculation formula corresponding to the first data analysis indicator and the calculation formula corresponding to the second data analysis indicator into standard calculation formulas, without relying on manual naming, thereby improving the similarity judgment result.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device, equipment and medium for determining similarity of data analysis indicators. Background Art

[0002] When researching a product or business, an indicator system is typically established to comprehensively measure its development. However, this system includes a large number of indicators, some of which overlap, leading to increased redundancy. Currently, similarity between two indicators is primarily determined through naming and description. However, these naming and description processes are largely manual, inevitably introducing subjective factors and resulting in inaccurate similarity assessments. Summary of the Invention

[0003] In view of this, embodiments of the present application provide a method, apparatus, device, and medium for determining similarity of data analysis indicators to improve the accuracy of indicator similarity determination and reduce the construction of similar indicators.

[0004] To achieve the above objectives, the technical solutions provided in the embodiments of the present application are as follows:

[0005] In a first aspect of the present application, a method for determining similarity of data analysis indicators is provided, the method comprising:

[0006] Obtaining a first calculation formula corresponding to the first data analysis indicator and a second calculation formula corresponding to the second data analysis indicator, wherein the first calculation formula and the second calculation formula are each composed of at least one atomic indicator, and different atomic indicators in the at least one atomic indicator are independent of each other;

[0007] Converting the first calculation formula into a first standard calculation formula and converting the second calculation formula into a second standard calculation formula, wherein the first standard calculation formula and the second standard calculation formula have the same structural form;

[0008] The similarity between the first data analysis index and the second data numerator index is determined according to the first standard calculation formula and the second standard calculation formula.

[0009] In a second aspect of the present application, a device for determining similarity of data analysis indicators is provided, the device comprising:

[0010] An acquiring unit, configured to acquire a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator, wherein the first calculation formula and the second calculation formula are respectively composed of at least one atomic indicator, and different atomic indicators in the at least one atomic indicator are independent of each other;

[0011] a conversion unit, configured to convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula, wherein the first standard calculation formula and the second standard calculation formula have the same structural form;

[0012] A determining unit is configured to determine the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula.

[0013] In a third aspect of the present application, an electronic device is provided, the device comprising: a processor and a memory;

[0014] The memory is used to store instructions or computer programs;

[0015] The processor is configured to execute the instructions or computer program in the memory so that the electronic device executes the method described in the first aspect.

[0016] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein instructions are stored in the computer-readable storage medium. When the instructions are executed on a device, the device executes the method described in the first aspect.

[0017] In a fifth aspect of the present application, a computer program product is provided, wherein the computer program product comprises a computer program / instructions, and when the computer program / instructions are executed by a processor, the method described in the first aspect is implemented.

[0018] It can be seen that the embodiments of the present application have the following beneficial effects:

[0019] In an embodiment of the present application, in order to judge the similarity between two data analysis indicators, the calculation formulas corresponding to the two data analysis indicators are obtained. That is, a first calculation formula corresponding to the first data analysis indicator and a second calculation formula corresponding to the second data analysis indicator are obtained, and the first calculation formula and the second calculation formula are respectively composed of at least one atomic indicator. Different atomic indicators in at least one atomic indicator are independent of each other. That is, the atomic indicators cannot be converted into each other. Then, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula. The first standard calculation formula and the second standard calculation formula have the same expression form, but the atomic indicators constituting the first standard calculation formula and the atomic indicators constituting the second standard calculation formula may be different. Then, the similarity between the first data analysis indicator and the second data analysis indicator is determined based on the first standard calculation formula and the second standard calculation formula. That is, the present application determines whether the two data analysis indicators are similar by comparing the two standard calculation formulas after converting the calculation formula corresponding to the first data analysis indicator and the calculation formula corresponding to the second data analysis indicator into standard calculation formulas, without relying on manual naming, thereby improving the similarity judgment result. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 A flow chart of a method for determining similarity of data analysis indicators provided in an embodiment of the present application;

[0022] Figure 2 A structural diagram of a data analysis indicator similarity judgment device provided in an embodiment of the present application;

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0025] When constructing an indicator system, for a newly added data analysis indicator or an existing data analysis indicator in the indicator system, it is necessary to determine whether the function of the newly added data analysis indicator is covered by the existing data analysis indicators in the indicator system, or whether there is functional duplication between the existing data analysis indicators in the indicator system, so as to avoid redundant growth of indicators.

