CN115311063A - Identity information auditing method and device - Google Patents
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- CN115311063A CN115311063A CN202210928858.9A CN202210928858A CN115311063A CN 115311063 A CN115311063 A CN 115311063A CN 202210928858 A CN202210928858 A CN 202210928858A CN 115311063 A CN115311063 A CN 115311063A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
- G06F40/295—Named entity recognition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
Abstract
The embodiment of the invention provides an identity information auditing method and device, wherein intimacy probability and authenticity probability are generated through contact information filled by a user, and contact information of a target user and target user information are obtained; the contact information comprises contact names and telephone numbers; and generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user. According to the technical scheme provided by the application and the model, the intimacy between each contact and the client and whether the mobile phone number of each contact is effective or not are effectively identified, and the model can be continuously trained based on the existing data, so that the accuracy is continuously improved, and the intimacy of the client is effectively identified; based on such scene scheme, not only can effectual reduction cost of labor, raise the efficiency, but also can accurately discern customer's risk degree.
Description
Technical Field
The invention relates to the field of information identification, in particular to an identity information auditing method and device.
Background
In the existing consumption financial business, a standard business operation mode is that a client fills in a contact person, a mobile phone number format of the client is verified, and then a creditor selectively dials up the linkability of the client based on the contact person filled in by the client, so that all the contact persons cannot be covered, and the accuracy is greatly uncertain.
Disclosure of Invention
In view of the above problems, the present application is provided to provide an identity information auditing method and apparatus for overcoming the problems or at least partially solving the problems, including:
an identity information auditing method, which generates intimacy probability and authenticity probability through contact information filled by a user, comprises the following steps:
acquiring contact person information and target user information of a target user; the contact information comprises contact names and telephone numbers;
and generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
Preferably, the step of generating the affinity probability and the authenticity probability according to the contact information of the target user and the information of the target user includes:
generating intimacy probability according to the contact names and the target user information;
and generating authenticity probability according to the telephone number.
Preferably, the step of generating affinity probability according to the contact name and the target user information includes:
performing preliminary analysis according to the contact name and the target user information to generate a first probability;
if the first probability is larger than zero and smaller than one, carrying out secondary analysis according to the contact name to generate a second probability;
and if the second probability is larger than zero and smaller than one, reversing according to the contact name to generate the intimacy probability.
Preferably, the step of performing preliminary analysis to generate a first probability according to the contact name and the target user information includes:
processing special characters according to the contact names and the target user information to generate preprocessing information;
performing relation judgment according to the preprocessing information to generate the first probability; wherein the relationships include a direct relationship, a non-direct relationship, a weak relationship, a degree, a ranking, a negative direction, and a mutual exclusion.
Preferably, the step of performing a secondary analysis according to the contact name to generate a second probability includes:
performing language confirmation according to the contact name to generate the second probability; wherein the language confirmation comprises address, circus, last name and entity analysis.
Preferably, if the first probability is zero, performing peer-to-peer analysis according to the contact name and the target user information to generate the intimacy probability.
Preferably, the step of generating the authenticity probability from the telephone number comprises:
and calculating the authenticity of the telephone number through a likelihood function according to the telephone number to generate the authenticity probability.
In order to realize the application, the method further comprises an identity information auditing device which generates intimacy probability and authenticity probability through contact information filled by a user, and is characterized by comprising the following steps:
the acquisition module is used for acquiring the contact information of the target user and the target user information; the contact information comprises contact names and telephone numbers;
and the generating module is used for generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
The application also includes an electronic device including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program, when executed by the processor, implements the steps of the identity information auditing method.
To implement the present application, a computer-readable storage medium stores thereon a computer program, which when executed by a processor implements the steps of the identity information auditing method.
The application has the following advantages:
in the embodiment of the application, the intimacy probability and the authenticity probability are generated through the contact information filled in by the user, and the contact information of the target user and the target user information are obtained; the contact information comprises a contact name and a telephone number; and generating intimacy probability and authenticity probability according to the contact information of the target user and the target user information. According to the technical scheme provided by the application and the model, the intimacy between each contact and the client and whether the mobile phone number of each contact is effective or not are effectively identified, and the model can be continuously trained based on the existing data, so that the accuracy is continuously improved, and the intimacy of the client is effectively identified; based on such scene scheme, not only can effectual reduction cost of labor, raise the efficiency, but also can accurately discern customer's risk degree.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings needed to be used in the description of the present application will be briefly introduced below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive labor.
