Search method and apparatus, data processing method and apparatus

Abstract

The present disclosure provides a search method and apparatus, relating to the field of big data technology. The specific implementation solution is as follows: obtain multiple data processing conditions corresponding to the same data processing target from a first target memory; extract corresponding measurement samples from a second target memory based on the data processing conditions; use a target processor to calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target, to obtain a conditional result sequence; combine the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence; determine an application condition set based on the measurement results corresponding to the intersection of the measurement samples of the conditional group sequence, and store the application condition set in the first target memory. This implementation manner improves the search efficiency of application conditions.

Description

Technical Field

[0001] The present disclosure relates to the technical field of data processing, specifically to technical fields such as big data, and particularly relates to a search method and apparatus, a data processing method and apparatus, an electronic device, a computer-readable medium, and a computer program product. Background Art

[0002] For the collection of data rules in different industries, existing solutions generally rely on decision tree models, where the nodes and node splitting paths of the decision tree are used as the application rules output. However, there are pre-dependencies between variables in the application rules generated by the decision tree model, and it is not easy to find the best rule combination. Summary of the Invention

[0003] A search method and apparatus, a data processing method and apparatus, an electronic device, a computer-readable medium, and a computer program product are provided.

[0004] According to a first aspect, a search method is provided. The method includes: obtaining a plurality of data processing conditions corresponding to the same data processing target from a first target memory; extracting corresponding measurement samples from a second target memory based on the data processing conditions; using a target processor to calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target, to obtain a conditional result sequence, where the conditional result sequence includes: a plurality of measurement results and the data processing conditions associated with each measurement result; combining the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence; and determining an application condition set based on the measurement results corresponding to the intersection of the measurement samples in the conditional group sequence, and storing the application condition set in the first target memory.

[0005] According to a second aspect, a data processing method is provided. The method includes: obtaining data to be measured; using the application condition sets corresponding to a plurality of data processing targets obtained by the method described in any implementation manner of the first aspect to detect whether the data to be measured meets at least one of the plurality of data processing targets; and in response to the measured data meeting at least one data processing target, determining the data to be measured as target data.

[0006] According to a third aspect, a search device is provided, the device comprising: a condition acquisition unit configured to acquire a plurality of data processing conditions corresponding to the same data processing target from a first target memory; a sample determination unit configured to extract corresponding measurement samples from a second target memory based on the data processing conditions; a calculation unit configured to use a target processor to calculate and sort the measurement results corresponding to all data processing conditions for the data processing target based on the measurement samples and the data processing target, obtaining a condition result sequence, the condition result sequence including: a plurality of measurement results and the data processing conditions associated with each measurement result; a combination unit configured to combine the data processing conditions corresponding to the measurement results in the condition result sequence, obtaining a condition group sequence; a condition determination unit configured to determine an application condition set based on the measurement results corresponding to the intersection of the measurement samples in the condition group sequence, and store the application condition set in the first target memory.

[0007] According to a fourth aspect, a data processing device is provided, the device comprising: a data acquisition unit configured to acquire data to be measured; a detection unit configured to use the application condition sets corresponding to a plurality of data processing targets obtained by the device described in any implementation manner of the third aspect to detect whether the data to be measured satisfies at least one of the plurality of data processing targets; a data determination unit configured to, in response to detecting that the data to be measured satisfies at least one data processing target, determine the data to be measured as target data.

[0008] According to a fifth aspect, an electronic device is provided, the electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in any implementation manner of the first aspect or the second aspect.

[0009] According to a sixth aspect, a non-transitory computer-readable storage medium storing computer instructions is provided, the computer instructions being used to cause a computer to execute the method described in any implementation manner of the first aspect or the second aspect.

[0010] According to a seventh aspect, a computer program product is provided, including a computer program which, when executed by a processor, implements the method described in any implementation manner of the first aspect or the second aspect.

[0011] The search method and device provided by the embodiments of the present disclosure first obtain a plurality of data processing conditions corresponding to the same data processing target from a first target memory; secondly, based on the data processing conditions, extract corresponding measurement samples from a second target memory; thirdly, use a target processor to calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target to obtain a conditional result sequence; fourthly, combine the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence; finally, determine an application condition set based on the measurement results corresponding to the intersection of the measurement samples in the conditional group sequence and store the application condition set in the first target memory. Thus, based on the sorting of the measurement results of all data processing conditions, an application condition set corresponding thereto is determined based on the measurement results corresponding to the intersection of the measurement samples. On the basis of meeting the data processing target, each data processing condition in the obtained application condition set can be free from the influence of variable dependencies, and the obtained application condition set can maximize the requirements of the data processing target, improving the obtaining efficiency of the application condition set and ensuring the reliability of the search for the application condition set; and different types of data are stored in different memories respectively, saving storage space, reducing storage consumption, and ensuring the standardization of data storage; using a target processor to calculate and sort different conditional results improves the data processing efficiency.

[0012] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings are used to better understand the solution and do not constitute a limitation to the present disclosure. Among them:

[0014] Figure 1 is a flowchart according to an embodiment of the search method of the present disclosure;

[0015] Figure 2 is a schematic structural diagram of searching for an application condition set in an embodiment of the present disclosure;

[0016] Figure 3 is a flowchart according to an embodiment of the data processing method of the present disclosure;

[0017] Figure 4 is a schematic structural diagram according to an embodiment of the search device of the present disclosure;

[0018] Figure 5 is a schematic structural diagram according to an embodiment of the data processing device of the present disclosure;

[0019] Figure 6It is a block diagram of an electronic device for implementing the search method and data processing method of the embodiments of the present disclosure. Detailed implementation manners

[0020] The following will describe exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following.

