A method, device and storage medium for obtaining a user portrait

Abstract

The application provides a method, device and storage medium for obtaining a user portrait. The method is based on original user identification data of all users in all business systems, combines user ID identification and ID type credibility and the importance of the business system to which the ID identification belongs, obtains the most credible unique user credible identification, and establishes the corresponding relationship between the credible identification and the user ID identification, so that the user can quickly obtain user data in different business systems through the unique user credible identification, and a more accurate user portrait is established.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a method, device and storage medium for obtaining a user portrait. BACKGROUND

[0002] Precise service and customized service have become a common way to provide services for terminal users. Through precise service, the use experience of terminal users can be greatly improved. The premise of precise service is the accurate description of the user portrait of terminal users. In the prior art, when terminal users use multiple different business systems, they usually use different types of user identifiers according to their own habits. Therefore, when collecting business system data of terminal users, it is necessary to log in to each business system one by one and obtain data. This data acquisition method is not only inefficient, but also easy to cause incomplete data collection due to mistakes, thereby causing inaccurate user portraits. SUMMARY

[0003] To solve the above technical problems, the technical solution adopted by the present application is as follows: a method for obtaining a user portrait, comprising the following steps: S1000, obtaining a trusted identifier of a user, wherein the trusted identifier is used to uniquely identify the user; S2000, based on the trusted identifier of the user and a preset ID identifier-trusted identifier correspondence table, obtaining system user data of the user in N business systems, wherein the preset ID identifier-trusted identifier correspondence table is used to represent the correspondence between the trusted identifier of different users and the ID identifier used by them in the N business systems, and the ID identifier is used to uniquely identify the user corresponding thereto; S3000, obtaining a user portrait of the user based on the system user data.

[0004] A device for obtaining a user portrait, comprising a processor and a non-transitory computer-readable storage medium, the storage medium being used to save at least one instruction or at least one program, the processor loading and executing the at least one instruction or at least one program to realize the above-mentioned method.

[0005] A computer-readable storage medium, the computer-readable storage medium storing a program or instructions, the program or instructions causing a computer to execute the above-mentioned method.

[0006] The present application has at least the following technical effects: based on the obtained original user identifier data of all users in all business systems, the present application combines the trustworthiness of user ID identifier and ID type, the importance degree of the business system to which the ID identifier belongs, obtains the unique user trusted identifier with the highest trustworthiness, and establishes the correspondence between the trusted identifier and the user ID identifier, thereby enabling the user to quickly obtain user data in different business systems through the unique user trusted identifier, and establish a more accurate user portrait. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a flowchart illustrating a method for obtaining a user profile, as provided in an embodiment of this application. Detailed Implementation

[0009] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0010] This application provides a method for obtaining user profiles, such as... Figure 1 As shown, the method includes the following steps:

[0011] S1000, obtain the user's trusted identifier.

[0012] Specifically, in this application, a user's trusted identifier can be used to uniquely identify the user, that is, the user can be uniquely identified through this trusted identifier. Furthermore, those skilled in the art will understand that a user's ID identifier can also be used to uniquely identify the user; the same user can set multiple different ID identifiers to identify themselves.

[0013] The trusted identifier can be any of the user's ID identifiers. In a preferred embodiment, the trusted identifier is obtained by encrypting the user's ID identifier. The encryption process can be any of the prior art. For example, the encryption process can be obtaining the MD5 value of the user's ID identifier to obtain the user's trusted identifier.

[0014] S2000: Based on the user's trusted identifier and a preset ID identifier-trusted identifier mapping table, obtain the user's system user data in N business systems. The preset ID identifier-trusted identifier mapping table is used to represent the correspondence between the trusted identifiers of different users and the ID identifiers they use in the N business systems.

[0015] In the present application, N≥2, and those skilled in the art can understand that the larger N is, the more likely it is that the user will miss some or several data in a business system due to negligence. Therefore, by setting the preset ID identifier-trustworthy identifier correspondence table in the present application, the user can quickly obtain all user data of the user in the N business systems through the trustworthy identifier. In addition, the use of the encrypted trustworthy identifier can protect the user information.

[0016] Further, the system user data can be, for example, system setting data of the user in the system, and can also be system use data of the user, etc. The specific content of the system user data is not limited in the present application. Those skilled in the art can know that the system user data that is helpful to establish the user portrait is within the protection scope of the present application.

[0017] S3000, obtaining a user portrait of the user based on the system user data.

[0018] As can be known from the above, by constructing the ID identifier-trustworthy identifier correspondence table, the user can quickly obtain all user data of the user in the N business systems through the trustworthy identifier, avoiding missing some or several data of the user in a business system due to negligence, so as to establish a more accurate user portrait.

[0019] In a preferred embodiment of the present application, the obtaining of the preset ID identifier-trustworthy identifier correspondence table comprises the following steps:

[0020] S100, obtaining first user original data of all users in N business systems at a first time point, each first user original sub-data in the first user original data comprising at least one ID identifier of the same user in the same business system.