Fig. 1 is a flowchart illustrating steps of an identity information auditing method according to an embodiment of the present application;
fig. 2 is a flowchart illustrating steps of an identity information auditing method according to an embodiment of the present application;
fig. 3 is a time sequence diagram of an identity information auditing method according to an embodiment of the present application;
fig. 4 is a schematic diagram illustrating affinity probability of an identity information auditing method according to an embodiment of the present application;
fig. 5 is a flowchart illustrating letter comparison steps of a scanning result of an identity information auditing method according to an embodiment of the present application;
fig. 6 is a likelihood function algorithm diagram of an identity information auditing method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an identity information auditing apparatus according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description. It is to be understood that the embodiments described are only a few embodiments of the present application and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
Referring to fig. 1, a flowchart illustrating steps of an identity information auditing method according to an embodiment of the present application is shown, which specifically includes the following steps:
s110, acquiring contact person information and target user information of a target user; the contact information comprises contact names and telephone numbers;
and S120, generating an affinity probability and an authenticity probability according to the contact information of the target user and the information of the target user.
It should be noted that, after the step S120, the method further includes determining the credit rating of the target user according to the affinity probability and the authenticity probability.
Next, the identity information auditing method in the present exemplary embodiment will be further described.
As described in step S110, the contact information and the target user information of the target user are obtained; the contact information comprises a contact name and a telephone number.
In an embodiment of the present invention, the step S110 of "obtaining contact information of a target user and target user information" may be further described with reference to the following description; wherein the contact information comprises the specific process of contact name and telephone number.
In one embodiment, the user has a greater randomness in the manual input (e.g., the user manually enters the contact: the twitch 134, the little brother 134) because the user uses the manual input method when filling in the contact name because the business system does not obtain the address book authorization.
As described in step S120, the intimacy probability and the authenticity probability are generated according to the contact information of the target user and the information of the target user.
In an embodiment of the present invention, the specific process of "generating the affinity probability and the authenticity probability according to the contact information of the target user and the information of the target user" in step S120 may be further described with reference to the following description.
Generating an affinity probability according to the contact name and the target user information; and generating authenticity probability according to the telephone number.
In an embodiment of the present invention, the specific process of "generating affinity probability according to the contact name and the target user information" may be further described with reference to the following description.
And performing preliminary analysis according to the contact names and the target user information to generate a first probability.
If the first probability is larger than zero and smaller than one, performing secondary analysis according to the contact name to generate a second probability; and if the second probability is larger than zero and smaller than one, reversing according to the contact name to generate the intimacy probability.
And if the first probability is one, directly outputting the intimacy probability as one.
And if the first probability is zero, performing same-clan analysis according to the contact name and the target user information to generate the intimacy probability.
In an embodiment of the present invention, a specific process of "generating a first probability by performing a preliminary analysis according to the contact name and the target user information" in the step may be further described with reference to the following description.
According to the contact name and the target user information, special character processing is carried out to generate preprocessing information; judging the relation according to the preprocessing information to generate the first probability; wherein the relationships include a direct relationship, a non-direct relationship, a weak relationship, a degree, a ranking, a negative direction, and a mutual exclusion. The details are shown in table one.
In a specific embodiment, when a user fills in a name of a contact, a manual input mode is adopted because a business system does not acquire address book authorization, so that the randomness of the user during manual input is large, and the user is influenced by dialects of all parts, habitual words, network vocabularies and other factors, some rules of pneumatic control are easily penetrated (for example, when the user judges whether the contact filled in by the user has a relative relationship by using keywords such as guy and tertiary, the user inputs the royal, express guy, or brother, and the like, so that the penetration of the pneumatic control rules is caused, because the tertiary, brother and the like hit the keywords, but the royal, express guy, brother and the lender do not have a relative relationship), and the complexity and the identification capability of the model are increased. For example, quanday is a brother, quanday is a perkin, other things are called as quanday, brother, little brother, etc., and for small Ming, daddy (dad), the former has a high probability of being expressed as daddy and the latter is roughly called as daddy. For example, children, grandchildren and the like can represent relatives and the context of an expropriator, and the like, while the Xiao-Gong, xiao-Jie and the like are network words, but the most probability of the words does not belong to relatives, so that the model adopts a dual rule check + language model + probability model to solve the problems.