[0021] In this embodiment, "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features.

[0022] Figure 1 Flow 100 according to an embodiment of the search method of the present disclosure is shown. The above search method includes the following steps:

[0023] Step 101, obtain a plurality of data processing conditions corresponding to the same data processing target from a first target memory.

[0024] In this embodiment, the first target memory is used to store various different types of data processing conditions. For example, the range of an individual's appearance, the range of an individual's age, etc. The data processing conditions may include rule variables and measurement indicators corresponding to the rule variables. Different measurement rules may include different rule variables or different measurement indicators. For example, two data processing conditions of a > 10 and a > 20, where a is the rule variable of the two data processing conditions, and 10 and 20 are different measurement indicators of the rule variable a respectively. It should be noted that the rule variables in the data processing conditions may be continuous variables or discrete variables.

[0025] The above obtaining a plurality of data processing conditions corresponding to the same data processing target includes: obtaining an initial rule, and the initial rule may include a rule variable and a measurement indicator corresponding to the rule variable; in response to the rule variable in the initial rule being a continuous variable, perform equal-frequency binning processing on the continuous variable to obtain a data processing condition. The above equal-frequency binning means: evenly divide the observation points of the rule variable into N equal parts, and each part contains the same number of observation points.

[0026] Optionally, the above obtaining a plurality of data processing conditions corresponding to the same data processing target may further include: in response to the rule variable in the initial rule being a discrete variable, directly use the initial rule as the data processing condition.

[0027] In this embodiment, the data processing objective is the objective that all data processing conditions need to achieve together. The data processing objective can be at least one numerical value, at least one rule, or a formula, where the formula is composed of addition, subtraction, multiplication, and division. For example, for the formula for the expected users, it can be: the total loan balance of overdue users / the total loan amount. In this embodiment, in order to obtain the best application conditions for the corresponding data processing objective, it is necessary to first obtain a plurality of data processing conditions corresponding to the data processing objective. For example, the data processing objective is the group of people with the highest happiness index, and the data processing conditions corresponding to this data processing objective include: adults over thirty years old, employees working in companies on the Fortune Global 500 list.

[0028] Step 102: Based on the data processing conditions, extract the corresponding measurement samples from the second target memory.

[0029] In this embodiment, the second target memory is used to store various different types of data that meet various data processing conditions. For example, individual behavior data, individual attribute data, etc. There are multiple sub-regions divided in the second target memory, and each sub-region corresponds to a different type of measurement sample. The measurement sample is a sample instance for measuring the data processing objective, and the measurement sample includes measurement variables and the values of the measurement variables. Among them, the measurement variable is a variable for measuring different aspects of the data processing objective. For example, if the measurement target is: to find people with high wealth, then the measurement variables of the measurement sample include: income, deposit, etc. Correspondingly, the values of the measurement variables are: 50,000, 2,000,000, etc. In this embodiment, when the data processing objective is a formula, the measurement variable is the variable in the formula of the data processing objective; further, the measurement variable is also a variable related to the rule variable in the data processing conditions. For example, the rule variables corresponding to the same data processing objective (to find people with high wealth) are: age, gender, years of service, occupation, and the measurement variables are: income, deposit, that is, only when the rule variables exist in advance can the measurement variables of the measurement sample be obtained accordingly.

[0030] In this embodiment, in order to achieve the data processing objective, it is possible to obtain the labeled measurement samples from the sample library, thus building a bridge to the data processing objective for finding the best data processing conditions, and the labeled completed measurement samples obtained from the sample library need to correspond to the data processing objective.

[0031] In this embodiment, the measurement sample is a rule for measuring the data processing objective set according to the data processing conditions, and the obtained data processing conditions correspond to the measurement sample. After the quantity and content of the obtained data processing conditions change, the measurement variables and the values of the measurement variables in the corresponding measurement sample also change accordingly.

[0032] Step 103: Using the target processor, calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target, to obtain a conditional result sequence.

[0033] In this embodiment, the target processor is a processor that can calculate a large amount of data. Based on the current measurement samples, the target processor can calculate the measurement results that meet the data processing conditions. The measurement samples correspond to the data processing conditions. For different data processing conditions, the values obtained by the measurement variables in the measurement samples are different. For example, the measurement target is to find people with high wealth, and the measurement variables of the measurement samples include income and deposits. For the data processing condition "working years > 5 years", through the annotation information in the measurement samples (people with different working years have different incomes), the income and deposit amounts corresponding to the data processing condition "working years > 5 years" can be calculated. The calculated income and storage size are the measurement results of "working years > 5 years".

[0034] In this embodiment, multiple data processing conditions are obtained in step 101. Therefore, multiple measurement results can be obtained for multiple data processing conditions (each data processing condition corresponds to one measurement result). Based on the data processing target, the multiple measurement results are sorted and associated to obtain a conditional result sequence.

[0035] In this embodiment, the conditional result sequence includes multiple measurement results and the data processing conditions associated with each measurement result. Among them, the multiple measurement results are the measurement results of each data processing condition, and each measurement result has an association relationship with the data processing condition. This association relationship is the relationship between each measurement result and the data processing condition. From this association relationship and each measurement result in the conditional result sequence, the data processing condition associated with the measurement result can be determined.

[0036] In this embodiment, the measurement results can be sorted based on the data processing target requirements. For example, if the data processing target is "the group of people with the highest happiness index", that is, the data processing target includes maximizing the measurement results, then the measurement results are sorted from high to low.

[0037] Step 104: Combine the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence.