[0026] Based on this, an embodiment of the present application provides a method for determining similarity between data analysis indicators. This method converts the calculation formula corresponding to the data analysis indicator into a standard calculation formula, and then compares the standard calculation formulas corresponding to different data analysis indicators to determine the similarity between the indicators. The calculation formula corresponding to the data analysis indicator is converted according to a preset conversion standard to ensure that the structure of the converted standard calculation formula is consistent, facilitating similarity calculation.

[0027] The conversion criteria can include rational function domain criteria or rational functions. For example, the indicator calculation formula can be converted according to the expression corresponding to the rational function domain, so that the expression form of the converted annotated calculation formula is consistent with the expression form of the rational function domain. For ease of understanding, rational functions and rational function domains are first explained.

[0028] A polynomial ring is a set R and two binary operations defined on it: addition and multiplication. Typically, a set R and two binary operations defined on it are called a ring if they satisfy the following conditions: addition is commutative and associative, and multiplication is associative and distributive.

[0029] Among them, the polynomial ring can include a univariate polynomial ring and an n-variate polynomial ring:

[0030] A univariate polynomial ring:

[0031] N-ary polynomial ring:

[0032] A field is a set in which addition, subtraction, multiplication, and division operations can be performed on non-zero elements in the set. A field is a type of ring, differing primarily in that it requires non-zero primitives to be divisible. After defining the necessary addition, subtraction, multiplication, and division operations on n elements X = {x1, x2, …, xn}, the elements in the set can be expressed using the following two polynomial ring division operations:

[0033]

[0034] In an embodiment of the present application, the calculation formula corresponding to the index can be converted into a polynomial ring according to a rational function, or the calculation formula corresponding to the index can be converted into the quotient of two polynomial rings according to a rational function.

[0035] The specific form of the data analysis indicators in the embodiments of the present application is determined according to the actual application scenario. For example, to analyze the effectiveness of advertising, the data analysis indicators may be ad click-through rate, ad conversion rate, etc. The judgment method provided in this application can be applied to any application scenario with data analysis requirements.

[0036] To facilitate understanding of the technical solutions provided in the embodiments of the present application, they will be described below with reference to the accompanying drawings.

[0037] See also Figure 1, this figure is a flow chart of a method for judging the similarity of data analysis indicators provided in an embodiment of the present application. The method can be executed by a data analysis indicator similarity judgment device, which can be a server, an electronic device, or other devices, and is not limited here. Among them, the server can be a cloud server or a server cluster and other devices with storage and computing functions. Electronic devices can include mobile phones, tablet computers, desktop computers, laptops, vehicle-mounted terminals, wearable electronic devices, all-in-one machines, smart home devices and other devices with communication functions, and can also be devices simulated by virtual machines or simulators. As Figure 1 As shown, the method may include the following steps:

[0038] S101: Obtain a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator.

[0039] In this embodiment, to compare the similarity between two data analysis metrics, we first obtain the corresponding formula for each data analysis metric. The first and second formulas are each composed of at least one atomic metric. Atomic metrics are the fundamental elements of an metric system. Different atomic metrics are independent of each other and cannot be transformed into each other through operations. For example, if the atomic metric set M includes n atomic metrics {M1, M2, …, Mn}, then Mi and Mj cannot be transformed into each other, and i is not equal to j.

[0040] Optionally, one of the first and second data analysis indicators is a newly added indicator, while the other already exists in the indicator system. In this case, similarity determination can be performed between the newly added indicator and the existing indicator, avoiding redundant additions. Alternatively, both the first and second data analysis indicators are already in the indicator system. In this case, similarity determination can be performed between the existing indicators in the indicator system, thereby removing duplicate indicators and reducing the workload of indicator system maintenance.

