User credit information integration method and device, electronic equipment and readable medium

Abstract

The embodiment of the invention discloses a user credit information integration method and device, electronic equipment and a readable medium. A specific embodiment of the method comprises the following steps: acquiring a user information set of each user applying a preset client; performing identity recognition integration processing on each acquired user information set to obtain each piece of integrated user information; generating each same user identity code corresponding to each piece of integrated user information; generating a coding mapping relation table; generating unified user credit information corresponding to the integrated user information, and storing the unified user credit information to a preset storage device; marking each piece of generated unified user credit information to obtain each piece of label information corresponding to each piece of unified user credit information; and clustering and sending the unified user credit information and the label information to the preset clients based on the coding mapping relation table. According to the embodiment, the data quality of the integrated data is improved.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a method, device, electronic device, and computer-readable medium for integrating user credit information. Background Art

[0002] With the continuous development of big data and cloud computing technologies, technical support has been provided for data sharing and integration. User credit information integration is a technology for integrating and sharing the credit information of each user from each client (such as each B-end). At present, when integrating and sharing the credit information of each user from each client (such as each B-end), the method usually adopted is: integrating the credit information of each user from each client (such as each B-end) into a user credit information set for sharing.

[0003] However, when the above method is used to integrate and share the credit information of each user, the following technical problems often occur:

[0004] Since users can have different user identities on different clients (e.g., B-side), corresponding to different user credit information, integrating the user credit information from various clients (e.g., various B-sides) into a user credit information set for sharing will cause the same user to have multiple different identities and different user credit information, resulting in serious user identity fragmentation. At the same time, integrating the user credit information from various clients (e.g., various B-sides) into a user credit information set for sharing without labeling the user credit information will cause the integrated data of the shared user credit information to be more chaotic, and the data quality of the integrated data of the shared user credit information will be poor.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose a user credit information integration method, device, electronic device and computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for integrating user credit information, the method comprising: for a preset client corresponding to each preset client identifier in each preset client identifier, obtaining a user information set of each user who applies the preset client, wherein each user information in the user information set includes: user identity information, user credit information, and the user information corresponds to a user identifier and a preset client identifier; performing identity identification and integration processing on each obtained user information set to obtain each integrated user information, wherein each integrated user information in the each integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identifier of the same user in at least one preset client; generating a corresponding user information set corresponding to each integrated user information set; each same user identity code, wherein each integrated user information in the above-mentioned integrated user information corresponds one-to-one to each same user identity code in the above-mentioned same user identity code; based on the above-mentioned each integrated user information and the above-mentioned each same user identity code, a code mapping relationship table is generated; for each integrated user information in the above-mentioned each integrated user information, unified user credit information corresponding to the above-mentioned integrated user information is generated, and the above-mentioned unified user credit information is stored in a preset storage device; each generated unified user credit information is marked to obtain each label information corresponding to the above-mentioned each unified user credit information; based on the above-mentioned code mapping relationship table, each unified user credit information and each label information are clustered and sent to each preset client.

[0009] In a second aspect, some embodiments of the present disclosure provide a user credit information integration device, the device comprising: an acquisition unit, configured to acquire, for each preset client corresponding to each preset client identifier in each preset client identifier, a user information set of each user who applies the preset client, wherein each user information in the user information set includes: user identity information, user credit information, and the user information corresponds to a user identifier and a preset client identifier; an identity identification integration processing unit, configured to perform identity identification integration processing on each acquired user information set to obtain each integrated user information, wherein each integrated user information in the above-mentioned each integrated user information includes at least one user information, and the above-mentioned integrated user information corresponds to at least one user identifier of the same user in at least one preset client; a first generation unit, configured to generate each identical user information corresponding to each of the above-mentioned integrated user information User identity code, wherein each integrated user information in the above-mentioned integrated user information corresponds one-to-one to each same user identity code in the above-mentioned same user identity code; a second generating unit is configured to generate a code mapping relationship table based on the above-mentioned each integrated user information and the above-mentioned each same user identity code; a third generating unit is configured to generate unified user credit information corresponding to the above-mentioned integrated user information for each integrated user information in the above-mentioned integrated user information, and store the above-mentioned unified user credit information to a preset storage device; a labeling processing unit is configured to label the generated each unified user credit information to obtain each label information corresponding to the above-mentioned each unified user credit information; a clustering sending unit is configured to cluster the above-mentioned each unified user credit information and each label information based on the above-mentioned code mapping relationship table and send them to each preset client.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