Firstly, we scan the state of the contact person input by the user, and we code the characters according to the direct, non-direct, weak relation, degree vocabulary, ranking vocabulary, negative vocabulary and mutual exclusion vocabulary.
After the contact person symbol is coded, the vocabulary state and the possible splitting state of the vocabulary can be obtained. After status scanning, we enter ambiguous scans such as son, grandson, miss, brother, miss, etc., which have strong language ambiguity, and therefore we need to perform ambiguous scans and label the ambiguity to bring it into the first round of rule scanning.
TABLE 1 relatives keywords and their lexical attributes
TABLE 2 results of the scans
Wherein the corresponding relationship of the results in the second table is shown in FIG. 5, such as O represents a miss, D represents a modified vocabulary, etc.
The first round of rule scanning is based on rough scores of rule analysis, and directly outputs all rules of hit relatives (as in table 2, dad scans all rules of hit relatives, and therefore outputs 1), and performs analysis on all rules of not hit entering the same family (as in domestic naming, contacts have similarity in the same family due to the existence of the same family and the same score), while for the case of only partial hit (as in table two, zhao, my lover, xiao Gou, etc. are only keywords of partial vocabulary hit relatives or the scanning results have mutual exclusion and negative results), we will enter a language model, as shown in fig. 4.
It should be noted that, all hits in the relationship judgment are performed according to the preprocessing information, and the first probability is one; judging whether all the information is not hit according to the relationship of the preprocessed information, wherein the first probability is zero; and judging that only part of the hits are achieved according to the relationship of the preprocessed information, wherein the first probability is larger than zero and smaller than one.
In an embodiment of the present invention, the specific process of "generating the second probability by performing the secondary analysis according to the contact name" in the step may be further described in conjunction with the following description.
Performing language confirmation according to the contact name to generate the second probability; wherein the language confirmation comprises address, circus, last name and entity analysis.
In one embodiment, the language validation is performed by a language model in which we perform language reversal in addition to address scanning, circus recognition, surname analysis, and entity analysis. For example (Dage, two brows, etc., according to the characteristics of domestic languages, the brow is a core word, and two, big, single, old, etc. represent the decoration of the brow), after the language model, we can obtain the address entity + appellation, or other entities + appellations, etc., so that we can judge and analyze the generated entities, if the aunt's middle mountain becomes the aunt's + middle mountain, and if the Jiangxi sister, we will form entities such as 'Jiangxi sister' and 'Jiangxi + sister', etc., and after the entity judgment, we eliminate the interfering entities. The retained entities then enter a second round of regular scanning. And generating a second probability as a second scanning round, generating a first probability as a first scanning round, directly outputting all hit relative rules, and enabling other probabilities to enter a probability model.
In an embodiment of the present invention, a specific process of "if the second probability is greater than zero and less than one, generating the affinity probability by inverting according to the contact name" in the step may be further described with reference to the following description.
The affinity probability is generated by a probabilistic model that attenuates the features of the language inversion, as described in the following steps. For example, "Megaku" is inverted to "Megaku", which is the source, and the probability attenuation increases with distance. For example, the 'Wang-tert' is inverted into 'tert-Wang', and in the process of probability attenuation, because the probability that the 'Wang' is a surname is greater than that of a first name, the attenuation speed is accelerated. The resulting probability is approximately 0.42.
Here we use newton's law of cooling to make the probabilistic output:
rolling probability = probability of upper stage exp (- (attenuation coefficient) × interval)
Wherein attenuation coefficient = state transition coefficient
In an embodiment of the present invention, a specific process of "calculating authenticity of the phone number through a likelihood function according to the phone number to generate the authenticity probability" in the step may be further described with reference to the following description.