[0038] In this embodiment, the conditional group sequence includes at least one conditional group, and each conditional group is obtained by combining multiple data processing conditions. As Figure 2 shown, X1 > 4, X2 < 10, and X3 < 9 are three different data processing conditions corresponding to the same data processing target. In Figure 2For each data processing condition in [condition], a measurement result can be calculated through the measured samples. Combining X1 > 4, X2 < 10, and X3 < 9 gives X1 > 4 && X2 < 10 && X3 < 9. This combination X1 > 4 && X2 < 10 && X3 < 9 is a type of condition group, and this condition group correspondingly has the measured samples of this condition group. Through the measured samples of this condition group, the measurement result of this condition group can be calculated. For example Figure 2 the measurement result in [result] is 98.

[0039] In this embodiment, the measurement results in the condition result sequence are sorted according to the sorting requirements of the data processing target. Therefore, when combining different data processing conditions, the combination can be carried out in the order of each measurement result in the condition result sequence. The data processing conditions corresponding to the measurement results in the above combined condition result sequence are obtained. The condition group sequence includes: based on the sorting result of the measurement results, determining the data processing conditions corresponding to each measurement result and arranged in order, and combining any two adjacent data processing conditions to obtain a condition group sequence formed by multiple condition groups.

[0040] Optionally, the condition group in the condition group sequence can also be a data processing condition, and this data processing condition is associated with the measurement result corresponding to this data processing condition.

[0041] Step 105: Determine the application condition set based on the measurement result corresponding to the intersection of the measured samples of the condition group sequence, and store the application condition set in the first target memory.

[0042] In this embodiment, the condition group sequence includes at least one condition group, and each condition group is obtained from one or more data processing conditions. When the condition group in the condition group sequence is a data processing condition, the intersection of the measured samples is the measured sample of this data processing condition; when the condition group in the condition group sequence is a combination of multiple data processing conditions, the intersection of the measured samples is the common measured sample of the multiple data processing conditions.

[0043] In this embodiment, the intersection of the measured samples of the condition group sequence can be the intersection of the measured samples of the condition groups. For example, the measured sample corresponding to the value 1 of a condition group in the condition group sequence is: wh t, and the measured sample corresponding to the value 2 of another condition group in the condition group sequence is: h t d. Then the intersection of the measured samples of the two condition groups is: h t. Calculate the measurement results of the data processing conditions in the two condition groups through the intersection of the measured samples, and detect whether the measurement results meet the data processing target. In response to the measurement results meeting the data processing target, retain the data processing conditions of the two condition groups to obtain the application function rule set.

[0044] If the measurement results of the data processing conditions in the two condition groups do not meet the data processing objective, it is determined that the data processing conditions of the two condition groups do not meet the requirements of the data processing objective, and the data processing conditions of the two condition groups are no longer retained. In this embodiment, all the retained data processing conditions are sorted according to the requirements of the data processing objective (such as maximizing or minimizing the measurement result), and the first set number (which is the number of data processing conditions required for the data processing objective, and the set number can be set based on the objective requirements) of data processing conditions are intercepted according to the required number of rules as the application condition group, so as to obtain the optimal rule set that meets the data processing objective.

[0045] Optionally, the intersection of the measurement samples of the condition group sequence can also be the intersection of the measurement samples corresponding to the data processing conditions in each condition group.

[0046] In this embodiment, the application condition set includes at least one application condition, and each application condition includes one or more data processing conditions. When the application condition is multiple data processing conditions, the application condition can be a condition group.

[0047] In this embodiment, the application condition set is the data processing conditions selected from the multiple data processing conditions corresponding to the data processing objective, and the data screening requirements of the data processing objective can be maximally covered through the application condition set. When the data processing objectives are different, the application conditions are correspondingly different. Storing the application condition sets of different data processing objectives in the first target memory can facilitate the selection of the application conditions of different data processing objectives from the first target memory.

[0048] The search method provided by the embodiments of the present disclosure first obtains multiple data processing conditions corresponding to the same data processing target from a first target memory; secondly, based on the data processing conditions, extracts corresponding measurement samples from a second target memory; thirdly, uses a target processor to calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples, obtaining a conditional result sequence; fourthly, combines the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence; finally, determines an application condition set based on the measurement results corresponding to the intersection of the measurement samples in the conditional group sequence and stores the application condition set in the first target memory. Thus, based on the sorting of the measurement results of all data processing conditions, an application condition set is determined based on the measurement results corresponding to the intersection of the measurement samples. On the basis of meeting the data processing target, the various data processing conditions in the obtained application condition set are not affected by variable dependencies, and the obtained application condition set can maximize the requirements of the data processing target, improving the efficiency of obtaining the optimal application condition set and ensuring the reliability of the search for the application condition set; and different types of data are stored in different memories respectively, saving storage space, reducing storage consumption, and ensuring the standardization of data storage; the target processor is used to calculate and sort different conditional results, improving the efficiency of data processing.

[0049] In some alternative implementation manners of this embodiment, the above data target is to determine data belonging to a predetermined group; the method further includes: obtaining data of multiple different individuals from the second target memory, searching for the data of multiple different individuals using the application condition set to obtain data corresponding to the predetermined group, and storing the data of the predetermined group in the second target memory.

[0050] In this embodiment, the data belonging to the predetermined group may correspond to the behavior data, attribute data, and related data of the predetermined group. For example, if the predetermined group is high school math teachers in a certain place, the data of the predetermined group may be the age values of high school math teachers, the activity areas of high school math teachers, etc. When the data target is to determine data belonging to high school math teachers, then obtain the "behavior data and attribute data of Person A1 and Person B1" from the second target memory, and screen the "behavior data and attribute data of Person A1 and Person B1" through the application condition set corresponding to the corresponding data target (such as teachers over 25 years old and active in Area C) to obtain data that meets the data of "high school math teachers", and this data is the data of the predetermined group.