[0012] The above-mentioned embodiments of the present disclosure have the following beneficial effects: through the user credit information integration method of some embodiments of the present disclosure, the phenomenon of user identity fragmentation is reduced and the data quality of the integrated data of user credit information is improved. Specifically, the reason for the serious fragmentation of user identity and the poor data quality of the integrated data of user credit information is that: since users can have different user identity identifiers on different clients (for example, B-end), corresponding to different user credit information. Integrating the various user credit information from various clients (for example, various B-ends) into a user credit information set for sharing will cause the same user to have multiple different identity identifiers and different user credit information, resulting in serious user identity fragmentation. At the same time, integrating the various user credit information from various clients (for example, various B-ends) into a user credit information set for sharing, without marking the user credit information, will cause the integrated data of the shared user credit information to be relatively chaotic, and the data quality of the integrated data of the shared user credit information is poor. Based on this, the user credit information integration method of some embodiments of the present disclosure, first, for each preset client corresponding to each preset client identifier in each preset client identifier, obtain the user information set of each user who applies the above preset client, wherein each user information in the above user information set includes: user identity information, user credit information, and the above user information corresponds to the user identifier and the preset client identifier. Thus, each user information set of each preset client can be obtained. Then, identity identification and integration processing is performed on each obtained user information set to obtain each integrated user information, wherein each integrated user information in the above integrated user information includes at least one user information, and the above integrated user information corresponds to at least one user identifier of the same user in at least one preset client. Thus, identity identification and integration processing can be performed on each user information set, and at least one user information of the same user in at least one preset client is integrated into an integrated user information, thereby reducing the phenomenon of user identity fragmentation. Generate each same user identity code corresponding to each integrated user information, wherein each integrated user information in the above integrated user information corresponds one-to-one to each same user identity code in the above same user identity code. Thus, each integrated user information of each same user can be encoded to generate each same user identity code corresponding to each same user, and a unique same user identity code is given to the same user from different clients. Then, based on the above-mentioned each integrated user information and the above-mentioned each same user identity code, a coding mapping relationship table is generated. Thus, a coding mapping relationship table representing the correspondence between the same user identity code and at least one user identifier of at least one preset client can be generated.Then, for each integrated user information in the above-mentioned integrated user information, a unified user credit information corresponding to the above-mentioned integrated user information is generated, and the above-mentioned unified user credit information is stored in a preset storage device. Thus, unified user credit information corresponding to each integrated user information can be generated. Then, each generated unified user credit information is marked to obtain each tag information corresponding to the above-mentioned unified user credit information. Thus, each unified user credit information can be marked, the meaning of each unified user credit information is clarified, the readability and availability of each unified user credit information are improved, data confusion is reduced, and data quality is improved. Based on the above-mentioned encoding mapping relationship table, the above-mentioned unified user credit information and each tag information are clustered and sent to each preset client. Thus, each unified user credit information and each tag information can be clustered and sent to each preset client. Also because in the process of integrating user credit information, by performing identity identification and integration processing on each user information set, at least one user information of the same user in at least one preset client is integrated into one integrated user information, and a unique same user identity code corresponding to the integrated user information is generated, the phenomenon of user identity fragmentation is reduced. At the same time, before sharing the unified user credit information, each unified user credit information is labeled to clarify the meaning of each unified user credit information, improve the readability and availability of each unified user credit information, reduce data confusion and improve data quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flow chart of some embodiments of the user credit information integration method according to the present disclosure;

[0015] Figure 2 is a schematic diagram of the structure of some embodiments of the user credit information integration device according to the present disclosure;

[0016] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0018] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] Figure 1 The process 100 of some embodiments of the user credit information integration method according to the present disclosure is shown. The user credit information integration method comprises the following steps:

[0024] Step 101: For a preset client corresponding to each preset client identifier in each preset client identifier, a user information set of each user who uses the preset client is obtained.

[0025] In some embodiments, the execution subject (e.g., server) of the user credit information integration method may obtain the user information set of each user who applies the preset client for each preset client corresponding to each preset client identifier in each preset client identifier. Wherein, each user information in the user information set includes: user identity information, user credit information, and the user information corresponds to the user identifier and the preset client identifier. The execution subject may obtain the user information set of each user who applies the preset client through a wired connection or a wireless connection. Wherein, the preset clients may be each B-end (e.g., online banking, lending platform, e-commerce platform, etc.). The users may be each C-end user of the preset client (e.g., preset B-end). The user identity information includes coded identity information and biometric data. The coded identity information may include at least one of the following: identity code, identity identifier, and user account. The biometric data may be data of the user's physical, physiological, behavioral, and other characteristics. The biometric data may be, but is not limited to, one of the following: fingerprint (e.g., fingerprint image), voiceprint, palmprint, iris, facial recognition feature (e.g., face image). The identity code may be the user's ID number. The identity identifier may be the user's name. The user account may be a personal account (e.g., a mobile phone number) registered and used by the user in the preset client. The user credit information may be the credit information of the user in the preset client (e.g., credit transaction information). The user identifier may be a user account or a user name. The preset client identifier may be the name of the preset client.

[0026] It should be noted that the above-mentioned wireless connection methods may include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0027] Step 102: Perform identity identification and integration processing on each acquired user information set to obtain each integrated user information.

[0028] In some embodiments, the execution subject may perform identity identification and integration processing on each acquired user information set to obtain each integrated user information, wherein each integrated user information in each integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identification of the same user in at least one preset client.

[0029] In some optional implementations of some embodiments, the execution subject may perform identity identification and integration processing on each acquired user information set through the following steps to obtain each integrated user information:

[0030] The first step is to determine the coded identity information included in each user information in the above-mentioned user information sets to obtain the coded identity information sets.

[0031] The second step is to perform format unification processing on each coded identity information in the above-mentioned coded identity information set to obtain standardized coded identity information after format unification processing. In practice, first, the above-mentioned execution subject can extract the identity code, identity identifier, and user account from the above-mentioned coded identity information in sequence through regular expression extraction. Then, the above-mentioned execution subject can arrange the extracted identity code, identity identifier, and user account in a preset arrangement order to obtain standardized coded identity information. As an example, the above-mentioned coded identity information can be "identity code: A, identity identifier: B", and the extracted identity code, identity identifier, and user account can be "A, B, Null". The above-mentioned preset arrangement order can be "identity code-identity identifier-user account". The standardized coded identity information can be "AB-Null".

[0032] The third step is to sort the obtained standardized coded identity information to obtain a standardized coded identity information sequence. In practice, the above execution entity can sequentially store the above standardized coded identity information to obtain a standardized coded identity information sequence.