As described in the following steps, the service system adopts a manual input mode because the address book authorization is not obtained, which results in that the randomness of the user is large when the user inputs the number manually (such as the user inputs the contact manually: minutia 134 × xiaoming 134 × xiaogong 134), and the algorithm is usually aimed at the authenticity of the mobile phone number, so the algorithm is designed to perform the initial screening of the authenticity of the mobile phone number of the user contact,
therefore, we use the likelihood function to calculate, as shown in fig. 6, the principle is that if the number has consecutive digits, such as 12345, the probability is very small, i.e. the authenticity probability is low. The authenticity probability is judged by calculating the consecutive digits in the number.
In a specific embodiment of the present application, the credit degree of the user is determined according to the intimacy probability and the authenticity probability, where if both the intimacy probability and the authenticity probability are one, the credit degree is one; or the mixture ratio is based on the full weight mode, such as 50% of intimacy probability, 50% of authenticity probability and the like.
For the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for relevant points.
Referring to fig. 7, an identity information auditing apparatus provided in an embodiment of the present application is shown, which specifically includes the following modules,
the obtaining module 710: the system comprises a server and a server, wherein the server is used for acquiring contact person information and target user information of a target user; the contact information comprises contact names and telephone numbers;
the generation module 720: and generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
In an embodiment of the present invention, the generating module 720 includes:
intimacy probability device: generating an affinity probability according to the contact name and the target user information;
authenticity probability means: for generating an authenticity probability in dependence of said telephone number.
In an embodiment of the present invention, the affinity probability device includes:
a first probability device: the system is used for carrying out preliminary analysis according to the contact name and the target user information to generate a first probability;
a second probability means: if the first probability is larger than zero and smaller than one, performing secondary analysis according to the contact name to generate a second probability;
a reversing device: and if the second probability is larger than zero and smaller than one, inverting according to the contact name to generate the intimacy probability.
An intimacy degree generating device: and if the first probability is zero, performing same-clan analysis according to the contact name and the target user information to generate the intimacy probability.
In an embodiment of the present invention, the first probability device includes:
a preprocessing information submodule: the system is used for processing special characters according to the contact names and the target user information to generate preprocessing information;
a first probability submodule: the first probability is generated by performing relation judgment according to the preprocessing information; wherein the relationships include a direct relationship, a non-direct relationship, a weak relationship, a degree, a ranking, a negative direction, and a mutual exclusion.
In an embodiment of the present invention, the second probability device includes:
a second probability submodule: the second probability is generated by performing language confirmation according to the contact name; wherein the language confirmation comprises address, circus, surname and entity analysis.
In one embodiment of the present invention, the authenticity probability means includes:
authenticity submodule: and the probability calculating unit is used for calculating the authenticity of the telephone number through a likelihood function according to the telephone number to generate the authenticity probability.
It should be noted that for simplicity of description, the method embodiments are shown as a series of combinations of acts, but those skilled in the art will recognize that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those of skill in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the embodiments of the invention.
The present embodiment and the above embodiments have repeated operation steps, and the present embodiment is only described briefly, and the rest of the schemes may be described with reference to the above embodiments.
For the device embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, refer to the partial description of the method embodiment.
Referring to fig. 8, a computer device of an identity information auditing method according to the present application is shown, which may specifically include the following:
the computer device 12 described above is embodied in the form of a general purpose computing device, and the components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a memory 28, and a bus 18 that couples various system components including the memory 28 and the processing unit 16.
The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory 30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (commonly referred to as "hard drives"). Although not shown in FIG. 8, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. The memory may include at least one program product having a set (e.g., at least one) of program modules 42, with the program modules 42 configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules 42, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the embodiments described herein.
The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, camera, etc.), with one or more devices that enable an operator to interact with the computer device 12, and/or with any device (e.g., network card, modem, etc.) that enables the computer device 12 to communicate with one or more other computing devices. Such communication may be through the I/O interface 22. Also, computer device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN)), a Wide Area Network (WAN), and/or a public network (e.g., the Internet) via network adapter 20. As shown in FIG. 8, the network adapter 20 communicates with the other modules of the computer device 12 via the bus 18. It should be appreciated that although not shown in FIG. 8, other hardware and/or software modules may be used in conjunction with computer device 12, including but not limited to: microcode, device drivers, redundant processing units 16, external disk drive arrays, RAID systems, tape drives, and data backup storage systems 34, etc.