[0021] In the present application, the N business systems are independent business systems performing different tasks. According to the difference in the type of task performed by different business systems, the N business systems are configured with a system trust coefficient for indicating the importance of the system. Specifically, the system trust coefficient is related to the business system itself, and the more important the business system itself is, the more trustworthy it is, and the higher the corresponding system trust coefficient is. The ID type can be a type known in the prior art, such as a mobile communication number, an email, a user-defined username, etc.

[0022] Specifically, in this step, the first user original data is obtained by collecting user identification information of all users in each business system at a first time point, wherein the user identification information of the same user in the same business system is recorded in one data. For example, if a user sets the user identification as mobile communication number T1-ID1, mobile communication number T1-ID2 and mailbox T2-ID1 in the first business system, the first user original sub-data collected at the first time point are T1-ID1, T1-ID2 and T2-ID1 respectively. If a user sets the user identification as mobile communication number T1-ID1 and T1-ID3 in the second business system, another first user original sub-data collected at the first time point are T1-ID1 and T1-ID3. If a user sets the user identification as two different mobile communication numbers T1-ID4 and T1-ID5 in the first business system, the third first user original sub-data collected at the first time point are T1-ID4 and T1-ID5. If a user sets the user identification as mailbox T2-ID6 and user-defined username T3-ID7 in the third business system, the fourth first user original sub-data collected at the first time point are T2-ID6 and T3-ID7.

[0023] In S200, the first user data conforming to the first ID type is obtained according to the first user original data, wherein each first user sub-data in the first user data at least includes an identification association part and a system trust coefficient, the identification association part is obtained by extracting the ID identification conforming to the first ID type in the first user original sub-data corresponding to the first user sub-data, and the system trust coefficient is used to represent the importance of the business system to which the first user sub-data belongs.

[0024] In the present application, the first ID type is a preset ID type with the highest trustworthiness. For example, when the ID types include mobile communication number, mailbox and user-defined username, the trustworthiness of the mobile communication number can be set to be higher than that of the mailbox and the user-defined username, and the trustworthiness of the user-defined username is the lowest. At this time, the first ID type is the mobile communication number. It is known to those skilled in the art that the above description is only exemplary and is not used to limit the protection scope of the present application.

[0025] Specifically, in order to more clearly illustrate the content of the step, taking the aforementioned exemplary content as an example, when the first ID type is a mobile communication number, the identification associated part T1-ID1, T1-ID2 in the first first user sub-data can be obtained by extracting the ID identification in the first first user original sub-data that conforms to the first ID type, and the corresponding system trust coefficient is the system trust coefficient w1 corresponding to the first service system. By analogy, the identification associated part T1-ID1, T1-ID3 of the second first user sub-data is obtained by extracting the ID identification in the second first user original sub-data that conforms to the first ID type, and the corresponding system trust coefficient is the system trust coefficient w2 corresponding to the second service system; the identification associated part T1-ID4, T1-ID5 in the third first user sub-data can be obtained by extracting the ID identification in the third first user original sub-data that conforms to the first ID type, and the corresponding system trust coefficient is the system trust coefficient w1 corresponding to the first service system. Since the ID types in the fourth first user original sub-data do not conform to the first ID type, the corresponding first user sub-data cannot be obtained according to the fourth first user original sub-data, or the corresponding first user sub-data is empty.

[0026] S300, obtaining a data processing cycle threshold TL according to the trust level of the first ID type, setting the data processing cycle number L=1, taking the first user data as the first input data, performing first data processing on the first input data, and obtaining the first output data corresponding to the first ID type, wherein each of the first output data corresponding to the first ID type at least saves the corresponding relationship between one ID identification of the user conforming to the first ID type and the trusted identification of the user.

[0027] Specifically, the data processing cycle threshold TL is a function of the trust level of the first ID type, and in one embodiment, TL=2z+k, wherein z is the trust level of the first ID type, and the integer k has a value of 0, and preferably, the value of k is 1. Since the trust level of the first ID type is at most 1, the value of TL is 2 or 3, and preferably 3. By setting TL, the accuracy of the obtained user trusted identification can be ensured while taking into account the amount of data calculation.

[0028] Further, the first data processing includes the following steps:

[0029] S301, data splitting is performed on each first user sub-data in the first input data to obtain first split data, and the data splitting specifically includes: for each first user sub-data, splitting into P first split sub-data including a user identification part, an identification association part and a system trust coefficient according to the number P of ID identifications contained in the identification association part, wherein the P ID identifications correspond to the user identification parts of the P first split sub-data respectively, the identification association parts of the P first split sub-data are the same as the identification association part of the first user sub-data corresponding thereto, and the system trust coefficients of the P first split sub-data are the same as the system trust coefficient of the first user sub-data corresponding thereto.