[0033] In the fourth step, based on the standardized encoded identity information sequence, the following clustering steps are performed:

[0034] In the first sub-step, the similarity between the first standardized coded identity information in the standardized coded identity information sequence and each standardized coded identity information in the standardized coded identity information sequence other than the first standardized coded identity information is determined as each screening similarity. Each standardized coded identity information in each standardized coded identity information corresponds to each screening similarity in each screening similarity. Each screening similarity in the above screening similarities can be represented by Levenshtein distance or Jaccard similarity.

[0035] In the second sub-step, each screening similarity that satisfies a preset screening condition among the screening similarities is determined as each target similarity, wherein the preset screening condition may be that the screening similarity is greater than a preset value.

[0036] In the third sub-step, each standardized coded identity information corresponding to the first standardized coded identity information and each target similarity is determined as a standardized coded identity information clustering group.

[0037] The fourth sub-step is to delete each standardized coded identity information in the standardized coded identity information cluster group from the standardized coded identity information sequence to update the standardized coded identity information sequence.

[0038] The fifth sub-step is, in response to determining that the updated standardized coded identity information sequence is not empty, executing the above clustering step again based on the updated standardized coded identity information sequence.

[0039] In a fifth step, in response to determining that the updated standardized coded identity information sequence is empty, the determined standardized coded identity information cluster groups are determined as a standardized coded identity information cluster group set.

[0040] The sixth step is to perform data correction and filling processing on the above-mentioned user information sets based on the above-mentioned standardized coded identity information clustering group set to obtain each corrected user information set, wherein each user information in the above-mentioned user information set corresponds one-to-one to each corrected user information set in the above-mentioned corrected user information set.

[0041] The seventh step is to generate various integrated user information based on the above-mentioned various modified user information sets.

[0042] Since the identity code (for example, the ID number) is an important and indispensable information of the user's identity information, the user information in each user information set obtained from each preset client often has a missing or incorrect identity code, resulting in incomplete user identity information. When filling and correcting the missing or incorrect identity code, the conventional solution is generally: from the various biometric data of all users, match the biometric data that is most similar to the biometric data corresponding to the missing or incorrect identity code, and use the identity code corresponding to the most similar biometric data to fill and correct the missing or incorrect identity code.

[0043] The above conventional solutions still have the following problems: the amount of biometric data of all users is usually huge, and a large amount of data calculation is required to match the biometric data most similar to the biometric data corresponding to the missing or erroneous identity code from the biometric data of all users. At the same time, the identity code corresponding to the most similar biometric data matched may also be missing or erroneous, resulting in missing and erroneous identity codes after filling and correction, and the data correction and filling efficiency is low, so the data correction and filling process needs to be performed again. The large amount of data calculation and the low data correction and filling efficiency increase the waste of computer computing resources.

[0044] In the face of the above technical problems, the inventors decided to adopt the following solutions:

[0045] In some optional implementations of some embodiments, the execution subject may perform data correction and filling processing on each of the user information sets based on the standardized coded identity information clustering group set through the following steps to obtain each corrected user information set:

[0046] In the first step, for each user identity information in each of the above user information sets, perform the following steps:

[0047] In the first sub-step, the standardized coded identity information corresponding to the above user identity information is determined as the target standardized coded identity information.

[0048] In the second sub-step, the standardized coded identity information cluster group including the target standardized coded identity information in the standardized coded identity information cluster group set is determined as the target standardized coded identity information cluster group.

[0049] The third sub-step is, in response to determining that the user identity information includes an identity code, determining each identity code included in the target standardized coded identity information cluster group as each target identity code.

[0050] In a fourth sub-step, the number of target identity codes that are the same as the above identity code among the above target identity codes is determined as the target number.

[0051] In a fifth sub-step, in response to determining that the user identity information does not include an identity code or in response to determining that the target number is less than or equal to a preset value, each user information in the user information set corresponding to the target standardized coded identity information cluster group is determined as each reference user information. For example, the preset value may be 2.

[0052] The sixth sub-step is to determine each biometric feature data included in the above-mentioned each reference user information.

[0053] In the seventh sub-step, the biometric data corresponding to the user identity information in each of the above user information sets is determined as the biometric data to be compared.

[0054] In the eighth sub-step, the above-mentioned biometric data are compared with the above-mentioned biometric data to be compared to obtain each target biometric data. In practice, for each biometric data in each biometric data, the above-mentioned execution subject can extract a first extracted feature vector representing the above-mentioned biometric data from the above-mentioned biometric data to obtain each first extracted feature vector corresponding to the above-mentioned biometric data. Then, the above-mentioned execution subject can extract a second extracted feature vector representing the biometric data to be compared from the above-mentioned biometric data to be compared. Afterwards, the above-mentioned execution subject can determine the similarity between the above-mentioned first extracted feature vectors and the above-mentioned second extracted feature vectors as each comparison similarity. Then, the above-mentioned execution subject can determine each comparison similarity whose comparison similarity value is greater than or equal to the preset similarity among the above-mentioned comparison similarities as each target comparison similarity. Afterwards, the above-mentioned execution subject can determine each biometric data corresponding to each target comparison similarity pair as each target biometric data. Among them, the above-mentioned execution subject can extract the first extracted feature vector from the above-mentioned biometric data through the biometric recognition technology, and the above-mentioned execution subject can extract the second extracted feature vector from the above-mentioned biometric data to be compared through the biometric recognition technology. The above comparison similarity can be expressed by cosine similarity.

[0055] A ninth sub-step is to determine each reference user information corresponding to each target biometric feature data in the reference user information as each target reference user information.