The processing unit 16 executes programs stored in the memory 28 to execute various functional applications and data processing, for example, to implement an identity information auditing method provided in the embodiments of the present application.
That is, the processing unit 16 implements, when executing the program,: acquiring contact person information and target user information of a target user; the contact information comprises contact names and telephone numbers; and generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
In the embodiments of the present application, the present application further provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor, implements an identity information auditing method as provided in all embodiments of the present application.
That is, the program when executed by the processor implements: acquiring contact person information and target user information of a target user; the contact information comprises contact names and telephone numbers; and generating intimacy probability and authenticity probability according to the contact information of the target user and the target user information.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the operator's computer, partly on the operator's computer, as a stand-alone software package, partly on the operator's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the operator's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). The embodiments in the present specification are all described in a progressive manner, and each embodiment focuses on differences from other embodiments, and portions that are the same and similar between the embodiments may be referred to each other.
While preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including the preferred embodiment and all changes and modifications that fall within the true scope of the embodiments of the present application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrases "comprising one of \ 8230; \8230;" does not exclude the presence of additional like elements in a process, method, article, or terminal device that comprises the element.
The identity information auditing method and device provided by the application are introduced in detail, a specific example is applied in the text to explain the principle and the implementation mode of the application, and the description of the embodiment is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An identity information auditing method, which generates an affinity probability and an authenticity probability through contact information filled in by a user, is characterized by comprising the following steps:
acquiring contact person information and target user information of a target user; the contact information comprises a contact name and a telephone number;
and generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
2. The identity information auditing method according to claim 1, characterized in that the step of generating the affinity probability and the authenticity probability according to the contact information of the target user and the target user information comprises:
generating an affinity probability according to the contact name and the target user information;
and generating authenticity probability according to the telephone number.
3. The identity information auditing method of claim 2 where the step of generating affinity probabilities from the contact names and the target user information includes:
performing preliminary analysis according to the contact names and the target user information to generate a first probability;
if the first probability is larger than zero and smaller than one, carrying out secondary analysis according to the contact name to generate a second probability;
and if the second probability is larger than zero and smaller than one, reversing according to the contact name to generate the intimacy probability.
4. The identity information auditing method of claim 3, where the step of performing preliminary analysis to generate a first probability based on the contact name and the target user information comprises:
processing special characters according to the contact names and the target user information to generate preprocessing information;
performing relation judgment according to the preprocessing information to generate the first probability; wherein the relationships include a direct relationship, a non-direct relationship, a weak relationship, a degree, a ranking, a negative direction, and a mutual exclusion.
5. The identity information auditing method according to claim 3, wherein the step of performing secondary analysis to generate a second probability according to the contact name comprises:
performing language confirmation according to the contact name to generate the second probability; wherein the language confirmation comprises address, circus, surname and entity analysis.
6. The identity information auditing method of claim 3, where if the first probability is zero, the affinity probability is generated by performing a peer-to-peer analysis based on the contact name and the target user information.
7. An identity information auditing method according to claim 1, where the step of generating a probability of authenticity from the telephone number comprises:
and calculating the authenticity of the telephone number through a likelihood function according to the telephone number to generate the authenticity probability.
8. An identity information auditing apparatus that generates an affinity probability and an authenticity probability from contact information filled in by a user, comprising:
the acquisition module is used for acquiring the contact information of the target user and the target user information; the contact information comprises a contact name and a telephone number;
and the generating module is used for generating the intimacy probability and the authenticity probability according to the contact information of the target user and the information of the target user.
9. An electronic device comprising a processor, a memory and a computer program stored on the memory and capable of running on the processor, the computer program, when executed by the processor, performing the steps of the identity information auditing method according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the identity information auditing method according to any one of claims 1 to 7.
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| CN202210928858.9A CN115311063A (en) | 2022-08-03 | 2022-08-03 | Identity information auditing method and device |
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