[0030] By the way, in this step, the first first user sub-data (T1-ID1, T1-ID2: w1) is split into two first split sub-data: (T1-ID1: T1-ID1, T1-ID2: w1) and (T1-ID2: T1-ID1, T1-ID2: w1). Among them, the three parts separated by “:” in the first split sub-data correspond to the user identification part, the identification association part and the system trust coefficient from front to back. Similarly, the second first user sub-data (T1-ID1, T1-ID3: w2) is split into two first split sub-data, which are (T1-ID1: T1-ID1, T1-ID3: w2) and (T1-ID3: T1-ID1, T1-ID3: w2) respectively. The third first user sub-data (T1-ID4, T1-ID5: w1) is split into two first split sub-data, which are (T1-ID4: T1-ID4, T1-ID5: w1) and (T1-ID5: T1-ID4, T1-ID5: w1) respectively. In this application, the composition or expression of the multiple parts included in each first user original sub-data, first user sub-data and first split sub-data is not specifically limited, and those skilled in the art can know that any method in the prior art can be used to represent the multiple constituent parts included in each sub-data. The above-mentioned method of using “:” to distinguish multiple different parts is only an exemplary content.

[0031] S302, obtaining first merged data based on the first split data, wherein all first split sub-data with the same user identification part are merged to obtain one first merged sub-data in the first merged data, the user identification part of the first merged sub-data is the same as the user identification part of any one of the first split sub-data corresponding thereto, the identification association part of the first merged sub-data is the union of the identification association parts of all first split sub-data corresponding thereto, and the system trust coefficient of the first merged sub-data is the sum of the system trust coefficients of all first split sub-data corresponding thereto.

[0032] As known from the foregoing examples, the first split data includes six first split sub-data, which are respectively:

[0033] (T1-ID1: T1-ID1, T1-ID2: w1);

[0034] (T1-ID2: T1-ID1, T1-ID2: w1)

[0035] (T1-ID1: T1-ID1, T1-ID3: w2);

[0036] (T1-ID3: T1-ID1, T1-ID3: w2);

[0037] (T1-ID4: T1-ID4, T1-ID5: w1);

[0038] (T1-ID5: T1-ID4, T1-ID5: w1).

[0039] The first split data includes six first split sub-data, which are respectively:

[0040] (T1-ID1: T1-ID1, T1-ID2, T1-ID3: w1+w2);

[0041] (T1-ID2: T1-ID1, T1-ID2: w1);

[0042] (T1-ID3: T1-ID1, T1-ID3: w2);

[0043] (T1-ID4: T1-ID4, T1-ID5: w1);

[0044] (T1-ID5: T1-ID4, T1-ID5: w1).

[0045] S303, if L < TL, S304 is executed, otherwise, S305 is executed. In order to illustrate the specific scheme of the present application, in an exemplary embodiment, TL = 2, as known from the foregoing examples, L < TL, S304 is executed.

[0046] S304, set L = L + 1, and the identification association part and the system trust coefficient in the first combined data are taken as the first user data, and return to execute S301. As known, L = 2 at this time.

[0047] Specifically, in this step, the first user data includes five first user sub-data, which are respectively:

[0048] (T1-ID1, T1-ID2, T1-ID3: w1+w2);

[0049] (T1-ID1, T1-ID2: w1);

[0050] (T1-ID1, T1-ID3: w2);

[0051] (T1-ID4, T1-ID5: w1);

[0052] (T1-ID4, T1-ID5: w1).

[0053] Return to execute S301 to get the first split data for data splitting:

[0054] (T1-ID1: T1-ID1, T1-ID2, T1-ID3: w1+w2);

[0055] (T1-ID2: T1-ID1, T1-ID2, T1-ID3: w1+w2);

[0056] (T1-ID3: T1-ID1, T1-ID2, T1-ID3: w1+w2);

[0057] (T1-ID1: T1-ID1, T1-ID2: w1);

[0058] (T1-ID2: T1-ID1, T1-ID2: w1);

[0059] (T1-ID1: T1-ID1, T1-ID3: w2);

[0060] (T1-ID3: T1-ID1, T1-ID3: w2);

[0061] (T1-ID4: T1-ID4, T1-ID5: w1);

[0062] (T1-ID5: T1-ID4, T1-ID5: w1);

[0063] (T1-ID4: T1-ID4, T1-ID5: w1);

[0064] (T1-ID5: T1-ID4, T1-ID5: w1).

[0065] Then execute S302 to get the first merged data:

[0066] (T1-ID1: T1-ID1, T1-ID2, T1-ID3: 2*(w1+w2));

[0067] (T1-ID2: T1-ID1, T1-ID2, T1-ID3: 2*w1+w2);

[0068] (T1-ID3: T1-ID1, T1-ID2, T1-ID3: w1+2*w2);

[0069] (T1-ID4: T1-ID4, T1-ID5: 2*w1);

[0070] (T1-ID5: T1-ID4, T1-ID5: 2*w1).