[0056] The tenth sub-step is to perform filling and correction processing on the user identity information based on the above-mentioned target reference user information to update the user information sets. In practice, the execution subject may determine the identity codes included in the above-mentioned target reference user information as the filling identity codes. Afterwards, the execution subject may group the filling codes with the same filling codes in the filling codes into a group to obtain the filling code groups. Then, the execution subject may determine the filling code group with the largest number of filling codes as the code group to be filled. Finally, in response to determining that the user identity information does not include the identity code, the execution subject may add a filling code in the code group to be filled to the user identity information to update the user information where the user identity information is located. In response to determining that the user identity information includes the identity code, the execution subject may replace the identity code included in the user identity information with the filling code to update the user information where the user identity information is located.

[0057] In the second step, each updated user information set is determined as each modified user information set.

[0058] The above technical solution and its related contents, as an inventive point of the embodiment of the present disclosure, solve the technical problem "the ultimate problem of computer computing power resource waste". The factors that lead to the waste of computer computing power resources are often as follows: Usually, the amount of data of each biometric data of all users is huge. It is necessary to perform a large amount of data operations to match the biometric data most similar to the biometric data corresponding to the missing or erroneous identity code from the biometric data of all users. At the same time, the identity code corresponding to the most similar biometric data matched may also be missing or erroneous, resulting in missing and erroneous identity codes after filling and correction. The data correction filling efficiency is low, and the data correction filling process needs to be performed again. A large amount of data operations and low data correction filling efficiency increase the waste of computer computing power resources. If the above factors are solved, the effect of reducing the waste of computer computing power resources can be achieved. In order to achieve this effect, in the first step, for each user identity information in the above user information sets, the following steps are performed: In the first sub-step, the standardized coded identity information corresponding to the above user identity information is determined as the target standardized coded identity information. Thus, the target standardized coded identity information used to determine the target standardized coded identity information cluster group can be obtained. In the second sub-step, the standardized coded identity information cluster group including the target standardized coded identity information in the standardized coded identity information cluster group is determined as the target standardized coded identity information cluster group. Thus, a target standardized coded identity information cluster group containing the target standardized coded identity information and having information similar to the target standardized coded identity information can be obtained. In the third sub-step, in response to determining that the user identity information includes an identity code, each identity code included in the target standardized coded identity information cluster group is determined as each target identity code. Thus, each target identity code used to determine the target number can be obtained. In the fourth sub-step, the number of target identity codes identical to the identity code in the target standardized coded identity information cluster group is determined as the target number. Thus, the number of each target identity code identical to the identity code in the target standardized coded identity information cluster group can be determined, and the target standardized coded identity information cluster group is an information group similar to the target standardized coded identity information. In the fifth sub-step, in response to determining that the user identity information does not include an identity code or in response to determining that the target number is less than or equal to a preset value, each user information corresponding to the target standardized coded identity information cluster group in the user information set is determined as each reference user information. Thus, when the identity code in the user identity information is missing or there is a possibility of error in the identity code, each reference user information that is relatively similar to the coded identity information of the target standardized coded identity information is determined within a smaller cluster range. The sixth sub-step is to determine each biometric feature data included in the above reference user information.Thus, when the identity code in the user identity information is missing or there is a possibility that the identity code is wrong, the various biometric data included in each reference user information is determined within a smaller clustering range. The seventh sub-step is to determine the biometric data corresponding to the user identity information in the above-mentioned user information set as the biometric data to be compared. Thus, the biometric data to be compared can be used to fill and correct the user identity information with the possibility that the identity code is missing or there is an error in the identity code. The eighth sub-step is to compare the above-mentioned biometric data with the above-mentioned biometric data to be compared to obtain each target biometric data. Thus, the various biometric data within a smaller clustering range (that is, within the range of similar user groups after clustering) can be targetedly compared with the biometric data to be compared, and the target biometric data that is relatively similar to the biometric data to be compared can be matched. Among the various biometric data of the similar user groups after clustering, the target biometric data that is relatively similar to the missing or erroneous biometric data to be compared is matched, thereby reducing the amount of data calculation in the comparison and matching process. The ninth sub-step is to determine the reference user information corresponding to the target biometric data in the reference user information as the target reference user information. In this way, the target reference user information that is relatively similar to the identity information of the user identity information with the possibility of missing identity code or identity code error can be obtained. The tenth sub-step is to perform filling and correction processing on the user identity information based on the target reference user information to update the user information sets. In this way, the user identity information can be filled and corrected by the target reference user information that is relatively similar to the identity information of the user identity information with the possibility of missing identity code or identity code error, thereby reducing the impact of the loss or error of individual single identity code (i.e., the identity code corresponding to the most similar biometric data) on the filling and correction, and improving the data correction and filling efficiency. The second step is to determine the updated user information sets as the corrected user information sets. In the process of data correction and filling processing for each user information set, the biometric data of the clustered similar user groups are compared, thereby reducing the amount of data calculation in the comparison and matching process. By generating reference user information for each target, and filling and correcting the user identity information based on the reference user information, the impact of the loss or error of individual single identity codes on the filling and correction is reduced, the efficiency of data correction and filling is improved, the number of re-filling and correction times is reduced, and the waste of computer computing resources is reduced.

[0059] In some optional implementations of some embodiments, the execution subject may generate each integrated user information based on each modified user information set through the following steps:

[0060] In the first step, the identity code included in each modified user information of each modified user information set is determined as the initial cluster code to obtain an initial cluster code set.

[0061] In the second step, the above initial cluster code set is deduplicated to obtain a cluster code set.

[0062] In the third step, for each cluster code in the above cluster code set, perform the following integration steps:

[0063] In the first sub-step, at least one modified user information including the cluster coding in each modified user information set is determined as a modified user information cluster.

[0064] In the second sub-step, at least one piece of user information corresponding to the modified user information cluster in each of the user information sets is determined as integrated user information.