[0051] In this embodiment, after obtaining the data corresponding to the predetermined group, the data of the predetermined group can be transformed to obtain measurement samples that meet the predetermined group, and the measurement samples can continue to be used to obtain an application condition set for other data processing targets.

[0052] The method for obtaining data corresponding to a data target provided by this alternative implementation manner, when the data target is determined to be data belonging to a predetermined group, obtains data of different individuals from a second target memory, and searches the data of different individuals through an application condition set, so as to screen out data of the predetermined group that meet the application condition set, and the data of the predetermined group that meet the application condition set is the data that meets the data target. Storing the data of the predetermined group into the second target memory provides a reliable implementation manner for searching for data that achieves a data processing target.

[0053] In the embodiments of the present disclosure, the data processing target is used to reflect various target requirements, such as maximizing the measurement result, minimizing the measurement result, etc. Based on different measurement requirements of the data processing target, the sorting of the measurement results of the data processing conditions can be sorted from large to small or from small to large. In some alternative implementation manners of this implementation, the above-mentioned target processor calculates and sorts the measurement results of all data processing conditions corresponding to the data processing target based on the measurement sample and the data processing target to obtain a condition result sequence, including: when the data processing target includes maximizing the measurement result, the target processor calculates the measurement results of all data processing conditions corresponding to the data processing target; sorts all the measurement results from large to small in sequence to obtain a condition result sequence.

[0054] As Figure 2 shown, the data processing target includes maximizing the measurement result, that is, the larger the value of the measurement result, the closer it is to the data processing target. Therefore, sort the measurement results of all data processing conditions from large to small. In Figure 2 the measurement results are 27, 16, and 13 in sequence. In Figure 2 each measurement result in the condition result sequence is sorted according to the size of the measurement result, and each measurement result is associated with a data processing condition.

[0055] The method for obtaining a condition result sequence provided by this alternative implementation manner, when the data processing target includes maximizing the measurement result, sorts the measurement results corresponding to all data processing conditions from large to small, which can make the unprocessed data conditions in the obtained condition result sequence better meet the data processing target requirements, and improves the reliability of obtaining the condition result sequence.

[0056] In some other alternative implementation manners of this embodiment, the above-mentioned calculation and sorting of the measurement results of all data processing conditions corresponding to the data processing target based on the measurement sample and the data processing target to obtain a condition result sequence includes: when the data processing target includes minimizing the measurement result, the target processor calculates the measurement results of all data processing conditions corresponding to the data processing target; sorts all the measurement results from small to large in sequence to obtain a condition result sequence.

[0057] In this alternative implementation, the data processing objective includes minimizing the measurement result, that is, the smaller the value of the measurement result, the closer it is to the data processing objective.

[0058] The method for obtaining the conditional result sequence provided in this alternative implementation, when the data processing objective includes minimizing the measurement result, sorts all the measurement results corresponding to the data processing conditions from small to large, which can make the data processing conditions in the obtained conditional result sequence better meet the requirements of the data processing objective and improve the reliability of obtaining the conditional result sequence.

[0059] In some alternative implementations of this embodiment, the data processing conditions corresponding to the measurement results in the above combined conditional result sequence are combined to obtain a conditional group sequence, including: for the first data processing condition corresponding to the first measurement result in the conditional result sequence, a set number of data processing conditions after the first data processing condition are selected; the first data processing condition is combined with the selected data processing conditions, and the selected data processing conditions are combined to obtain a conditional group sequence including multiple conditional groups.

[0060] As Figure 2 shown, "X1 > 4" is the first data processing condition, and the first data processing condition and 2 data processing conditions "X2 < 10" and "X3 < 9" after the first data processing condition are selected for combination to obtain two conditional groups "X1 > 4 && X2 < 10 && X3 < 9" and "X1 > 4 && X2 < 10", and the selected data processing conditions are combined to obtain the conditional group "X3 < 9 && X2 < 10". It should be noted that each conditional group has a corresponding measurement sample, and each conditional group has its own measurement result. As Figure 2 shown, the measurement result of the conditional group "X1 > 4 && X2 < 10 && X3 < 9" is 98, the measurement result of the conditional group "X1 > 4 && X2 < 10" is 66, and the measurement result of the conditional group "X3 < 9 && X2 < 10" is 43.

[0061] In this alternative implementation, combining the first data processing condition with the selected data processing conditions may include: combining all the data processing conditions in the first data processing condition and the selected data processing conditions together to obtain a conditional group, or combining the first data processing condition with one or more data processing conditions in the selected data processing conditions to obtain multiple conditional groups.

[0062] In this alternative implementation manner, the combination of the selected data processing conditions described above includes: combining at least two of the selected data processing conditions to obtain multiple condition groups. It should be noted that the measurement samples of the condition groups obtained after combining at least two data processing conditions may be the same as or different from those of the original two data processing condition groups. Therefore, the measurement result of the condition group is not related to the sum of the measurement results of the two data processing conditions.

[0063] The method for obtaining a condition group sequence provided by this alternative implementation manner selects a set number of data processing conditions after the first data processing condition, combines the first data processing condition with the selected data processing conditions, and combines the selected data processing conditions to obtain a condition group sequence including multiple condition groups, providing an alternative implementation manner for the obtaining of the condition group sequence.

[0064] Optionally, combining the data processing conditions corresponding to the measurement results in the above combination condition result sequence to obtain a condition group sequence includes: for the first data processing condition corresponding to the first measurement result in the condition result sequence, selecting a set number of data processing conditions after the first data processing condition; combining the first data processing condition with one or more of the selected data processing conditions to obtain a condition group sequence including multiple condition groups.