[0041] Optionally, the first data analysis indicator and the second data analysis indicator may be derived indicators or calculated indicators. A derived indicator refers to an indicator that takes on different values ​​under different given conditions, and a calculated indicator refers to an indicator obtained by calculation based on one or more atomic indicators. Specifically, a calculated indicator may be obtained by calculation based on one or more of the four arithmetic operations based on one or more atomic indicators.

[0042] For example, Q = {M1 / 2, if M1>0; M1, if M1≤0}. The data analysis indicator Q is a derived indicator. When the value of the atomic indicator M1 is greater than 0, Q is equal to M1 / 2; when the value of the atomic indicator M1 is less than or equal to 0, Q is equal to M1. P = M1+M2-M3. The data analysis indicator P is a calculated indicator.

[0043] Among them, since the derived indicators are generated based on different judgment conditions, in order to facilitate subsequent conversion, the derived indicators can be converted into a linear combination of atomic indicators. For example, the derived indicator Q = M1*(I M1>0 / 2+I M1≤0 ).

[0044] S102: Convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula.

[0045] After obtaining a first calculation formula corresponding to the first data analysis indicator and a second calculation formula corresponding to the second data analysis indicator, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula, wherein the first standard calculation formula and the second standard calculation formula have the same structure.

[0046] Optionally, the first calculation formula can be converted into a first standard calculation formula and the second calculation formula can be converted into a second standard calculation formula based on a rational function. Under this conversion method, the first standard calculation formula and the second standard calculation formula are structurally in the form of a polynomial ring. The polynomial ring is composed of at least one atomic index through one or more of addition or subtraction and multiplication. The polynomial ring can be a univariate polynomial ring or a multivariate polynomial ring.

[0047] When a calculation index depends on only one atomic index M1 and is obtained by addition and multiplication, the standard calculation formula corresponding to the calculation index is a univariate index polynomial ring:

[0048]

[0049] When a calculation index depends on n atomic indexes and is obtained by addition and multiplication, the standard calculation formula corresponding to the calculation index is an n-ary index polynomial ring:

[0050]

[0051] Optionally, the first calculation formula can be converted into a first standard calculation formula and the second calculation formula can be converted into a second standard calculation formula based on the field of rational functions. The first standard calculation formula and the second standard calculation formula have the structural form of the quotient of two polynomial rings. Each of the two polynomial rings is composed of at least one atomic index through one or more of addition, subtraction, or multiplication. In this embodiment, the polynomial ring can be a univariate polynomial ring or an n-variate polynomial ring.

[0052] When a computational index depends on n atomic indices and is obtained through addition and multiplication, the standard computational formula corresponding to the computational index is the quotient of two n-ary index polynomial rings:

[0053]

[0054] For example, the calculation formula corresponding to the indicator Q is Q=M1 / M2+M3. After the calculation formula is converted based on the rational function field, the converted standard calculation formula is Q=(M1+M2*M3) / M2.

[0055] S103: Determine the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula.

[0056] After obtaining a first standard calculation formula corresponding to the first data analysis indicator and a second standard calculation formula corresponding to the second data analysis indicator, the similarity between the first data analysis indicator and the second data analysis indicator is determined according to the first standard calculation formula and the second standard calculation formula.

[0057] Optionally, in response to the fact that the polynomial ring corresponding to the first standard calculation formula is the same as the polynomial ring corresponding to the second standard calculation formula, the first data analysis index and the second data analysis index are determined to be equivalent. That is, when the composition of the polynomial ring corresponding to the first standard calculation formula and the composition of the polynomial ring corresponding to the second standard calculation formula are completely consistent, the two indicators are determined to be equivalent. For example, the polynomial ring corresponding to the first standard calculation formula is a1*M1+a2*M2, and the polynomial ring corresponding to the second standard calculation formula is b1*M1+b2*M2, then the first data analysis index and the second data analysis index are determined to be equivalent. For another example, the polynomial ring corresponding to the first standard calculation formula is (a1*M1+a2*M2) / (M3+M4), and the polynomial ring corresponding to the second standard calculation formula is (b1*M1+b2*M2) / (c1*M3+M4), then the first data analysis index and the second data analysis index are determined to be equivalent.

