CN113362162A - Wind control identification method and device based on network behavior data, electronic equipment and medium - Google Patents
Wind control identification method and device based on network behavior data, electronic equipment and medium Download PDFInfo
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- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
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Abstract
The invention relates to the technical field of data analysis, and discloses a wind control identification method based on network behavior data, which comprises the following steps: acquiring project application information of a target user and determining identity information of the target user; judging whether a user has a registration behavior in a first target website according to the identity information, and if so, acquiring first information of the first target website; judging whether a posting behavior or a comment behavior of the user exists in the second target website or not according to the identity information and preset keywords, and if so, acquiring posting content or comment content; and inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control identification model to obtain a wind control portrait of the user. The invention also provides a wind control identification device, equipment and a storage medium based on the network behavior data. The invention also relates to a blockchain technique, the first information being storable in a blockchain node. The invention can improve the accuracy of wind control identification of the user.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a wind control identification method and device based on network behavior data, electronic equipment and a computer readable storage medium.
Background
In a modern financial scene, a financial institution usually performs wind control identification when checking user loans, namely performs prediction evaluation on credit of a user, so as to determine whether to deposit money to the user and what manner to deposit the money to the user, and if the credit prediction evaluation is not accurate, bad accounts are generated, and the operation risk of the financial institution is improved.
In the traditional risk control system, the user credit loan information and the user credit loan labels are mainly acquired by means of financial transaction behaviors which occur in a mainstream credit investigation system, and effective data capture cannot be carried out on some new forms of credit behaviors in the internet era, so that the user credit loan information and the user credit loan labels cannot be provided when the recorded user applies for loan in the mainstream credit investigation system, and therefore the user cannot be accurately identified in a wind control mode.
Disclosure of Invention
The invention provides a method and a device for identifying wind control based on network behavior data, electronic equipment and a computer readable storage medium, and mainly aims to improve the accuracy of wind control identification of a user.
In order to achieve the above object, the present invention provides a wind control identification method based on network behavior data, including:
acquiring project application information of a target user;
determining identity information of the target user from the project application information;
judging whether the target user has a registration behavior in a first target website according to the identity information, and if the target user has the registration behavior in the first target website, acquiring first information of the first target website; and
judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and if the posting behavior or the comment behavior of the target user exists in the second target website, acquiring the posting content or the comment content of the target user;
inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user, and generating a credit rating of the target user according to the wind control portrait.
Optionally, the determining the identity information of the target user from the project application information includes:
extracting the real name or communication contact information of the user from the project application information;
when the item application information does not have the network nickname of the user, searching a first network nickname matched with the real name or the communication contact information in the network; and
searching a network for a second network nickname associated with the first network nickname;
and determining one or more of the real name, the communication contact information, the first network nickname and the second network nickname as the identity information of the target user.
Optionally, the determining, according to the identity information, whether the target user has a registration behavior at the first target website includes:
sending an interface calling request to the first target website, wherein the interface calling request comprises the identity information, so that the first target website searches whether registration information related to the identity information exists in a database of the first target website according to the identity information;
acquiring a registration information query result returned by the first target website;
and if the registration information query result is that the registered information exists, determining that the target user has a registration behavior in the first target website.
Optionally, the first target website or the second target website includes a financial forum, a consumption forum, a social APP, and an online credit APP, where the financial forum includes an online credit forum, a credit card forum, and an investment forum.
Optionally, the determining whether the posting behavior or the comment behavior of the target user exists in a second target website according to the identity information and a preset keyword includes:
constructing a retrieval text by using the identity information and preset keywords;
crawling a text which is the same as or similar to the retrieval text in the page of the second target website according to the retrieval text to obtain a crawler result;
and if the crawler result is not empty, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
Optionally, the determining whether the posting behavior or the comment behavior of the target user exists in a second target website according to the identity information and a preset keyword includes:
searching in the second target website through the identity information and preset keywords to obtain search information;
acquiring a plurality of key entities from the search reply by using a preset natural language processing method;
distributing weights to the key entities based on a preset weight distribution table;
and if the sum of the search weights in the search information is greater than a first preset threshold value, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
Optionally, the obtaining of the posting content or the comment content of the target user includes:
obtaining a plurality of posting contents or a plurality of comment contents according to posting behaviors or comment behaviors of the target user;
acquiring a plurality of content features from each posting content or each comment content by using a preset feature extraction method;
if the sum of the weights of the content features is smaller than a second preset threshold value, deleting the posted content or the comment content corresponding to the content features;
if the sum of the weights of the content features is larger than a second preset threshold value, the posting content or the comment content corresponding to the content features is reserved.