[0065] Step 103: Generate respective identical user identity codes corresponding to respective integrated user information.

[0066] In some embodiments, the execution subject may generate respective same user identity codes corresponding to the respective integrated user information, wherein each integrated user information in the respective integrated user information corresponds one-to-one to each same user identity code in the respective same user identity codes.

[0067] In some optional implementations of some embodiments, after generating the same user identity codes corresponding to the integrated user information, the execution subject may further perform the following steps:

[0068] In the first step, for each integrated user information in each integrated user information, perform the following encryption storage steps:

[0069] In the first sub-step, the same user identity code corresponding to the integrated user information among the above-mentioned same user identity codes is determined as the target user identity code.

[0070] The second sub-step is to obtain the pre-stored encryption algorithm information from the preset database. The preset database may be a MySQL database for storing encryption algorithm information. The encryption algorithm information may represent a preset encryption algorithm. For example, the preset encryption algorithm may be an RSA (Rivest-Shamir-Adleman) encryption algorithm.

[0071] The third sub-step is to perform an encryption operation on the integrated user information according to the encryption algorithm information to obtain encrypted integrated user information. The encrypted integrated user information may be information obtained by encrypting the integrated user information.

[0072] The fourth sub-step is to store the encrypted integrated user information in a preset storage device. The storage tag of the encrypted integrated user information is the target user identity code. The preset storage device may be a storage device for storing the encrypted integrated user information and the unified user credit information (e.g., a database or hard disk for storing data).

[0073] In some optional implementations of some embodiments, the execution subject may generate the same user identity codes corresponding to the above-mentioned integrated user information through the following steps:

[0074] The first step is to encode each of the above integrated user information to obtain a code corresponding to the above integrated user information. In practice, the above execution subject may encode the above integrated user information through a hash function to obtain a code corresponding to the above integrated user information. Alternatively, the above execution subject may encode the above integrated user information through a UUID generation algorithm to obtain a code corresponding to the above integrated user information.

[0075] In the second step, each generated code is determined as each identical user identity code corresponding to each of the above-mentioned integrated user information.

[0076] Step 104: Generate a code mapping relationship table based on each integrated user information and each identical user identity code.

[0077] In some embodiments, the execution entity may generate a code mapping relationship table based on the integrated user information and the same user identity codes.

[0078] In some optional implementations of some embodiments, the execution subject may generate a code mapping relationship table based on the above-mentioned integrated user information and the above-mentioned same user identity codes through the following steps:

[0079] In the first step, for each integrated user information in the above integrated user information, the following mapping relationship table generation steps are performed:

[0080] In a first sub-step, the same user identity code corresponding to the integrated user information among the above-mentioned same user identity codes is determined as a target same user identity code.

[0081] The second sub-step is to determine at least one user identifier corresponding to at least one user information included in the integrated user information as at least one same user identifier. The at least one same user identifier is at least one user identifier of the same user in at least one preset client, and the target same user identity code corresponds to the at least one same user identifier.

[0082] The third sub-step is to determine at least one preset client identifier corresponding to at least one user information included in the integrated user information, wherein the target same user identity code corresponds to the at least one preset client identifier, and each of the at least one same user identifier corresponds to each of the at least one preset client identifier.

[0083] The fourth sub-step is to store the target same user identity code, the at least one same user identifier, the at least one preset client identifier, and the correspondence between the three in a pre-created data table to update the data table. The correspondence between the three can be the correspondence between the target same user identity code, the at least one same user identifier, and the at least one preset client identifier. As an example, the correspondence between the three can be the correspondence between the target same user identity code and the at least one same user identifier, the target same user identity code and the at least one preset client identifier, and each of the at least one same user identifier corresponds to each of the at least one preset client identifier.

[0084] The second step is to determine the updated data table as a coding mapping relationship table.

[0085] Step 105 : for each piece of integrated user information, generate unified user credit information corresponding to the integrated user information, and store the unified user credit information in a preset storage device.

[0086] In some embodiments, the execution subject may generate unified user credit information corresponding to each of the integrated user information, and store the unified user credit information in a preset storage device. In practice, the execution subject may determine at least one user credit information included in the integrated user information as unified user credit information.

[0087] Step 106: label each generated unified user credit information to obtain each label information corresponding to each unified user credit information.

[0088] In some embodiments, the execution entity may label each generated unified user credit information to obtain each label information corresponding to each unified user credit information. In practice, the execution entity may label each generated unified user credit information through a pre-trained label model to obtain each label information corresponding to each unified user credit information. For example, the label model may be a large credit scoring model. Each of the label information may represent a label of the unified user credit information. For example, the label information may be "good credit", "high credit risk", etc.

[0089] Step 107: Based on the encoding mapping relationship table, each unified user credit information and each tag information is clustered and sent to each preset client.

[0090] In some embodiments, the execution entity may cluster and send the unified user credit information and tag information to each preset client based on the encoding mapping relationship table.

[0091] After generating each unified user credit information and each tag information, each unified user credit information and each tag information needs to be shared with each preset client. However, directly sharing all the generated unified user credit information and all the tag information with each preset client does not take into account the actual needs of each client for the unified user credit information and its corresponding tag information. Since some of the unified user credit information and all the tag information do not have corresponding users on some preset clients, when the user credit information and its corresponding tag information that do not have corresponding users on the preset client are sent to the above-mentioned client, it will cause a waste of network resources.

[0092] In some optional implementations of some embodiments, the execution subject may cluster and send the above-mentioned unified user credit information and each tag information to each preset client based on the above-mentioned encoding mapping relationship table through the following steps:

[0093] In the first step, each preset client identifier included in the above encoding mapping relationship table is determined as each target preset client identifier.