[0065] Optionally, combining the data processing conditions corresponding to the measurement results in the above combination condition result sequence to obtain a condition group sequence may further include: in response to the existence of a second data processing condition after the selected data processing conditions, selecting a set number of data processing conditions after the second data processing condition; combining the second data processing condition with the set number of data processing conditions after the second data processing condition, and combining the set number of data processing conditions after the second data processing condition to obtain a condition group sequence.

[0066] In this embodiment, a condition group may be a single data processing condition or a combination of multiple data processing conditions. In some alternative implementation manners of this embodiment, combining the data processing conditions corresponding to the measurement results in the above combination condition result sequence to obtain a condition group sequence further includes: taking at least one of all the data processing conditions as a condition group and adding it to the condition group sequence.

[0067] As Figure 2 in, adding the data processing condition "X1 > 4" to the condition group sequence as a condition group in the condition group sequence can effectively enrich the number of condition groups in the condition group sequence.

[0068] In this alternative implementation, at least one of all the data processing conditions can be any one or more of the data processing conditions corresponding to the same data processing objective, or can also be all the data processing conditions corresponding to the same data processing objective.

[0069] The method for obtaining the condition group sequence provided by this alternative implementation adds at least one of all the data processing conditions to the condition group sequence, improving the data diversity of the condition group sequence.

[0070] In some alternative implementations of this embodiment, determining the application condition set based on the measurement result corresponding to the intersection of the measurement samples of the condition group sequence includes: for each condition group in the condition group sequence, taking the intersection of the measurement samples corresponding to the data processing conditions in the condition group to obtain the intersection of the measurement samples of the condition group; calculating the measurement result of the data processing objective corresponding to the intersection of the measurement samples; in response to the measurement result of the intersection meeting the data processing objective, determining this condition group as an application condition; sorting all the application conditions and selecting a set number of application conditions from the sorted application conditions to obtain the application condition set.

[0071] In this alternative implementation, taking the intersection of the measurement samples corresponding to the data processing conditions in the condition group to obtain the intersection of the measurement samples of the condition group includes: obtaining the measurement samples of each data processing condition in the condition group and taking the intersection of the obtained measurement samples of the condition group to obtain the intersection of the measurement samples of the condition group. For example, the condition group includes: data processing condition 1 and data processing condition 2, the measurement samples of data processing condition 1 are e, t, g; the measurement samples of data processing condition 2 are: t, k, l, then the intersection of the measurement samples of the condition group is: t.

[0072] In this alternative implementation, the application condition includes one condition group or multiple condition groups, and each condition group includes one data processing condition or multiple data processing conditions. When the measurement result of the intersection of the measurement samples of the condition group obtained by combining the data processing conditions meets the data processing objective, determine the condition group obtained by combining the data processing conditions as the application condition that can be used to measure whether different data meets the data processing objective.

[0073] In this alternative implementation, sorting the application conditions based on the measurement result corresponding to the application condition and the data processing objective. Specifically, sorting all the application conditions includes: in response to the data processing objective including maximizing the measurement result, sorting the measurement results corresponding to all the application conditions from largest to smallest to obtain the sorted measurement results; based on the sorted measurement results, obtaining the sorted application conditions.

[0074] In this alternative implementation, each application condition corresponds to a measurement result, and the sorting of the measurement results is the sorting of the application conditions.

[0075] Optionally, the sorting of all the application conditions includes: in response to the data processing objective including minimizing the measurement result, sorting the measurement results corresponding to all the application conditions from smallest to largest to obtain the sorted measurement results; based on the sorted measurement results, obtaining the sorted application conditions.

[0076] In this alternative implementation, the measurement results corresponding to the respective application conditions are calculated based on the measurement samples of the respective application conditions, and the measurement samples of the respective application conditions are obtained by taking the intersection of the measurement samples of the condition groups.

[0077] The method for determining the application condition set provided by this alternative implementation determines the application conditions through the measurement results of the intersection of the measurement samples corresponding to the data processing conditions, sorts all the application conditions, and obtains the application condition set. Thus, in the process of obtaining the application condition set, only through the calculation of the measurement results of the measurement samples, the best condition combination can be found, improving the efficiency and quality of obtaining the condition combination.

[0078] Figure 3 The flowchart 300 of an embodiment of the data processing method of the present disclosure is shown. The above data processing method includes the following steps:

[0079] Step 301, obtain the data to be measured.

[0080] In this embodiment, the data to be measured is the data to be detected for the application condition set. The data in the data to be measured may or may not meet the data processing objective. By detecting the application condition set, it can be determined whether the data to be measured meets the data processing objective.

[0081] In this embodiment, the execution subject of the data processing method can obtain the data to be measured in various ways. For example, the execution subject can obtain the data to be measured stored therein from the database server through a wired connection method or a wireless connection method. For another example, the execution subject can also receive the data to be measured collected in real time by the terminal or other devices. For another example, the execution subject can also directly obtain the data to be measured stored by the user in the second target memory.

[0082] In this embodiment, the specific content of the data to be measured is different according to the different fields corresponding to the application condition set. For example, when generating an intelligent report, the data to be measured can be the initial data before the generation of the intelligent report; in the field of individual classification, the data to be measured can be the behavior data corresponding to various different types of individuals; in the field of risk individual division, the data to be measured can be the corresponding risk individuals or reliable individuals.

[0083] In step 302, an application condition set corresponding to multiple data processing objectives obtained by a search method is used to detect whether the data to be measured satisfies at least one of the multiple data processing objectives.

[0084] In this embodiment, the execution entity may match the data to be measured obtained in step 301 with each application condition in the application condition set. In response to detecting that the data to be measured satisfies all the application conditions in the application condition set of at least one of the multiple data processing objectives, it is determined that the data to be measured satisfies at least one data processing objective.