[0071] Since L < TL is not true at this time, S305 is executed.

[0072] S305, a user trusted identity part is added to each first merging sub-data in the first merging data to obtain first merging processing data, wherein the user trusted identity part is obtained by encrypting the user identity part in the corresponding first merging sub-data.

[0073] As known from the foregoing, the first merging processing data obtained at this time is:

[0074] (T1-ID1: T1-ID1, T1-ID2, T1-ID3: 2*(w1+w2): oneid1);

[0075] (T1-ID2: T1-ID1, T1-ID2, T1-ID3: 2*w1+w2: oneid2);

[0076] (T1-ID3: T1-ID1, T1-ID2, T1-ID3: w1+2*w2: oneid3);

[0077] (T1-ID4: T1-ID4, T1-ID5: 2*w1: oneid4);

[0078] (T1-ID5: T1-ID4, T1-ID5: 2*w1: oneid5).

[0079] oneid1 is obtained by encrypting T1-ID1, oneid2 is obtained by encrypting T1-ID2, and oneid3-oneid5 are obtained in the same way.

[0080] S306, data decomposition is performed on each piece of first combined processing sub-data in the first combined processing data to obtain first decomposition data, and the data decomposition specifically includes: for each piece of first combined processing sub-data, decomposing it into Q pieces of first decomposition sub-data including a user identification part, a user trusted identification part and a system trusted coefficient according to the number Q of ID identifications contained in the identification association part, wherein the Q ID identifications correspond to the user identification parts of the Q pieces of first decomposition sub-data respectively, the user trusted identification parts of the Q pieces of first decomposition sub-data are the same as the user trusted identification part of the first combined processing sub-data corresponding thereto, and the system trusted coefficients of the Q pieces of first decomposition sub-data are the same as the system trusted coefficient of the first combined processing sub-data corresponding thereto.

[0081] The first decomposition data obtained by data decomposition on the first combined processing data is as follows:

[0082] (T1-ID1: oneid1: 2*(w1+w2));

[0083] (T1-ID2: oneid1: 2*(w1+w2));

[0084] (T1-ID3: oneid1: 2*(w1+w2));

[0085] (T1-ID1: oneid2: 2*w1+w2);

[0086] (T1-ID2: oneid2: 2*w1+w2);

[0087] (T1-ID3: oneid2: 2*w1+w2);

[0088] (T1-ID1: oneid3: w1+2*w2);

[0089] (T1-ID2: oneid3: w1+2*w2);

[0090] (T1-ID3: oneid3: w1+2*w2);

[0091] (T1-ID4: oneid4: 2*w1);

[0092] (T1-ID5: oneid4: 2*w1);

[0093] (T1-ID4: oneid5: 2*w1)

[0094] (T1-ID5: oneid5: 2*w1).

[0095] S307, obtaining first output data based on the first decomposition data, wherein a first decomposition sub-data with the largest system trust coefficient among all first decomposition sub-data with the same user identification part is saved to obtain a first output sub-data in the first output data.

[0096] In this step, exemplary, all first decomposition sub-data with the same user identification part T1-ID1 are:

[0097] (T1-ID1: oneid1: 2*(w1+w2));

[0098] (T1-ID1: oneid2: 2*w1+w2);

[0099] (T1-ID1: oneid3: w1+2*w2);

[0100] If w1 is much larger than w2, i.e., the importance of the first business system is much larger than that of the second business system, it can be known that (T1-ID1: oneid1: 2*(w1+w2)) needs to be saved as a first output sub-data in the first output data.

[0101] According to the above, the first output data is:

[0102] (T1-ID1: oneid1: 2*(w1+w2));

[0103] (T1-ID2: oneid1: 2*(w1+w2));

[0104] (T1-ID3: oneid1: 2*(w1+w2));

[0105] (T1-ID4: oneid4: 2*w1);

[0106] (T1-ID5: oneid4: 2*w1);

[0107] Specifically, for T1-ID4 and T1-ID5, the system trust coefficients of the two first decomposition sub-data corresponding thereto are the same, at this time, the first output sub-data can be obtained according to a preset rule, for example, the preset rule is to output the data in the front. It can also be known by those skilled in the art that a plurality of other ways can be set to output the first output sub-data corresponding to T1-ID4 and T1-ID5, and the present application does not make specific limitation thereto.

[0108] S400, obtaining the preset ID identification-trust identification corresponding table according to the first output data corresponding to the first ID type and the first user original data.

[0109] In this step, for each first output sub-data in the first output data corresponding to the first ID type, according to the user identification part thereof, at least one first user original sub-data containing the user identification part of the first output sub-data is found in the first user original data, and each of the other type ID identifications of the non-first ID type in the at least one first user original sub-data is added to the first output data in the form of user identification part and user trusted identification part to obtain the preset ID identification-trusted identification correspondence table, wherein each ID identification of the other type ID identifications of the non-first ID type corresponds to the same user trusted identification part as the user trusted identification part corresponding to the user identification part of the first output sub-data corresponding thereto.