In order to solve the above problem, the present invention further provides a wind control identification apparatus based on network behavior data, the apparatus including:
the application information acquisition module is used for acquiring project application information of a target user;
the identity information confirmation module is used for determining the identity information of the target user from the project application information;
the website information acquisition module is used for judging whether the target user has a registration behavior in a first target website according to the identity information, and acquiring first information of the first target website if the target user has the registration behavior in the first target website;
the interactive information acquisition module is used for judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and acquiring the posting content or the comment content of the target user if the posting behavior or the comment behavior of the target user exists in the second target website;
and the wind control portrait creating module is used for inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user and generating a credit rating of the target user according to the wind control portrait.
In order to solve the above problem, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of wind control identification based on network behavior data as described above.
In order to solve the above problem, the present invention further provides a computer-readable storage medium including a storage data area and a storage program area, the storage data area storing created data, the storage program area storing a computer program; wherein the computer program, when executed by a processor, implements a method of wind control identification based on network behavior data as described above.
In the embodiment of the invention, the project application information of a target user is acquired, the identity information of the target user is extracted from the project application information of the target user, whether the user has a registration behavior or not is inquired from a first target website according to the identity information, the first information of the first target website is acquired when the registration behavior exists, the information of the website registered by the user is acquired, the posting content or the comment content of the target user is acquired from a second target website when the posting behavior or the comment behavior of the target user exists in a second website, the posting content or the comment content is acquired from the second target website, one or more of the first information, the posting content and the comment content are input into a pre-constructed wind control identification model, the network behavior data of the user is input into the wind control identification model, and the richness of the data input into the wind control identification model is improved, and further, a more accurate wind control portrait of the target user is obtained, and the purpose of improving the accuracy of wind control identification on the user is achieved.
Drawings
Fig. 1 is a schematic flowchart of a wind control identification method based on network behavior data according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a wind control identification apparatus based on network behavior data according to an embodiment of the present invention;
fig. 3 is a schematic internal structural diagram of an electronic device implementing a network behavior data-based wind control identification method according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the application provides a wind control identification method based on network behavior data. The execution subject of the wind control identification method based on the network behavior data includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiments of the present application. In other words, the network behavior data-based wind control identification method may be executed by software or hardware installed in the terminal device or the server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Fig. 1 is a schematic flow chart of a wind control identification method based on network behavior data according to an embodiment of the present invention. In this embodiment, the method for identifying a wind control based on network behavior data includes:
and S1, acquiring the project application information of the target user.
In the embodiment of the invention, the project application information is loan project application information, and the target user is a loan project application user, such as a user applying for credit loan based on the existing credit system.
In this embodiment, the project application information may include personal information provided by the target user based on the purpose of applying for the project, for example: household address, current address, work unit, mobile phone number, mailbox number, identity card number, etc.
Further, in this solution, the project application information provided by the target user may be stored in a user information database preset in the credit system, and when credit analysis needs to be performed on the target user, the project application information is extracted from the user information database.
In detail, the acquiring the project application information of the target user includes:
acquiring a project information database for storing the project application information;
and acquiring the unique characteristics of the target user, and extracting the project application information of the target user from the project information database by using the uniqueness of the target user.
In the scheme, the unique feature is a feature for identifying the uniqueness of the user, such as an identity number of the user, a mobile phone number of the user, a mailbox number of the user, and the like, and meanwhile, features that the uniqueness of the user cannot be determined, such as a household address of the user, a current residence address of the user, a work unit of the user, and the like, are not taken as the unique feature.
And S2, determining the identity information of the target user from the project application information.
In this embodiment, the identity information of the target user includes a real name of the target user, communication contact information of the target user, a network nickname of the target user, and the like.
In detail, the determining the identity information of the target user from the project application information includes:
extracting the real name or communication contact information of the user from the project application information;
when the item application information does not have the network nickname of the user, searching a first network nickname matched with the real name or the communication contact information in the network; and
searching a network for a second network nickname associated with the first network nickname;
and determining one or more of the real name, the communication contact information, the first network nickname and the second network nickname as the identity information of the target user.