[0085] In response to detecting that the data to be measured does not satisfy all the application conditions in the condition set of any one of the multiple data processing objectives, it is determined that the data to be measured does not satisfy the data processing objective.

[0086] In this embodiment, the application condition set may be generated by using the method described in the foregoing Figure 1 embodiment. The specific generation process may refer to the relevant description in the Figure 1 embodiment and will not be elaborated here.

[0087] It should be noted that the data processing method in this embodiment can be used to test the application condition sets generated in the foregoing embodiments. Furthermore, the application conditions in the application condition set can be continuously optimized according to the test results of the application condition set. This method can also be the actual application method of the application condition sets generated in the foregoing embodiments. Using the application condition sets generated in the foregoing embodiments to perform data processing objective verification helps to improve the accuracy of measuring the data to be measured and the reliability obtained by the application condition set.

[0088] In step 303, in response to detecting that the data to be measured satisfies at least one data processing objective, the data to be measured is determined as the target data.

[0089] In this embodiment, the target data is data applicable to the algorithm application corresponding to the data processing objective. The target data obtained through the application condition set can be applied to the project corresponding to at least one data processing objective, ensuring the implementation of the project.

[0090] The data processing method provided in this embodiment obtains the data to be measured, detects whether the data to be measured satisfies the data processing objective based on the application condition set, and when the data to be measured satisfies the data processing objective, uses the data to be measured as the target data, which can effectively identify the target data that satisfies the data processing objective and improve the identification efficiency of the target data.

[0091] In some alternative implementations of this embodiment, the multiple data processing target data includes at least one of the following: generating portrait data of each group among multiple groups in an intelligent report, defining individual circles to which multiple individuals in different industries belong, and generating a list of different risk individuals among multiple risk individuals.

[0092] In this alternative implementation, the target data is data that meets the data processing objective. For example, the data processing objective is the income portrait data of group T and group W; the target data is the population of different industries and different ages with high income. Through the target data, the group portrait data for generating an intelligent report analyzing group T and group W can be generated, thus providing a reliable basis for the construction of the intelligent report.

[0093] In this embodiment, by analyzing the target data corresponding to multiple data processing objectives, the individual circles to which individuals in different industries belong can be clustered to obtain analysis data for the individual circles corresponding to different industries, thereby providing a reliable basis for analyzing individuals in different industries. For another example, by analyzing the target data corresponding to multiple data processing objectives, risk individuals and non-risk individuals can also be accurately identified, providing a reliable basis for individual analysis.

[0094] The application method of the target data provided in this alternative implementation provides multiple different application directions for the application of the target data, improving the versatility of the application of the target data.

[0095] Further referring to Figure 4 , as an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a search device. This device embodiment corresponds to the Figure 1 shown method embodiment, and this device can be specifically applied to various electronic devices.

[0096] Such as Figure 4As shown in the figure, the search device 400 provided in this embodiment includes: a condition acquisition unit 401, a sample determination unit 402, a calculation unit 403, a combination unit 404, and a condition determination unit 405. Among them, the above-mentioned condition acquisition unit 401 can be configured to acquire multiple data processing conditions corresponding to the same data processing target from a first target memory. The above-mentioned sample determination unit 402 can be configured to extract corresponding measurement samples from a second target memory based on the data processing conditions. The above-mentioned calculation unit 403 can be configured to use a target processor to calculate and sort the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target, to obtain a condition result sequence, and the condition result sequence includes: multiple measurement results and the data processing conditions associated with each measurement result. The above-mentioned combination unit 404 can be configured to combine the data processing conditions corresponding to the measurement results in the condition result sequence to obtain a condition group sequence. The above-mentioned condition determination unit 405 can be configured to determine an application condition set based on the measurement results corresponding to the intersection of the measurement samples in the condition group sequence, and store the application condition set in the first target memory.

[0097] In this embodiment, in the search device 400: the specific processing of the condition acquisition unit 401, the sample determination unit 402, the calculation unit 403, the combination unit 404, and the condition determination unit 405 and the technical effects brought by them can respectively refer to Figure 1 the relevant descriptions of steps 101, 102, 103, 104, and 105 in the corresponding embodiments, which will not be elaborated here.

[0098] In some alternative implementation manners of this embodiment, the above data target is to determine data belonging to a predetermined group; the device further includes: a data acquisition unit (not shown in the figure), and the data acquisition unit can be configured to acquire data of multiple different individuals from a second target memory, search the data of multiple different individuals using the application condition set, obtain data corresponding to the predetermined group, and store the data of the predetermined group in the second target memory.

[0099] In some alternative implementation manners of this embodiment, the above calculation unit 403 is further configured to: when the data processing target includes maximizing the measurement result, the target processor calculates the measurement results of all data processing conditions corresponding to the data processing target; sorts all the measurement results from largest to smallest in sequence to obtain a condition result sequence.

[0100] In some alternative implementation manners of this embodiment, the above calculation unit 403 is further configured to: when the data processing target includes minimizing the measurement result, the target processor calculates the measurement results of all data processing conditions corresponding to the data processing target; sorts all the measurement results from smallest to largest in sequence to obtain a condition result sequence.

[0101] In some alternative implementation manners of this embodiment, the above combination unit 404 is further configured to: for a first data processing condition corresponding to a first measurement result in a condition result sequence, select a set number of data processing conditions after the first data processing condition; combine the first data processing condition with the selected data processing conditions, and combine the selected data processing conditions to obtain a condition group sequence including a plurality of condition groups.

[0102] In some alternative implementation manners of this embodiment, the above combination unit 404 is further configured to: use at least one data processing condition among all data processing conditions as a condition group and add it to the condition group sequence.