[0058] Optionally, in response to the polynomial ring corresponding to the first standard calculation formula being different from the polynomial ring corresponding to the second standard calculation formula, it is determined that the first data analysis indicator and the second data analysis indicator are not equivalent. For example, the polynomial ring corresponding to the first standard calculation formula is a1*M1+a2*M2, and the polynomial ring corresponding to the second standard calculation formula is b1*M1 2 For another example, if the polynomial ring corresponding to the first standard calculation formula is a1*M1+a2*M2, and the polynomial ring corresponding to the second standard calculation formula is b1*M3+b2*M2, then the two indices are determined to be unequal.

[0059] When it is determined that the first data analysis indicator and the second data analysis indicator are not equivalent, it is necessary to further judge the similarity between the two, specifically: obtain the first index corresponding to each atomic index in each polynomial ring corresponding to the first standard calculation formula and the second index corresponding to each atomic index in each polynomial ring corresponding to the second standard calculation formula; determine the similarity between the first data analysis indicator and the second data analysis indicator based on the first index and the second index.

[0060] For example, there are three atomic indices M1 to M3. The polynomial ring corresponding to the first standard calculation formula is a1*M1+a2*M2, and the polynomial ring corresponding to the second standard calculation formula is b1*M3+b2*M2. Then the first index set is [1 1 0 3], indicating that the first standard calculation formula has a dependency index of 1 on atomic indices M1 and M2, respectively, and a dependency index of 0 on atomic indices M3. The second index set is [0 1 1], indicating that the second standard calculation formula has a dependency index of 1 on atomic indices M2 and M3, and a dependency index of 0 on atomic indices M1.

[0061] For another example, the first standard calculation formula is (M1 2 +M2 2 +M3 2 ) / (M1+M2+M3), then the first index set is [2 2 2; 11 1], where the first index 2 indicates that the dependence index of the numerator polynomial ring on the atomic index is 2; the second index 1 indicates that the dependence index of the denominator polynomial ring on the atomic index is 1. The second standard calculation formula is (M1+M3) / (M1 2 +M3 2 ), then the second index set is [1 0 1; 2 0 2], where 1 in the first group of indices indicates that the dependency index of the numerator polynomial ring on the atomic indices M1 and M3 is 1, and 0 in the first group of indices indicates that the dependency index of the numerator polynomial ring on the atomic indices M2 is 0; 2 in the second group of indices indicates that the dependency index of the denominator polynomial on the atomic indices M1 and M3 is 2, and 0 in the second group of indices indicates that the dependency index of the denominator polynomial ring on the atomic indices M2 is 0.

[0062] Determining the similarity between the first data analysis indicator and the second data analysis indicator based on the first index and the second index may include the following implementations:

[0063] One implementation method is: obtain a first vector set, which includes the minimum exponent corresponding to each atomic index in the polynomial ring; obtain a second vector set, which includes the maximum exponent corresponding to each atomic index in the polynomial ring; and calculate the similarity based on the first vector set and the second vector set.

[0064] For ease of understanding, the first vector set can be expressed as:

[0065]

[0066] The second vector set can be expressed as:

[0067]

[0068] Among them, kn (1) Indicates the dependence index of the molecular polynomial ring on the nth atomic index in the first standard calculation formula, tn (1) kn represents the dependence index of the denominator polynomial ring on the nth atomic index in the first standard calculation formula. (2) Indicates the dependence index of the molecular polynomial ring on the nth atomic index in the second standard calculation formula, tn (2) Indicates the dependence index of the denominator polynomial ring on the nth atomic index in the second standard calculation formula. max(kn (1) ,tn (1) ) represents the maximum dependence index on the nth atomic index in the first standard calculation formula, max(kn (2) ,tn (2) ) represents the maximum dependence index on the nth atomic index in the second standard calculation formula.