In this embodiment of the present invention, the network nickname is a name set in the network by the target user.
In the embodiment of the present invention, the communication contact information is information that can contact the target user, for example, a mobile phone number, a mailbox number, and the like.
Furthermore, the data source can be widened by searching the second network nickname associated with the first network nickname in the network, and the data feasibility is improved.
The searching for the second network nickname associated with the first network nickname over the network comprises:
searching a first communication account number to which the first network nickname belongs;
acquiring a communication record of the first communication account, and screening out a second communication account with the maximum communication frequency from the communication record;
and acquiring the account nickname of the second communication account, and taking the account nickname as a second network nickname associated with the first network nickname.
Specifically, the screening out the second communication account with the maximum communication frequency from the communication records includes:
acquiring all communication accounts in the communication record to obtain a communication account set;
counting the communication times of each communication account in the communication account set according to the communication records;
and sequencing the communication times of the communication accounts in the communication account set, and acquiring the communication account with the maximum communication time as the second communication account.
Further, the communication times of the communication accounts in the communication account set can be sorted by a sorting method such as insert sorting, hill sorting, heap sorting, quick sorting and the like.
In the embodiment of the invention, the communication record is an opened information record or an information record authorized by a user.
S3, judging whether the target user has a registration behavior in the first target website according to the identity information, and if the target user has the registration behavior in the first target website, acquiring first information of the first target website.
In the embodiment of the invention, the first target website comprises a financial forum, a consumption forum, a social APP and an internet credit APP, wherein the financial forum comprises an internet credit forum, a credit card forum and an investment forum.
In detail, the determining whether the target user has a registration behavior in the first target website according to the identity information includes:
sending an interface calling request to the first target website, wherein the interface calling request comprises the identity information, so that the first target website searches whether registration information related to the identity information exists in a database of the first target website according to the identity information;
acquiring a registration information query result returned by the first target website;
and if the registration information query result is that the registered information exists, determining that the target user has a registration behavior in the first target website.
For example, if mr. wang registers an account with the X website, the account ID is 02304, and the loan amount is 10000 renminbi, the registration information of mr. wang in the website includes the account ID and may also include the loan amount.
In this embodiment, the first information includes a website name of the first target website, a website domain name of the first target website, registration information of the target user on the first target website, and the like.
S4, judging whether the posting behavior or the comment behavior of the target user exists in a second target website according to the identity information and preset keywords, and if the posting behavior or the comment behavior of the target user exists in the second target website, acquiring the posting content or the comment content of the target user.
Preferably, the second target website is another website different from the first target website in financial forum, consumer forum, social APP, and network credit APP, wherein the financial forum includes network credit forum, credit card forum, and investment forum.
In the embodiment of the invention, the preset keywords are xx credit, xx card and the like.
In an optional embodiment of the present invention, the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword includes:
constructing a retrieval text by using the identity information and preset keywords;
crawling a text which is the same as or similar to the retrieval text in the page of the second target website according to the retrieval text to obtain a crawler result;
and if the crawler result is not empty, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
In the embodiment of the invention, the crawling result is published data, and the crawler is a web crawler and is a program or script for crawling data from the second target website according to a certain rule.
In another optional embodiment of the present invention, the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword includes:
searching in the second target website through the identity information and preset keywords to obtain search information;
acquiring a plurality of key entities from the search reply by using a preset natural language processing method;
distributing weights to the key entities based on a preset weight distribution table;
and if the sum of the search weights in the search information is greater than a first preset threshold value, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
The Natural Language Processing method (NLP) is a branch in artificial intelligence and has the capabilities of Chinese automatic word segmentation, part of speech tagging, syntactic analysis, Natural Language generation and the like
In an embodiment of the present invention, the Natural Language Processing method (NLP) is a branch in artificial intelligence, and has capabilities of automatic word segmentation, part-of-speech tagging, syntactic analysis, Natural Language generation, and the like in chinese, and the preset weight distribution table is a table for distributing a weight to the key entity, for example, when the key entity is "loan share" or "repayment deadline", the weight of the key entity distributed with the weight of "loan share" is 0.4, and the weight of the key entity distributed with the weight of "repayment deadline" is 0.6.