[0110] For example, for the first output sub-data (T1-ID1: oneid1: 2*(w1+w2)) in the first output data, according to the user identification part T1-ID1 thereof, two first user original sub-data containing the T1-ID1 are found, i.e., T1-ID1, T1-ID2, T2-ID1; T1-ID1, T1-ID3. Since the ID identifications of the non-first ID type in the above two first user original sub-data are only T2-ID1, T2-ID1 is added to the first output data in the form of (T2-ID1: oneid1). By analogy in the above manner, the preset ID identification-trusted identification correspondence table can be obtained.

[0111] It is known to those skilled in the art that when T1-ID2 is operated according to the above process, since (T2-ID1: oneid1) already exists in the first output data, it can be selected not to be repeatedly added at this time.

[0112] It is known to those skilled in the art that the preset ID identification-trusted identification correspondence table can also be saved in other manners, for example, the first output sub-data (T1-ID1: oneid1: 2*(w1+w2)) and T2-ID1 are recombined and saved.

[0113] Specifically, the correspondence between the user trusted identification and the ID identification of the user can be recorded in any manner in the prior art, such as text, database, etc. In the preferred embodiment of the present application, the correspondence between the ID identifications can be represented in the form of a graph, wherein any node in the graph represents an ID identification or a trusted identification, and any two nodes having a correspondence are connected by a line segment.

[0114] From the above, based on the obtained original user identifier data of all users in all business systems, the application screens out the user identifier data of all users corresponding to the ID type with the highest credibility, and combines the identification association part in the user identifier data and the importance of the user identifier source system to obtain the unique user trusted identifier with the highest credibility and establish the corresponding relationship between the trusted identifier and the user ID identifier, so that the user can quickly obtain user data in different business systems through the unique user trusted identifier and establish a more accurate user portrait.

[0115] In the preferred embodiment of the application, S200 further includes the following content:

[0116] (M-1) type user data of (M-1) preset ID types are obtained respectively, wherein each piece of type user sub-data in the type user data corresponding to each of the (M-1) preset ID types at least includes an identification association part and a system credibility coefficient, the identification association part is obtained by extracting an ID identifier conforming to the preset ID type corresponding to the type user sub-data from a piece of user original sub-data corresponding to the type user sub-data, the system credibility coefficient is used to represent the importance of the business system to which the type user sub-data belongs, M>1, and the (M-1) preset ID types are different from the first ID type.

[0117] From the foregoing exemplary content, if M-1=2, i.e., the (M-1) preset ID types are two types of mailbox and user-defined username, the type user data corresponding to the preset ID type of mailbox is (T2-ID6: w3) and (T2-ID1, w1), and the type user data corresponding to the preset ID type of user-defined username is (T3-ID7: w3).

[0118] At this time, S400 further includes the following steps:

[0119] S500, according to the order from large to small of the preset ID type credibility level, the second data processing is performed on the type user data corresponding to the (M-1) preset ID types in turn.

[0120] The second data processing includes the following content:

[0121] S501, obtaining second user data based on the type user data corresponding to the mth ID type, wherein the second user data is obtained by deleting the type user sub-data in the type user data corresponding to the mth ID type which has established a corresponding relationship with the trusted identifier of any user, 1≤m≤(M-1). Specifically, when the preset ID type is an email, since T2-ID1 has established a corresponding relationship with oneid1 in S400, (T2-ID1, w1) needs to be deleted at this time, that is, when the preset ID type is an email, the second user data corresponding thereto only contains (T2-ID6: w3). Specifically, in the present application, the establishment of the corresponding relationship between the trusted identifier of the user and the user ID identifier is based on the first user original sub-data. As described above, since T2-ID1 is included in the first user original sub-data T1-ID1, T1-ID2, and T2-ID1, the corresponding relationship between oneid1 and T2-ID1 can be directly established. If only T2-ID1 is included in a piece of first user original sub-data, and T1-ID1 or T1-ID2 is not included in the piece of first user original sub-data, T2-ID1 in the piece of first user original sub-data cannot directly establish a corresponding relationship with oneid1.

[0122] S502, associating the identifier association part of the second user data and the system trusted coefficient as first input data, obtaining a data processing cycle threshold TL according to the trusted level of the mth ID type, setting the data processing cycle number L=1, and based on the TL and L before this step, performing first data processing on the aforementioned first input data in this step to obtain first output data corresponding to the mth ID type, wherein each piece of the first output data corresponding to the mth ID type at least saves the corresponding relationship between one ID identifier of the user conforming to the mth ID type and the trusted identifier of the user;

[0123] S503, updating the preset ID identifier-trusted identifier corresponding table based on the first output data corresponding to the mth ID type and the first user original data.