[0069] Then the first vector set min[max(kn (1) ,tn (1) ),max(kn (2) ,tn (2) )] represents the minimum dependency index of the two maximum dependency indices of the first standard calculation formula and the second standard calculation formula for the nth atomic index. (1) ,tn (1) ),max(kn (2) ,tn (2) )] represents the maximum dependence index of the two maximum dependence indices on the nth atomic index in the first standard calculation formula and the second standard calculation formula.

[0070] After determining the first vector set and the second vector set, the similarity between the first vector set and the second vector set can be determined using a cosine similarity calculation method. The cosine similarity calculation formula is as follows:

[0071]

[0072] Among them, Ai and Bi are the i-th elements in vector A and vector B respectively.

[0073] For example, atomic index vector M = {M1 M2 M3}, Q1 = (M1 2 +M2 2 +M32 ) / (M1+M2+M3), Q2=(M1+M3) / (M1 2 +M3 2 ), then the first vector set is [2 0 2], and the second vector set is [2 2 2], then the cosine similarity between Q1 and Q2 is:

[0074]

[0075] In this implementation, the similarity between two calculation indicators can be determined based on the dependency index on the atomic indicator.

[0076] Another implementation method is: when the structural form of the first standard calculation formula and the second standard calculation formula is the quotient of two polynomial rings, obtain a third vector set, which includes the first exponent corresponding to each atomic index in the denominator polynomial in the first standard calculation formula and the first exponent corresponding to each atomic index in the numerator polynomial; obtain a fourth vector set, which includes the second exponent corresponding to each atomic index in the denominator polynomial in the second standard calculation formula and the second exponent corresponding to each atomic index in the numerator polynomial; calculate the similarity based on the third vector set and the fourth vector set.

[0077] For ease of understanding, the third vector set can be expressed as:

[0078]

[0079] The fourth vector set can be expressed as:

[0080]

[0081] Among them, max(kn (1) ) represents the maximum dependence index of the molecular polynomial on the nth atomic index in the first standard calculation formula, max(tn (1) ) represents the maximum dependence index of the denominator polynomial on the nth atomic index in the first standard calculation formula, max(kn (2) ) represents the maximum dependence index of the molecular polynomial on the nth atomic index in the second standard calculation formula, max(tn (2) ) represents the maximum dependence index on the nth atomic index in the denominator polynomial in the second standard calculation formula.

[0082] After the first vector set and the second vector set are determined, the similarity between the first vector set and the second vector set may be determined using a cosine similarity calculation method.

[0083] For example, atomic index vector M = {M1 M2 M3}, Q1 = (M1 2 +M2 2 +M3 2) / (M1+M2+M3), Q2=(M1+M3) / (M1 2 +M3 2 ), then the third vector set is [2 -1 2 -1 2-1], and the fourth vector set is [1 -2 0 0 1 -2], then the cosine similarity between Q1 and Q2 is:

[0084]

[0085] In this implementation, not only the dependency index on the atomic indicator is considered, but also the position of the atomic indicator in the calculation formula (numerator or denominator). The opposite of the index corresponding to the atomic indicator in the denominator can be included in the vector for similarity calculation. In other words, the similarity between two indicators is determined not only based on the dependency index, but also based on the calculation logic.

[0086] As can be seen, the similarity between indicators can be determined by converting the calculation formulas corresponding to different indicators into standard calculation formulas, and then comparing the standard calculation formulas corresponding to different indicators. When two standard calculation formulas are completely consistent, the two indicators are considered equivalent. When there are differences between the two standard calculation formulas, the similarity between them can be determined by the dependence index of each atomic indicator in the standard calculation formula.