The first preset threshold may be preset.
In detail, the obtaining of the posting content or the comment content of the target user includes:
obtaining a plurality of posting contents or a plurality of comment contents according to posting behaviors or comment behaviors of the target user;
acquiring a plurality of content features from each posting content or each comment content by using a preset feature extraction method;
if the sum of the weights of the content features is smaller than a second preset threshold value, deleting the posted content or the comment content corresponding to the content features;
if the sum of the weights of the content features is larger than a second preset threshold value, the posting content or the comment content corresponding to the content features is reserved.
The second preset threshold may be preset.
In the embodiment of the present invention, the feature extraction method is a method for acquiring content features from posting content or comment content through a Vector Space Model (VSM), and the Vector Space Model can simplify processing of text content into Vector operation in a Vector Space, so as to extract features according to similarity of vectors in the Space.
Specifically, the weight of the content feature may be calculated by an entropy method (information quantity method), where the larger the information quantity contained in the content feature is, the smaller the uncertainty is, the smaller the entropy value is, the larger the weight is, the smaller the information contained in the content feature is, the larger the uncertainty is, the larger the entropy value is, and the smaller the weight is. Further, the content features may include information amount obtained when the content features are obtained by the vector space model, and when each content feature is represented by a vector, the longer the vector, the larger the represented information amount.
S5, inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user, and generating a credit rating of the target user according to the wind control portrait.
In an embodiment of the present invention, before inputting one or more of the first information, the posted content, and the comment content into a pre-constructed wind control identification model, the method further includes:
acquiring an open-source automatic learning framework;
and constructing the wind control identification model by utilizing a gradient descent algorithm and an extreme gradient lifting algorithm based on the automatic learning framework.
Further, the wind control identification model is a model constructed based on an automatic machine learning system, and has the capabilities of feature selection, feature generation and feature coding, the feature generation is to construct the features of the wind control identification model according to the first information, the posting content and the comment content, the feature selection can screen the first information, the posting content and the comment content and remove irrelevant information, and the feature coding is to digitally code the first information, the posting content and the comment content so that the first information, the posting content and the comment content become digital information understood by a computer.
In the embodiment of the invention, after the wind control portrait of the target user is obtained, the wind control portrait of the target user can be stored in each financial supervision system, and when the target user needs credit behavior, the wind control portrait of the target user is obtained from the financial supervision systems, and information such as credit rating of the target user is provided through the wind control portrait of the target user.
In the embodiment of the invention, the project application information of a target user is acquired, the identity information of the target user is extracted from the project application information of the target user, whether the user has a registration behavior or not is inquired from a first target website according to the identity information, the first information of the first target website is acquired when the registration behavior exists, the information of the website registered by the user is acquired, the posting content or the comment content of the target user is acquired from a second target website when the posting behavior or the comment behavior of the target user exists in a second website, the posting content or the comment content is acquired from the second target website, one or more of the first information, the posting content and the comment content are input into a pre-constructed wind control identification model, the network behavior data of the user is input into the wind control identification model, and the richness of the data input into the wind control identification model is improved, and further, a more accurate wind control portrait of the target user is obtained, and the purpose of improving the accuracy of wind control identification on the user is achieved.
Fig. 2 is a schematic block diagram of the wind control identification apparatus based on network behavior data according to the present invention.
The wind control identification device 100 based on the network behavior data can be installed in electronic equipment. According to the realized function, the wind control identification device based on the network behavior data can comprise an application information acquisition module 101, an identity information confirmation module 102, a website information acquisition module 103, an interaction information acquisition module 104 and a wind control portrait creation module 105. The module of the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the application information acquiring module 101 is configured to acquire project application information of a target user.
In the embodiment of the invention, the project application information is loan project application information, and the target user is a loan project application user, such as a user applying for credit loan based on the existing credit system.
In this embodiment, the project application information may include personal information provided by the target user based on the purpose of applying for the project, for example: household address, current address, work unit, mobile phone number, mailbox number, identity card number, etc.
Further, in this solution, the project application information provided by the target user may be stored in a user information database preset in the credit system, and when credit analysis needs to be performed on the target user, the project application information is extracted from the user information database.