[0124] Specifically, in this step, first, if the user identification part of a first output sub-data in the first output data corresponding to the mth ID type is contained in the user identification part of the preset ID identification-trustworthy identification correspondence table, the user trustworthy identification part corresponding to the user identification part in the preset ID identification-trustworthy identification correspondence table is used to update the user trustworthy identification part of all first output sub-data in the first output data corresponding to the mth ID type which has the same user trustworthy identification part as the first output sub-data; second, each ID identification in the first output data corresponding to the mth ID type which is not contained in the preset ID identification-trustworthy identification correspondence table is added to the preset ID identification-trustworthy identification correspondence table in the form of a user identification part and a user trustworthy identification part; and finally, for each first output sub-data in the first output data corresponding to the mth ID type, at least one first user original sub-data containing the user identification part of the first output sub-data is found in the first user original data according to the user identification part, and each of the other type ID identification whose trustworthy level is lower than the mth ID type is added to the preset ID identification-trustworthy identification correspondence table in the form of a user identification part and a user trustworthy identification part, wherein the user trustworthy identification part corresponding to each of the other type ID identification whose trustworthy level is lower than the mth ID type and the user trustworthy identification part corresponding to the user identification part of the first output sub-data corresponding thereto are the same.

[0125] As described above, when the preset ID type is a mailbox, since T2-ID6 does not exist in the preset ID identification-trustworthy identification correspondence table, the related content of the first output sub-data related to T2-ID6 is added to the preset ID identification-trustworthy identification correspondence table for updating.

[0126] As described above, the application establishes a unique user trustworthy identification with a higher trustworthiness for the other type identification of the user without the first ID type, so as to obtain the system data of the user from multiple different business systems by using the unique user trustworthy identification under the type, thereby improving the comprehensiveness of the obtained data and the accuracy of the user portrait.

[0127] In another embodiment disclosed in the application, S500 further includes the following steps:

[0128] S1, obtaining second user original data of all users in N business systems at a second time point, each second user original sub-data in the second user original data including at least one ID identification of the same user in the same business system; wherein the second time point is later than the first time point.

[0129] S2, updating the preset ID mark-trust mark correspondence table according to the second user original data. The updating is, for example, that according to the user ID mark in each piece of second user original sub-data and contained in the preset ID mark-trust mark correspondence table, a correspondence between other ID marks and trust marks of the user is established in the preset ID mark-trust mark correspondence table.

[0130] Further, in another embodiment of the present application, S2 further includes the following content:

[0131] S3, obtaining screening user data in the second user original data, wherein the screening user data is obtained by deleting second user original sub-data that has established a correspondence with any user's trust mark in the second user original data.

[0132] S4, obtaining M pieces of second type user data of preset ID types based on the screening user data, wherein the M pieces of preset ID types are the first ID type and (M-1) pieces of preset ID types.

[0133] S5, associating the identification part of the second type user data corresponding to the first ID type in the screening user data and the system trust coefficient as the first user data, and performing S300 to obtain the first output data corresponding to the first ID type in the screening user data, wherein each piece of the first output data corresponding to the first ID type in the screening user data at least stores a correspondence between one ID mark of the user conforming to the first ID type and the trust mark of the user.

[0134] S6, updating the preset ID mark-trust mark correspondence table according to the first output data corresponding to the first ID type in the screening user data.

[0135] S7, for the second type user data of the (M-1) pieces of preset ID types different from the first ID type in the screening user data, performing second data processing on the second type user data corresponding to the (M-1) pieces of preset ID types in order according to the preset ID type trust level from large to small.

[0136] From the above content, it can be known that by directly establishing a correspondence between the user mark collected later than the first time point and the unique user trust mark already possessed by the user, repeated processing of data can be avoided to occupy computing resources and the like. In addition, by processing the user mark data in the user original data collected at the second time point which has not established a correspondence, a unique user trust mark can be obtained for a new user of the business system in a timely manner, so as to establish a reliable user portrait.

[0137] In another embodiment of the present application, in order to further ensure the accuracy of the established user portrait, the method further comprises the following content:

[0138] S001, for each user ID in the preset ID- trusted ID correspondence table, obtaining a time difference value between the current time and the latest collection time of the user ID. For example, if the second time point is the collection time of the latest collected data, the time difference value between the current time and the second time point is obtained.

[0139] S002, when the time difference value is greater than a preset time interval threshold, canceling the correspondence between the user ID and the trusted ID corresponding thereto in the preset ID- trusted ID correspondence table. Those skilled in the art can know that the cancellation can be realized in various ways, such as deleting the data, or emptying the user ID, or emptying the trusted ID corresponding to the user ID, etc. Specifically, the preset time interval threshold = (24 months- time difference value) * A / B, wherein A represents the number of times the user ID is collected within the time period between the first time point and the current time, and B represents the total number of data collection within the time period between the first time point and the current time.