[0087] Optionally, in order to improve the cache hit rate, the atomic indicators or combinations that high-frequency query indicators depend on can also be pre-cached. Specifically, determine the third data analysis indicator in the indicator set whose query times are greater than the query times threshold; determine the atomic indicator on which the third data analysis indicator depends and the dependence strength on the atomic indicator; cache the atomic indicators or combinations whose dependence strength is greater than the dependence strength threshold. The combination includes multiple atomic indicators. The query times threshold and the dependence strength threshold can be determined according to the actual application situation, and this embodiment does not limit this. The dependence strength is the dependence index of the third data analysis indicator on the atomic indicator.

[0088] Based on the above method embodiment, the embodiment of the present application provides a data analysis indicator similarity judgment device, which will be described below with reference to the accompanying drawings.

[0089] See also Figure 2 , which is a schematic diagram of the structure of a data analysis indicator similarity judgment device provided in an embodiment of the present application, such as Figure 2 As shown, the apparatus 200 may include: an acquiring unit 201 , a converting unit 202 and a determining unit 203 .

[0090] An acquiring unit 201 is configured to acquire a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator, wherein the first calculation formula and the second calculation formula are each composed of at least one atomic indicator, and different atomic indicators in the at least one atomic indicator are independent of each other;

[0091] A conversion unit 202 is configured to convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula, wherein the first standard calculation formula and the second standard calculation formula have the same structural form;

[0092] The determining unit 203 is configured to determine the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula.

[0093] In a specific implementation, the conversion unit 202 is specifically used to convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula based on a rational function, and the structural form of the first standard calculation formula and the second standard calculation formula is a polynomial ring, and the polynomial ring is composed of at least one atomic indicator through one or more of addition, subtraction and multiplication; or, based on the rational function field, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula, and the structural form of the first standard calculation formula and the second standard calculation formula is the quotient of two polynomial rings, and each of the two polynomial rings is composed of at least one atomic indicator through one or more of addition, subtraction, and multiplication.

[0094] In a specific implementation, the determining unit 203 is specifically configured to determine that the first data analysis indicator and the second data analysis indicator are equivalent in response to the polynomial ring corresponding to the first standard calculation formula and the polynomial ring corresponding to the second standard calculation formula being the same;

[0095] In a specific implementation, the determination unit 203 is specifically used to obtain a first index corresponding to each atomic indicator in each polynomial ring corresponding to the first standard calculation formula and a second index corresponding to each atomic indicator in each polynomial ring corresponding to the second standard calculation formula in response to the fact that the polynomial ring corresponding to the first standard calculation formula is different from the polynomial ring corresponding to the second standard calculation formula; and determine the similarity between the first data analysis indicator and the second data analysis indicator based on the first index and the second index.

[0096] In a specific implementation, the determination unit 203 is specifically used to obtain a first vector set, where the first vector set includes the minimum exponent corresponding to each atomic index in the polynomial ring, and the minimum exponent is one of the first exponent or the second exponent; obtain a second vector set, where the second vector set includes the maximum exponent corresponding to each atomic index in the polynomial, and the maximum exponent is the other of the first exponent or the second exponent; and calculate the similarity based on the first vector set and the second vector set.

[0097] In a specific implementation, the determination unit 203 is specifically used to obtain a third vector set when the structural form of the first standard calculation formula and the second standard calculation formula is the quotient of two polynomial rings, the third vector set including the first exponent corresponding to each atomic index in the denominator polynomial in the first standard calculation formula and the first exponent corresponding to each atomic index in the numerator polynomial; obtain a fourth vector set, the fourth vector set including the second exponent corresponding to each atomic index in the denominator polynomial in the second standard calculation formula and the second exponent corresponding to each atomic index in the numerator polynomial; calculate the similarity based on the third vector set and the fourth vector set.