In detail, the application information obtaining module 101 is specifically configured to:
acquiring a project information database for storing the project application information;
and acquiring the unique characteristics of the target user, and extracting the project application information of the target user from the project information database by using the uniqueness of the target user.
In the scheme, the unique feature is a feature for identifying the uniqueness of the user, such as an identity number of the user, a mobile phone number of the user, a mailbox number of the user, and the like, and meanwhile, features that the uniqueness of the user cannot be determined, such as a household address of the user, a current residence address of the user, a work unit of the user, and the like, are not taken as the unique feature.
The identity information confirming module 102 is configured to determine the identity information of the target user from the project application information.
In this embodiment, the identity information of the target user includes a real name of the target user, communication contact information of the target user, a network nickname of the target user, and the like.
In detail, the identity information confirmation module 102 is specifically configured to:
extracting the real name or communication contact information of the user from the project application information;
when the item application information does not have the network nickname of the user, searching a first network nickname matched with the real name or the communication contact information in the network; and
searching a network for a second network nickname associated with the first network nickname;
and determining one or more of the real name, the communication contact information, the first network nickname and the second network nickname as the identity information of the target user.
In this embodiment of the present invention, the network nickname is a name set in the network by the target user.
In the embodiment of the present invention, the communication contact information is information that can contact the target user, for example, a mobile phone number, a mailbox number, and the like.
Furthermore, the data source can be widened by searching the second network nickname associated with the first network nickname in the network, and the data feasibility is improved.
The searching for the second network nickname associated with the first network nickname over the network comprises:
searching a first communication account number to which the first network nickname belongs;
acquiring a communication record of the first communication account, and screening out a second communication account with the maximum communication frequency from the communication record;
and acquiring the account nickname of the second communication account, and taking the account nickname as a second network nickname associated with the first network nickname.
Specifically, the screening out the second communication account with the maximum communication frequency from the communication records includes:
acquiring all communication accounts in the communication record to obtain a communication account set;
counting the communication times of each communication account in the communication account set according to the communication records;
and sequencing the communication times of the communication accounts in the communication account set, and acquiring the communication account with the maximum communication time as the second communication account.
Further, the communication times of the communication accounts in the communication account set can be sorted by a sorting method such as insert sorting, hill sorting, heap sorting, quick sorting and the like.
In the embodiment of the invention, the communication record is an opened information record or an information record authorized by a user.
The website information obtaining module 103 is configured to determine whether the target user has a registration behavior in the first target website according to the identity information, and obtain first information of the first target website if the target user has the registration behavior in the first target website.
In the embodiment of the invention, the first target website comprises a financial forum, a consumption forum, a social APP and an internet credit APP, wherein the financial forum comprises an internet credit forum, a credit card forum and an investment forum.
In detail, the determining whether the target user has a registration behavior in the first target website according to the identity information includes:
sending an interface calling request to the first target website, wherein the interface calling request comprises the identity information, so that the first target website searches whether registration information related to the identity information exists in a database of the first target website according to the identity information;
acquiring a registration information query result returned by the first target website;
and if the registration information query result is that the registered information exists, determining that the target user has a registration behavior in the first target website.
For example, if mr. wang registers an account with the X website, the account ID is 02304, and the loan amount is 10000 renminbi, the registration information of mr. wang in the website includes the account ID and may also include the loan amount.
In this embodiment, the first information includes a website name of the first target website, a website domain name of the first target website, registration information of the target user on the first target website, and the like.
The interaction information obtaining module 104 is configured to determine whether a posting behavior or a comment behavior of the target user exists in a second target website according to the identity information and a preset keyword, and if the posting behavior or the comment behavior of the target user exists in the second target website, obtain posting content or comment content of the target user.
Preferably, the second target website is another website different from the first target website in financial forum, consumer forum, social APP, and network credit APP, wherein the financial forum includes network credit forum, credit card forum, and investment forum.
In the embodiment of the invention, the preset keywords are xx credit, xx card and the like.
In an optional embodiment of the present invention, the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword includes:
constructing a retrieval text by using the identity information and preset keywords;
crawling a text which is the same as or similar to the retrieval text in the page of the second target website according to the retrieval text to obtain a crawler result;
and if the crawler result is not empty, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
In the embodiment of the invention, the crawling result is published data, and the crawler is a web crawler and is a program or script for crawling data from the second target website according to a certain rule.