[0140] According to the above content, by timely canceling the correspondence between the user ID with low use frequency or no longer used and the user trusted ID, the accuracy of the user portrait can be further improved.

[0141] Embodiments of the present application also provide a device for obtaining a user portrait, which comprises a processor and a non-transitory computer readable storage medium, the storage medium is used to save at least one instruction or at least one program, the processor loads and executes the at least one instruction or at least one program to realize the method provided by the above-mentioned embodiments.

[0142] Embodiments of the present application also provide a computer readable storage medium, the computer readable storage medium stores programs or instructions, the programs or instructions make the computer execute the steps of the method provided by the above-mentioned embodiments.

[0143] Embodiments of the present application also provide a non-transitory computer readable storage medium, which can be arranged in an electronic device to save at least one instruction or at least one program related to a method in the method embodiment, the at least one instruction or the at least one program is loaded and executed by the processor to realize the method provided by the above-mentioned embodiments.

[0144] Embodiments of the present application also provide an electronic device, comprising a processor and the aforementioned non-transitory computer readable storage medium.

[0145] Embodiments of the present application also provide a computer program product comprising program code for causing an electronic device to perform the steps of the methods according to various exemplary embodiments of the present application described above in the specification when the program product is run on the electronic device.

[0146] While certain embodiments of the application have been described in detail as above, those skilled in the art should understand that they are merely examples of the application and should not limit the scope of the application. Those skilled in the art should also understand that various modifications can be made to the embodiments without departing from the scope and spirit of the application. The scope of the application is defined by the appended claims.

Claims

1. A method of acquiring a user profile, characterized by, The method comprises the following steps: S1000, obtaining a trusted identity of a user, wherein the trusted identity is used for uniquely identifying the user; S2000, obtaining system user data of the user in N business systems based on the trusted identity of the user and a preset ID identity-trusted identity correspondence table, wherein the preset ID identity-trusted identity correspondence table is used for representing a correspondence relationship between the trusted identity of different users and the ID identity used by the users in the N business systems, and the ID identity is used for uniquely identifying the user corresponding thereto; S3000, obtaining a user portrait of the user based on the system user data; The preset ID identity-trusted identity correspondence table is obtained through the following steps: S100, obtaining first user original data of all users in the N business systems at a first time point, and each first user original sub-data in the first user original data comprises at least one ID identity of the same user in the same business system in the same ID type; S200, obtaining first user data in the first ID type according to the first user original data, wherein each first user sub-data in the first user data comprises at least an identification association part and a system trusted coefficient, the identification association part is obtained by extracting the ID identity in the same ID type in the first user original sub-data corresponding to the first user sub-data, and the system trusted coefficient is used for representing the importance of the business system to which the first user sub-data belongs; the first ID type is the ID type with the highest trusted level; S300, obtaining a data processing cycle number threshold TL according to the trusted level of the first ID type, setting a data processing cycle number L = 1, taking the first user data as first input data, performing first data processing on the first input data, and obtaining first output data corresponding to the first ID type, wherein each first output data corresponding to the first ID type is used for saving at least the correspondence relationship between one ID identity of the user in the first ID type and the trusted identity of the user; S400, obtaining the preset ID identity-trusted identity correspondence table according to the first output data corresponding to the first ID type and the first user original data; The first data processing comprises the following steps: S301, performing data splitting on each first user sub-data in the first input data to obtain first split data, and the data splitting specifically comprises: for each first user sub-data, according to the number P of ID identities contained in the identification association part thereof, splitting into P first split sub-data comprising a user identification part, an identification association part and a system trusted coefficient, wherein the P ID identities correspond to the user identification part of the P first split sub-data respectively, the identification association part of the P first split sub-data is the same as the identification association part of the first user sub-data corresponding thereto, and the system trusted coefficient of the P first split sub-data is the same as the system trusted coefficient of the first user sub-data corresponding thereto; S302, obtaining first combined data based on the first split data, wherein all first split sub-data with the same user identification part are combined to obtain a first combined sub-data in the first combined data, the user identification part of the first combined sub-data is the same as the user identification part of any first split sub-data corresponding to the first combined sub-data, the identification association part of the first combined sub-data is the union of the identification association parts of all first split sub-data corresponding to the first combined sub-data, and the system trust coefficient of the first combined sub-data is the sum of the system trust coefficients of all first split sub-data corresponding to the first combined sub-data; S303, if L < TL, performing S304, otherwise, performing S305; S304, setting L = L + 1, taking the identification association part and the system trust coefficient in the first combined data as the first user data, and returning to perform S301; S305, adding a user trust identification part to each first combined sub-data in the first combined data to obtain first combined processing data, wherein the user trust identification part is obtained by encrypting the user identification part in the corresponding first combined sub-data; S306, performing data decomposition on each first combined processing sub-data in the first combined processing data to obtain first split data, wherein the data decomposition specifically includes: for each first combined processing sub-data, decomposing it into Q first split sub-data including the user identification part, the user trust identification part and the system trust coefficient according to the number Q of ID identifications contained in the identification association part of the first combined processing sub-data, wherein the Q ID identifications correspond to the user identification parts of the Q first split sub-data respectively, the user trust identification parts of the Q first split sub-data are the same as the user trust identification part of the first combined processing sub-data corresponding to the Q first split sub-data, and the system trust coefficients of the Q first split sub-data are the same as the system trust coefficient of the first combined processing sub-data corresponding to the Q first split sub-data; S307, obtaining first output data based on the first split data, wherein the first output data is obtained by saving a first split sub-data with the maximum system trust coefficient among all first split sub-data with the same user identification part.