[0098] In a specific implementation, the apparatus further includes: a cache unit;

[0099] The determining unit 203 is further configured to determine a third data analysis indicator in the indicator set whose query times are greater than a query times threshold;

[0100] The determining unit 203 is further configured to determine the atomic indicators on which the third data analysis indicator depends and the strength of the dependence on the atomic indicators;

[0101] The cache unit is used to cache the atomic indicators or combinations whose dependency strength is greater than the dependency strength threshold, where the combination includes multiple atomic indicators.

[0102] In a specific implementation, the first data analysis indicator and the second data analysis indicator are derived indicators or calculated indicators. The derived indicator refers to an indicator that takes different values ​​under different given conditions, and the calculated indicator refers to an indicator obtained by calculation based on one or more atomic indicators.

[0103] In a specific implementation manner, the first data analysis indicator is a newly added indicator, and the second data analysis indicator is an existing indicator; or the first data analysis indicator and the second data analysis indicator are both existing indicators.

[0104] It should be noted that the implementation of each unit in this embodiment can refer to the relevant description in the above method embodiment, and this embodiment will not be repeated here.

[0105] See also Figure 3 , which shows a schematic structural diagram of an electronic device 300 suitable for implementing an embodiment of the present application. The terminal device in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (portable Android devices), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs (televisions) and desktop computers. Figure 3 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0106] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. Various programs and data required for the operation of the electronic device 300 are also stored in the RAM 303. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0107] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0108] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of the embodiment of the present application are performed.

[0109] The electronic device provided in the embodiment of the present application and the method provided in the above embodiment belong to the same inventive concept. For technical details not fully described in this embodiment, please refer to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0110] An embodiment of the present application provides a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any of the above embodiments is implemented.

[0111] It should be noted that the computer-readable medium mentioned above in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0112] In some embodiments, the client and server can communicate using any currently known or future developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0113] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0114] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the data analysis indicator similarity judgment method.

[0115] Computer program code for performing the operations of the present application may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0117] The units involved in the embodiments described in this application may be implemented by software or hardware. In some cases, the name of a unit / module does not constitute a limitation of the unit itself. For example, a voice data acquisition module may also be described as a "data acquisition module."

[0118] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0119] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared or semiconductor system, device or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium can include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0120] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the systems or devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0121] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0122] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0123] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0124] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining similarity of data analysis indicators, characterized in that: The method comprises: Obtaining a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator, where the first calculation formula and the second calculation formula are each composed of at least one atomic indicator, different atomic indicators in the at least one atomic indicator are independent of each other and cannot be converted into each other, the first data analysis indicator and the second data analysis indicator are used to analyze advertising delivery effects, the first data analysis indicator is one of an ad click-through rate or an ad conversion rate, and the second data analysis indicator is the other of the ad click-through rate or the ad conversion rate; Based on a rational function, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula, the first standard calculation formula and the second standard calculation formula are structurally in the form of a polynomial ring, and the polynomial ring is composed of at least one atomic index through one or more of addition, subtraction, and multiplication; or based on a rational function field, the first calculation formula is converted into a first standard calculation formula and the second calculation formula is converted into a second standard calculation formula, the first standard calculation formula and the second standard calculation formula are structurally in the form of a quotient of two polynomial rings, and each of the two polynomial rings is composed of at least one atomic index through one or more of addition, subtraction, and multiplication; The similarity between the first data analysis indicator and the second data analysis indicator is determined according to the first standard calculation formula and the second standard calculation formula.

2. The method according to claim 1, characterized in that The determining the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula includes: In response to the polynomial ring corresponding to the first standard calculation formula being the same as the polynomial ring corresponding to the second standard calculation formula, it is determined that the first data analysis indicator and the second data analysis indicator are equivalent.

3. The method according to claim 1 or 2, characterized in that The determining the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula includes: In response to the polynomial ring corresponding to the first standard calculation formula being different from the polynomial ring corresponding to the second standard calculation formula, obtaining a first exponent corresponding to each atomic index in each polynomial ring corresponding to the first standard calculation formula and a second exponent corresponding to each atomic index in each polynomial ring corresponding to the second standard calculation formula; The similarity between the first data analysis indicator and the second data analysis indicator is determined according to the first index and the second index.