[0103] In some alternative implementation manners of this embodiment, the above condition determination unit 405 is further configured to: for each condition group in the condition group sequence, find the intersection of the measurement samples corresponding to the data processing conditions in the condition group to obtain the intersection of the measurement samples of the condition group; calculate the measurement result of the data processing target corresponding to the intersection of the measurement samples; in response to the measurement result of the intersection meeting the data processing target, determine the condition group as an application condition; sort all the application conditions and select a set number of application conditions from the sorted application conditions to obtain an application condition set.

[0104] For the search device provided in the embodiment of the present disclosure, first, the condition acquisition unit 401 acquires a plurality of data processing conditions corresponding to the same data processing target from a first target memory; second, the sample determination unit 402 extracts corresponding measurement samples from a second target memory based on the data processing conditions; third, the target processor calculation unit 403 calculates and sorts the measurement results of all data processing conditions corresponding to the data processing target based on the measurement samples and the data processing target to obtain a condition result sequence; fourth, the combination unit 404 combines the data processing conditions corresponding to the measurement results in the condition result sequence to obtain a condition group sequence; finally, the condition determination unit 405 determines an application condition set based on the measurement results corresponding to the intersection of the measurement samples of the condition group sequence and stores the application condition set in the first target memory. Thus, based on the sorting of the measurement results of all data processing conditions, an application condition set is determined based on the measurement results corresponding to the intersection of the measurement samples. On the basis of meeting the data processing target, each data processing condition in the obtained application condition set can be free from the influence of variable dependencies, and the obtained application condition set can maximize the requirements of the data processing target, improving the efficiency of obtaining the optimal application condition set and ensuring the reliability of the search for the application condition set; and different types of data are stored in different memories respectively, saving storage space, reducing storage consumption, and ensuring the standardization of data storage; the target processor is used to calculate and sort different condition results, improving the efficiency of data processing.

[0105] Continue to refer to Figure 5 , as an implementation of the method described above Figure 3 , this application provides an embodiment of a data processing device. This device embodiment corresponds to Figure 3 the method embodiment shown, and this device can be specifically applied to various electronic devices.

[0106] As Figure 5 shown, the data processing device 500 in this embodiment may include: a data acquisition unit 501, configured to acquire data to be measured. A detection unit 502, configured to detect whether the data to be measured meets at least one of the multiple data processing objectives based on the application condition set corresponding to the multiple data processing objectives obtained by the device described in the above Figure 4 embodiment. A data determination unit 503, configured to determine the data to be measured as target data in response to detecting that the data to be measured meets at least one data processing objective.

[0107] It can be understood that the various units described in this device 500 correspond to the respective steps in the method described with reference to Figure 3 . Therefore, the operations, features, and beneficial effects described above for the method also apply to the device 500 and the units included therein, and will not be elaborated here.

[0108] In some optional implementation manners of this embodiment, the above multiple data processing objectives include at least one of the following: generating portrait data of each group among multiple groups in an intelligent report, delineating individual circles to which multiple individuals in different industries belong, and generating a list of different risk individuals among multiple risk individuals.

[0109] In the technical solution of the present disclosure, the processing of collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved all complies with the provisions of relevant laws and regulations and does not violate public order and good customs.

[0110] According to the embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0111] Figure 6FIG. 0 shows a schematic block diagram of an exemplary electronic device 600 that can be used to implement embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, for example, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as, for example, personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementations of the present disclosure described and / or claimed herein.

[0112] As Figure 6 shown, the device 600 includes a computing unit 601 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 can also be stored. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0113] A plurality of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as, for example, a keyboard, a mouse, etc.; an output unit 607, such as, for example, various types of displays, speakers, etc.; a storage unit 608, such as, for example, a magnetic disk, an optical disk, etc.; and a communication unit 609, such as, for example, a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0114] The computing unit 601 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 executes the various methods and processes described above, such as the search method and the data processing method. For example, in some embodiments, the search method and the data processing method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the search method and the data processing method described above can be executed. Alternatively, in other embodiments, the computing unit 601 can be configured to execute the search method and the data processing method by any other suitable means (e.g., by means of firmware).

[0115] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, and the programmable processor can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0116] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to the processor or controller of a general-purpose computer, a special-purpose computer, or other programmable search devices and data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0117] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. 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, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0118] To provide for interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic, speech, or tactile input).

[0119] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of a communication network include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0120] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0121] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in this disclosure can be achieved, and no limitations are imposed herein.

[0122] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A search method, the method comprising: Obtaining a plurality of data processing conditions corresponding to the same data processing objective from a first target memory; Extracting corresponding measurement samples from a second target memory based on the data processing conditions; Using a target processor to calculate and sort the measurement results corresponding to all the data processing conditions for the data processing objective based on the measurement samples and the data processing objective, obtaining a conditional result sequence, the conditional result sequence including: a plurality of measurement results and the data processing conditions associated with each measurement result; Combining the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence; Determining an application condition set based on the measurement results corresponding to the intersection of the measurement samples of the conditional group sequence, and storing the application condition set in the first target memory.

2. The method according to claim 1, wherein The data processing objective is to determine data belonging to a predetermined group; the method further comprising: obtaining data of a plurality of different individuals from the second target memory, using the application condition set to search the data of the plurality of different individuals, obtaining data corresponding to the predetermined group, and storing the data of the predetermined group in the second target memory.

3. The method according to claim 1, wherein, The using a target processor to calculate and sort the measurement results corresponding to all the data processing conditions for the data processing objective based on the measurement samples and the data processing objective, obtaining a conditional result sequence, includes: When the data processing objective includes maximizing the measurement result, the target processor calculates the measurement results corresponding to all the data processing conditions for the data processing objective; Sorting all the measurement results from largest to smallest in sequence to obtain a conditional result sequence.