[0094] In the second step, deduplication processing is performed on the above-mentioned target preset client identifiers to obtain deduplication preset client identifiers.

[0095] In the third step, for each of the above-mentioned deduplication preset client identifiers, the following clustering and sending process is performed:

[0096] In a first sub-step, at least one target same user identity code corresponding to the above-mentioned code mapping relationship table and the above-mentioned deduplication preset client identifier is determined as at least one screening same user identity code.

[0097] In the second sub-step, at least one unified user credit information corresponding to the at least one screened same user identity code among the above-mentioned unified user credit information is determined as at least one unified user credit information to be sent.

[0098] In a third sub-step, the tag information corresponding to each unified user credit information in the at least one unified user credit information is determined as the tag information to be sent, so as to obtain at least one tag information to be sent.

[0099] The fourth sub-step is to send the at least one unified user credit information to be sent and the at least one tag information to be sent to the preset client corresponding to the deduplication preset client identifier.

[0100] The above technical solution and its related contents, as an inventive point of the embodiment of the present disclosure, solve the technical problem "the ultimate problem of waste of network bandwidth resources". The factors that lead to the waste of network bandwidth resources are often as follows: directly sharing all the generated unified user credit information and all the tag information to each preset client without considering the actual needs of each client for the unified user credit information and its corresponding tag information. Since some of the unified user credit information and its corresponding tag information in all the unified user credit information and all the tag information do not have corresponding users on some preset clients, when the user credit information and its corresponding tag information that do not have corresponding users on the preset client are sent to the above client, it will cause a waste of network resources. If the above factors are solved, the effect of reducing the waste of network bandwidth resources can be achieved. In order to achieve this effect, first, the preset client identifiers included in the above encoding mapping relationship table are determined as the target preset client identifiers. Then, the above target preset client identifiers are deduplicated to obtain the deduplicated preset client identifiers. Thus, the deduplicated preset client identifiers of the preset clients that need to share the unified user credit information can be obtained. Afterwards, for each of the above-mentioned deduplication preset client identifiers, the following clustering and sending processing is performed: the first step is to determine the at least one target same user identity code corresponding to the above-mentioned deduplication preset client identifier in the above-mentioned coding mapping relationship table as at least one screening same user identity code. Thus, the at least one target same user identity code of at least one user of the preset client corresponding to the deduplication preset client identifier can be determined through the coding mapping relationship table. The second step is to determine at least one unified user credit information corresponding to the above-mentioned at least one screening same user identity code in the above-mentioned unified user credit information as at least one unified user credit information to be sent. Thus, considering the actual needs of the preset client for the unified user credit information, at least one unified user credit information to be sent can be screened out from each unified user credit information. The third step is to determine the tag information to be sent by the tag information corresponding to each unified user credit information in the above-mentioned at least one unified user credit information, and obtain at least one tag information to be sent. Thus, at least one tag information to be sent required by the preset client can be obtained. The fourth step is to send the above-mentioned at least one unified user credit information to be sent and the above-mentioned at least one tag information to be sent to the preset client corresponding to the above-mentioned deduplication preset client identifier. Thus, at least one piece of unified user credit information to be sent and the at least one piece of label information to be sent can be sent to a preset client.Also, when sharing each unified user credit information and each tag information to each preset client, the actual needs of the preset client for the unified user credit information and its corresponding tag information are taken into consideration, thereby reducing the possibility of sending user credit information and its corresponding tag information beyond the actual needs of the preset client to the preset client, thereby reducing the waste of network resources.

[0101] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: through the user credit information integration method of some embodiments of the present disclosure, the phenomenon of user identity fragmentation is reduced and the data quality of user credit integration data is improved. Specifically, the reason for the serious fragmentation of user identity and the poor data quality of user credit integration data is that: since users can have different user identity identifiers on different clients (for example, B-end), corresponding to different user credit information. Integrating the various user credit information from various clients (for example, various B-ends) into a user credit information set for sharing will cause the same user to have multiple different identity identifiers and different user credit information, resulting in serious user identity fragmentation. At the same time, integrating the various user credit information from various clients (for example, various B-ends) into a user credit information set for sharing, without marking the user credit information, will cause the integrated data of the shared user credit information to be relatively chaotic, and the data quality of the integrated data of the shared user credit information is poor. Based on this, the user credit information integration method of some embodiments of the present disclosure, first, for each preset client corresponding to each preset client identifier in each preset client identifier, obtain the user information set of each user who applies the above preset client, wherein each user information in the above user information set includes: user identity information, user credit information, and the above user information corresponds to the user identifier and the preset client identifier. Thus, each user information set of each preset client can be obtained. Then, identity identification and integration processing is performed on each obtained user information set to obtain each integrated user information, wherein each integrated user information in the above integrated user information includes at least one user information, and the above integrated user information corresponds to at least one user identifier of the same user in at least one preset client. Thus, identity identification and integration processing can be performed on each user information set, and at least one user information of the same user in at least one preset client is integrated into an integrated user information, thereby reducing the phenomenon of user identity fragmentation. Generate each same user identity code corresponding to each integrated user information, wherein each integrated user information in the above integrated user information corresponds one-to-one to each same user identity code in the above same user identity code. Thus, each integrated user information of each same user can be encoded to generate each same user identity code corresponding to each same user, and a unique same user identity code is given to the same user from different clients. Then, based on the above-mentioned each integrated user information and the above-mentioned each same user identity code, a coding mapping relationship table is generated. Thus, a coding mapping relationship table representing the correspondence between the same user identity code and at least one user identifier of at least one preset client can be generated.Then, for each integrated user information in the above-mentioned integrated user information, a unified user credit information corresponding to the above-mentioned integrated user information is generated, and the above-mentioned unified user credit information is stored in a preset storage device. Thus, unified user credit information corresponding to each integrated user information can be generated. Then, each generated unified user credit information is marked to obtain each tag information corresponding to the above-mentioned unified user credit information. Thus, each unified user credit information can be marked, the meaning of each unified user credit information is clarified, the readability and availability of each unified user credit information are improved, data confusion is reduced, and data quality is improved. Based on the above-mentioned encoding mapping relationship table, the above-mentioned unified user credit information and each tag information are clustered and sent to each preset client. Thus, each unified user credit information and each tag information can be clustered and sent to each preset client. Also because in the process of integrating user credit information, by performing identity identification and integration processing on each user information set, at least one user information of the same user in at least one preset client is integrated into one integrated user information, and a unique same user identity code corresponding to the integrated user information is generated, the phenomenon of user identity fragmentation is reduced. At the same time, before sharing the unified user credit information, each unified user credit information is labeled to clarify the meaning of each unified user credit information, improve the readability and availability of each unified user credit information, reduce data confusion and improve data quality.