4. The method according to claim 3, characterized in that Determining the similarity between the first data analysis indicator and the second data analysis indicator according to the first index and the second index includes: Obtain a first vector set, where the first vector set includes minimum exponents corresponding to atomic indices in the polynomial ring, where the minimum exponent is one of the first exponent and the second exponent; Obtain a second vector set, where the second vector set includes maximum exponents corresponding to atomic indices in the polynomial, where the maximum exponent is the other of the first exponent and the second exponent; Similarity is calculated based on the first vector set and the second vector set.

5. The method according to claim 1, wherein The first standard calculation formula and the second standard calculation formula are structural forms of the quotient of two polynomial rings, and determining the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula includes: Obtaining a third vector set, the third vector set including first exponents corresponding to each atomic index in the denominator polynomial and first exponents corresponding to each atomic index in the numerator polynomial in the first standard calculation formula; Obtaining a fourth vector set, the fourth vector set including the second exponent corresponding to each atomic index in the denominator polynomial and the second exponent corresponding to each atomic index in the numerator polynomial in the second standard calculation formula; Similarity is calculated based on the third vector set and the fourth vector set.

6. The method according to claim 1, wherein The method further comprises: Determine a third data analysis indicator in the indicator set, wherein the query number is greater than a query number threshold, wherein the third data analysis indicator is used to analyze advertising delivery efficiency; Determining the atomic indicators on which the third data analysis indicator depends and the intensity of the dependence on the atomic indicators; The atomic indicators or combinations whose dependency strength is greater than a dependency strength threshold are cached, where the combination includes multiple atomic indicators.

7. The method according to claim 1, characterized in that The first data analysis indicator and the second data analysis indicator are derived indicators or calculated indicators. The derived indicator refers to an indicator that takes different values ​​under different given conditions, and the calculated indicator refers to an indicator obtained by calculation based on one or more atomic indicators.

8. The method according to claim 1, characterized in that The first data analysis indicator is a newly added indicator, and the second data analysis indicator is an existing indicator; or the first data analysis indicator and the second data analysis indicator are both existing indicators.

9. A data analysis indicator similarity judgment device, characterized in that: The device comprises: an acquisition unit, configured to acquire a first calculation formula corresponding to a first data analysis indicator and a second calculation formula corresponding to a second data analysis indicator, wherein the first calculation formula and the second calculation formula are respectively composed of at least one atomic indicator, different atomic indicators in the at least one atomic indicator are independent of each other and cannot be converted into each other, the first data analysis indicator and the second data analysis indicator are used to analyze the effectiveness of advertising delivery, the first data analysis indicator is one of an advertisement click-through rate or an advertisement conversion rate, and the second data analysis indicator is the other of the advertisement click-through rate or the advertisement conversion rate; a conversion unit, configured to convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula based on a rational function, wherein the first standard calculation formula and the second standard calculation formula are structurally polynomial rings, wherein the polynomial rings are constructed by at least one atomic index through one or more of addition, subtraction, and multiplication; or, based on a rational function field, convert the first calculation formula into a first standard calculation formula and convert the second calculation formula into a second standard calculation formula, wherein the first standard calculation formula and the second standard calculation formula are structurally the quotient of two polynomial rings, wherein each of the two polynomial rings is constructed by at least one atomic index through one or more of addition, subtraction, and multiplication; A determining unit is configured to determine the similarity between the first data analysis indicator and the second data analysis indicator according to the first standard calculation formula and the second standard calculation formula.

10. An electronic device, characterized in that: The device includes: a processor and a memory; The memory is used to store instructions or computer programs; The processor is configured to execute the instructions or computer program in the memory, so that the electronic device executes the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on a device, the device is caused to execute the method according to any one of claims 1 to 8.

12. A computer program product, characterized in that The computer program product comprises a computer program / instruction, and when the computer program / instruction is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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