4. The method according to claim 1, wherein, The using a target processor to calculate and sort the measurement results corresponding to all the data processing conditions for the data processing objective based on the measurement samples and the data processing objective, obtaining a conditional result sequence, includes: When the data processing objective includes minimizing the measurement result, the target processor calculates the measurement results corresponding to all the data processing conditions for the data processing objective; Sorting all the measurement results from smallest to largest in sequence to obtain a conditional result sequence.

5. The method according to claim 1, wherein The combining the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence includes: For a first data processing condition corresponding to the first measurement result in the conditional result sequence, selecting a set number of data processing conditions after the first data processing condition; Combining the first data processing condition with the selected data processing conditions, and combining the selected data processing conditions, to obtain a conditional group sequence including a plurality of conditional groups.

6. The method according to claim 5, wherein The combining the data processing conditions corresponding to the measurement results in the conditional result sequence to obtain a conditional group sequence further includes: Taking at least one data processing condition among all the data processing conditions as a conditional group and adding it to the conditional group sequence.

7. The method according to any one of claims 1-6, wherein, The determining an application condition set based on the measurement results corresponding to the intersection of the measurement samples of the conditional group sequence includes: For each conditional group in the conditional group sequence, taking the intersection of the measurement samples corresponding to the data processing conditions in the conditional group to obtain the intersection of the measurement samples of the conditional group; Calculate the measurement result corresponding to the intersection of the measured samples for the data processing objective; In response to the measurement result of the intersection meeting the data processing objective, determine this condition group as the application condition; Sort all the application conditions, and select a set number of application conditions from the sorted application conditions to obtain an application condition set.

8. A data processing method, the method comprising: Obtain data to be measured; Based on the application condition sets corresponding to multiple data processing objectives obtained by the search method according to any one of claims 1-7, detect whether the data to be measured meets at least one of the multiple data processing objectives; In response to detecting that the data to be measured meets the at least one data processing objective, determine the data to be measured as the target data.

9. The method according to claim 8, wherein The multiple data processing objectives include at least one of the following: generating portrait data of each group among multiple groups in an intelligent report, defining individual circles to which multiple individuals in different industries belong, and generating a list of different risk individuals among multiple risk individuals.

10. A search device, the device comprising: A condition acquisition unit configured to obtain multiple data processing conditions corresponding to the same data processing objective from a first target memory; A sample determination unit configured to extract corresponding measured samples from a second target memory based on the data processing conditions; A calculation unit configured to use a target processor to calculate and sort the measurement results corresponding to all data processing conditions for the data processing objective based on the measured samples and the data processing objective, to obtain a condition result sequence, where the condition result sequence includes: multiple measurement results and the data processing conditions associated with each measurement result; A combination unit configured to combine the data processing conditions corresponding to the measurement results in the condition result sequence to obtain a condition group sequence; A condition determination unit configured to determine an application condition set based on the measurement result corresponding to the intersection of the measured samples in the condition group sequence, and store the application condition set in the first target memory.

11. The apparatus according to claim 10, wherein, The data processing objective is to determine data belonging to a predetermined group; the device further includes: a data acquisition unit configured to obtain data of multiple different individuals from the second target memory, search the data of the multiple different individuals using the application condition set to obtain data corresponding to the predetermined group, and store the data of the predetermined group in the second target memory.

12. The apparatus according to claim 10, wherein, The calculation unit is further configured to: when the data processing objective includes: maximizing the measurement result, the target processor calculates the measurement results corresponding to all data processing conditions for the data processing objective; sorts all the measurement results from largest to smallest in sequence to obtain a condition result sequence.

13. The apparatus according to claim 10, wherein, The calculation unit is further configured to: when the data processing objective includes: minimizing the measurement result, the target processor calculates the measurement results corresponding to all data processing conditions for the data processing objective; sorts all the measurement results from smallest to largest in sequence to obtain a condition result sequence.

14. The apparatus according to claim 10, wherein, The combination unit is further configured to: for a first data processing condition corresponding to a first measurement result in the condition result sequence, select a set number of data processing conditions after the first data processing condition; combine the first data processing condition with the selected data processing conditions, and combine the selected data processing conditions to obtain a condition group sequence including a plurality of condition groups.

15. The device according to claim 12, wherein, The combination unit is further configured to: use at least one data processing condition among all data processing conditions as a condition group and add it to the condition group sequence.

16. The device according to any one of claims 10 to 15, wherein The condition determination unit is further configured to: for each condition group in the condition group sequence, find the intersection of the measurement samples corresponding to the data processing conditions in the condition group to obtain the intersection of the measurement samples of the condition group. Calculate the measurement result of the intersection of the measurement samples corresponding to the data processing target; in response to the measurement result of the intersection meeting the data processing target, determine that this condition group is an application condition. Sort all the application conditions and select a set number of application conditions from the sorted application conditions to obtain an application condition set.

17. A data processing device, the device includes: A data acquisition unit configured to acquire data to be measured. A detection unit configured to detect whether the data to be measured meets at least one of the data processing targets corresponding to the application condition sets obtained by the search device according to any one of claims 10-16. A data determination unit configured to, in response to detecting that the data to be measured meets the at least one data processing target, determine that the data to be measured is target data.

18. The apparatus according to claim 17, wherein, The multiple data processing targets include at least one of the following: generating portrait data of each group among multiple groups in an intelligent report, defining individual circles to which multiple individuals in different industries belong, and generating lists of different risk individuals among multiple risk individuals.

19. An electronic device, characterized in that, Including: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-9.

20. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-9.

21. A computer program product, including a computer program that implements the method according to any one of claims 1-9 when executed by a processor.

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