[0102] Further references Figure 2 As an implementation of the methods shown in the figures, the present disclosure provides some embodiments of a user credit information integration device. These device embodiments are similar to Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0103] like Figure 2As shown, the user credit information integration device 200 of some embodiments includes: an acquisition unit 201, an identity recognition and integration processing unit 202, a first generation unit 203, a second generation unit 204, a third generation unit 205, a labeling processing unit 206 and a clustering sending unit 207. The acquisition unit 201 is configured to acquire, for each preset client corresponding to each preset client identifier in each preset client identifier, a user information set of each user who applies the preset client, wherein each user information in the user information set includes: user identity information and user credit information, and the user information corresponds to a user identifier and a preset client identifier; the identity recognition and integration processing unit 202 is configured to perform identity recognition and integration processing on each acquired user information set to obtain each integrated user information, wherein each integrated user information in the integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identifier of the same user in at least one preset client; the first generation unit 203 is configured to generate each same user identity code corresponding to each integrated user information, wherein each integrated user information is a user information set corresponding to at least one user identifier of the same user in at least one preset client; Each integrated user information in the user information corresponds to each same user identity code in the above-mentioned same user identity code; the second generation unit 204 is configured to generate a code mapping relationship table based on the above-mentioned each integrated user information and the above-mentioned each same user identity code; the third generation unit 205 is configured to generate unified user credit information corresponding to the above-mentioned integrated user information for each integrated user information in the above-mentioned integrated user information, and store the above-mentioned unified user credit information to a preset storage device; the marking processing unit 206 is configured to mark the generated each unified user credit information to obtain each label information corresponding to the above-mentioned each unified user credit information; the cluster sending unit 207 is configured to cluster the above-mentioned each unified user credit information and each label information based on the above-mentioned code mapping relationship table and send them to each preset client.

[0104] It is understood that the units described in the device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 200 and the units contained therein, and will not be described in detail here.

[0105] Reference below Figure 3 , which shows a structural schematic diagram of an electronic device 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

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

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

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

[0109] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination thereof.

[0110] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0111] The computer-readable medium may be included in the electronic device; or it may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: for each preset client identifier corresponding to each preset client identifier, obtains a user information set of each user who uses the preset client, wherein each user information in the user information set includes: user identity information, user credit information, and the user information corresponds to a user identifier and a preset client identifier; performs identity identification and integration processing on each obtained user information set to obtain each integrated user information, wherein each integrated user information in the integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identifier of the same user in at least one preset client; generates information corresponding to each integrated user identifier. each same user identity code corresponding to the user information, wherein each integrated user information in the above-mentioned integrated user information corresponds one-to-one to each same user identity code in the above-mentioned same user identity code; based on the above-mentioned each integrated user information and the above-mentioned each same user identity code, a code mapping relationship table is generated; for each integrated user information in the above-mentioned each integrated user information, unified user credit information corresponding to the above-mentioned integrated user information is generated, and the above-mentioned unified user credit information is stored in a preset storage device; each generated unified user credit information is marked to obtain each label information corresponding to the above-mentioned each unified user credit information; based on the above-mentioned code mapping relationship table, each unified user credit information and each label information are clustered and sent to each preset client.

[0112] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0113] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0114] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including an acquisition unit, an identity recognition integration process, a first generation unit, a second generation unit, a third generation unit, a labeling processing unit, and a clustering sending unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances, for example, the acquisition unit may also be described as "a unit for acquiring a user information set of each user who applies the above-mentioned preset client for each preset client identifier corresponding to each preset client identifier".

[0115] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0116] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of technical features, but should also cover other technical solutions formed by any combination of technical features or their equivalent features without departing from the inventive concept. For example, a technical solution formed by replacing the features with (but not limited to) the technical features with similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for integrating user credit information, comprising: For each preset client corresponding to each preset client identifier in each preset client identifier, obtaining a user information set of each user who uses the preset client, wherein each user information in the user information set includes: user identity information and user credit information, and the user information corresponds to the user identifier and the preset client identifier; Performing identity identification and integration processing on each of the acquired user information sets to obtain each integrated user information, wherein each of the integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identification of the same user in at least one preset client; Generating respective same user identity codes corresponding to the respective integrated user information, wherein each integrated user information in the respective integrated user information corresponds one-to-one to each same user identity code in the respective same user identity codes; Generate a code mapping relationship table based on the respective integrated user information and the respective same user identity codes; For each integrated user information in the integrated user information, generating unified user credit information corresponding to the integrated user information, and storing the unified user credit information in a preset storage device; Labeling each generated unified user credit information to obtain each label information corresponding to the each unified user credit information; Based on the encoding mapping relationship table, the unified user credit information and the tag information are clustered and sent to the preset clients.