2. The method of claim 1, wherein, S400 specifically includes: For each first output sub-data in the first output data corresponding to the first ID type, at least one first user original sub-data containing the user identification part of the first output sub-data is found in the first user original data according to the user identification part of the first output sub-data, and each ID identification of other types of ID identifications of the first output sub-data is added to the first output data in the form of user identification part and user trust identification part to obtain the preset ID identification-trust identification corresponding table, wherein the user trust identification part corresponding to each ID identification of other types of ID identifications of the first output sub-data is the same as the user trust identification part corresponding to the user identification part of the first output sub-data.

3. The method of claim 1, wherein, S200 further includes the following content: (M-1) type user data of (M-1) preset ID types are acquired respectively, wherein each piece of type user sub-data in the type user data corresponding to each of the (M-1) preset ID types at least includes an identification association part and a system trust coefficient, the identification association part is obtained by extracting an ID identifier conforming to the preset ID type corresponding to the type user sub-data from a user original sub-data corresponding to the type user sub-data, and the system trust coefficient is used to represent the importance of a business system to which the type user sub-data belongs, M>1, and the (M-1) preset ID types are different from the first ID type.

4. The method of claim 3, wherein, S400 further includes the following steps: S500, according to the order from large to small of the preset ID type trust level, the type user data corresponding to the (M-1) preset ID types is sequentially executed second data processing; The second data processing includes the following contents: S501, the second user data is acquired based on the type user data corresponding to the mth ID type, wherein the second user data is obtained by deleting the type user sub-data in the type user data corresponding to the mth ID type which has established a corresponding relationship with any user's trust identifier, 1≤m≤(M-1); S502, the identification association part and the system trust coefficient of the second user data are taken as the first input data, the data processing cycle threshold TL is acquired according to the trust level of the mth ID type, the data processing cycle number L is set to 1, and the first data processing is performed on the first input data in this step based on the TL and L before this step, to obtain the first output data corresponding to the mth ID type, wherein each piece of the first output data corresponding to the mth ID type at least saves the corresponding relationship between the ID identifier conforming to the mth ID type of the user and the trust identifier of the user; S503, the preset ID identifier-trust identifier corresponding table is updated based on the first output data corresponding to the mth ID type and the first user original data.

5. The method of claim 4, wherein, S500 further includes the following steps: S1, the second user original data of all users in N business systems at a second time point is acquired, each piece of second user original sub-data in the second user original data includes at least one ID identifier of the same user in the same business system; wherein the second time point is later than the first time point; S2, the preset ID identifier-trust identifier corresponding table is updated according to the second user original data.

6. The method of claim 5, wherein, S2 further includes the following contents: S3, the screening user data in the second user original data is acquired, wherein the screening user data is obtained by deleting the second user original sub-data in the second user original data which has established a corresponding relationship with any user's trust identifier; S4, the second type user data of M preset ID types is acquired based on the screening user data, wherein the M preset ID types are the first ID type and the (M-1) preset ID types. S5, associating the identification association part and the system trust coefficient of the second type user data corresponding to the first ID type in the screening user data as the first user data, performing according to S300 to obtain the first output data corresponding to the first ID type in the screening user data, wherein each of the first output data corresponding to the first ID type in the screening user data at least saves the corresponding relationship between one ID identification of the user conforming to the first ID type and the trust identification of the user; S6, updating the preset ID identification-trust identification corresponding table according to the first output data corresponding to the first ID type in the screening user data; S7, for the second type user data of (M-1) preset ID types different from the first ID type in the screening user data, according to the order from large to small of the preset ID type trust level, the second data processing is performed on the second type user data corresponding to the (M-1) preset ID types in turn.

7. The method of claim 1, wherein, The corresponding relationship between the ID identifications is represented in the form of a graph, wherein any one node in the graph represents an ID identification, and any two nodes with a corresponding relationship are connected by a line segment.

8. An apparatus for acquiring a user profile, the apparatus comprising a processor and a non-transitory computer readable storage medium storing at least one instruction or at least one program, wherein, The processor loads and executes the at least one instruction or at least one program to implement the method of any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores programs or instructions, which make the computer execute the method of any one of claims 1-7.

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