2. The method according to claim 1, wherein: After generating the respective same user identity codes corresponding to the respective integrated user information, the method further includes: For each integrated user information in each integrated user information, perform the following encryption storage steps: Determine the same user identity code corresponding to the integrated user information among the same user identity codes as the target user identity code; Acquire pre-stored encryption algorithm information from the preset database; According to the encryption algorithm information, the integrated user information is encrypted to obtain encrypted integrated user information; The encrypted integrated user information is stored in a preset storage device, wherein the storage tag of the encrypted integrated user information is the target user identity code.

3. The method according to claim 1, wherein: The generating of each identical user identity code corresponding to each integrated user information includes: For each piece of integrated user information in the integrated user information, encoding the integrated user information to obtain a code corresponding to the integrated user information; The generated codes are determined as the same user identity codes corresponding to the integrated user information.

4. The method according to claim 1, wherein: Each user identity information in each user information set includes: coded identity information, biometric data, and the identity identification and integration processing of each acquired user information set is performed to obtain each integrated user information, including: Determine the coded identity information included in each user information in each user information set to obtain a coded identity information set; Performing format unification processing on each coded identity information in the coded identity information set to obtain standardized coded identity information after format unification processing; Sorting the obtained standardized coded identity information to obtain a standardized coded identity information sequence; Based on the standardized encoded identity information sequence, the following clustering steps are performed: Determine the similarities between the first standardized coded identity information in the standardized coded identity information sequence and each standardized coded identity information in the standardized coded identity information sequence except the first standardized coded identity information as each screening similarity, wherein each standardized coded identity information in each standardized coded identity information corresponds to each screening similarity in each screening similarity; Determine each screening similarity that satisfies a preset screening condition among the screening similarities as each target similarity; Determine each standardized coded identity information corresponding to the first standardized coded identity information and each target similarity as a standardized coded identity information clustering group; Deleting each standardized coded identity information in the standardized coded identity information cluster group from the standardized coded identity information sequence to update the standardized coded identity information sequence; In response to determining that the updated standardized coded identity information sequence is not empty, performing the clustering step again based on the updated standardized coded identity information sequence; In response to determining that the updated standardized coded identity information sequence is empty, determining the determined respective standardized coded identity information cluster groups as a standardized coded identity information cluster group set; Based on the standardized coded identity information cluster group set, performing data correction and filling processing on each of the user information sets to obtain each corrected user information set, wherein each user information in each of the user information sets corresponds one-to-one to each corrected user information set in each of the corrected user information sets; Based on the respective modified user information sets, respective integrated user information are generated.

5. The method according to claim 4, wherein: Each modified user information in each modified user information set includes user identity information and user credit information, wherein the user identity information includes coded identity information and biometric data, wherein the coded identity information includes an identity code, and generating each integrated user information based on each modified user information set includes: Determine the identity code included in each modified user information of each modified user information set as the initial cluster code to obtain an initial cluster code set; Performing deduplication processing on the initial cluster code set to obtain a cluster code set; For each cluster code in the cluster code set, perform the following integration steps: Determining at least one modified user information containing the cluster code in each modified user information set as a modified user information cluster; At least one piece of user information in each of the user information sets corresponding to the modified user information cluster is determined as integrated user information.

6. The method according to claim 1, wherein: The generating a code mapping relationship table based on the respective integrated user information and the respective same user identity codes comprises: For each piece of integrated user information, the following mapping relationship table generation step is performed: Determine the same user identity code corresponding to the integrated user information among the same user identity codes as the target same user identity code; Determine at least one user identifier corresponding to at least one user information included in the integrated user information as at least one same user identifier, wherein the at least one same user identifier is at least one user identifier of the same user in at least one preset client, and the target same user identity code corresponds to the at least one same user identifier; Determine at least one preset client identifier corresponding to at least one user information included in the integrated user information, wherein the target same user identity code corresponds to the at least one preset client identifier, and each same user identifier in the at least one same user identifier corresponds to each preset client identifier in the at least one preset client identifier in a one-to-one manner; The target same user identity code, the at least one same user identifier, the at least one preset client identifier, and the correspondence between the three are stored in a pre-created data table to update the data table; The updated data table is determined as a coding mapping relationship table.

7. A user credit information integration device, comprising: The obtaining unit is configured to obtain, for each preset client corresponding to each preset client identifier in each preset client identifier, a user information set of each user who uses the preset client, wherein each user information in the user information set includes: user identity information and user credit information, and the user information corresponds to the user identifier and the preset client identifier; An identity identification and integration processing unit is configured to perform identity identification and integration processing on each acquired user information set to obtain each integrated user information, wherein each integrated user information in each integrated user information includes at least one user information, and the integrated user information corresponds to at least one user identification of the same user in at least one preset client; A first generating unit is configured to generate respective same user identity codes corresponding to the respective integrated user information, wherein each integrated user information in the respective integrated user information corresponds to each same user identity code in the respective same user identity codes in a one-to-one correspondence; A second generating unit is configured to generate a code mapping relationship table based on the respective integrated user information and the respective same user identity codes; a third generating unit configured to generate, for each integrated user information in the integrated user information, unified user credit information corresponding to the integrated user information, and store the unified user credit information in a preset storage device; A labeling processing unit is configured to perform labeling processing on each generated unified user credit information to obtain each label information corresponding to the each unified user credit information; The cluster sending unit is configured to cluster and send the unified user credit information and the tag information to each preset client based on the encoding mapping relationship table.

8. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

Images