In another optional embodiment of the present invention, the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword includes:
searching in the second target website through the identity information and preset keywords to obtain search information;
acquiring a plurality of key entities from the search reply by using a preset natural language processing method;
distributing weights to the key entities based on a preset weight distribution table;
and if the sum of the search weights in the search information is greater than a first preset threshold value, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
The Natural Language Processing method (NLP) is a branch in artificial intelligence and has the capabilities of Chinese automatic word segmentation, part of speech tagging, syntactic analysis, Natural Language generation and the like
In an embodiment of the present invention, the Natural Language Processing method (NLP) is a branch in artificial intelligence, and has capabilities of automatic word segmentation, part-of-speech tagging, syntactic analysis, Natural Language generation, and the like in chinese, and the preset weight distribution table is a table for distributing a weight to the key entity, for example, when the key entity is "loan share" or "repayment deadline", the weight of the key entity distributed with the weight of "loan share" is 0.4, and the weight of the key entity distributed with the weight of "repayment deadline" is 0.6.
The first preset threshold may be preset.
In detail, the obtaining of the posting content or the comment content of the target user includes:
obtaining a plurality of posting contents or a plurality of comment contents according to posting behaviors or comment behaviors of the target user;
acquiring a plurality of content features from each posting content or each comment content by using a preset feature extraction method;
if the sum of the weights of the content features is smaller than a second preset threshold value, deleting the posted content or the comment content corresponding to the content features;
if the sum of the weights of the content features is larger than a second preset threshold value, the posting content or the comment content corresponding to the content features is reserved.
The second preset threshold may be preset.
In the embodiment of the present invention, the feature extraction method is a method for acquiring content features from posting content or comment content through a Vector Space Model (VSM), and the Vector Space Model can simplify processing of text content into Vector operation in a Vector Space, so as to extract features according to similarity of vectors in the Space.
Specifically, the weight of the content feature may be calculated by an entropy method (information quantity method), where the larger the information quantity contained in the content feature is, the smaller the uncertainty is, the smaller the entropy value is, the larger the weight is, the smaller the information contained in the content feature is, the larger the uncertainty is, the larger the entropy value is, and the smaller the weight is. Further, the content features may include information amount obtained when the content features are obtained by the vector space model, and when each content feature is represented by a vector, the longer the vector, the larger the represented information amount.
The wind control portrait creating module 105 is configured to input one or more of the first information, the posting content, and the comment content into a pre-constructed wind control recognition model, obtain a wind control portrait of the target user, and generate a credit rating of the target user according to the wind control portrait.
In an embodiment of the present invention, the apparatus further includes a model building module, where the model building module is configured to:
before one or more items of the first information, the posting content and the comment content are input into a pre-constructed wind control identification model, an open-source automatic learning framework is obtained;
and constructing the wind control identification model by utilizing a gradient descent algorithm and an extreme gradient lifting algorithm based on the automatic learning framework.
Further, the wind control identification model is a model constructed based on an automatic machine learning system, and has the capabilities of feature selection, feature generation and feature coding, the feature generation is to construct the features of the wind control identification model according to the first information, the posting content and the comment content, the feature selection can screen the first information, the posting content and the comment content and remove irrelevant information, and the feature coding is to digitally code the first information, the posting content and the comment content so that the first information, the posting content and the comment content become digital information understood by a computer.
In the embodiment of the invention, after the wind control portrait of the target user is obtained, the wind control portrait of the target user can be stored in each financial supervision system, and when the target user needs credit behavior, the wind control portrait of the target user is obtained from the financial supervision systems, and information such as credit rating of the target user is provided through the wind control portrait of the target user.
In the embodiment of the invention, the project application information of a target user is acquired, the identity information of the target user is extracted from the project application information of the target user, whether the user has a registration behavior or not is inquired from a first target website according to the identity information, the first information of the first target website is acquired when the registration behavior exists, the information of the website registered by the user is acquired, the posting content or the comment content of the target user is acquired from a second target website when the posting behavior or the comment behavior of the target user exists in a second website, the posting content or the comment content is acquired from the second target website, one or more of the first information, the posting content and the comment content are input into a pre-constructed wind control identification model, the network behavior data of the user is input into the wind control identification model, and the richness of the data input into the wind control identification model is improved, and further, a more accurate wind control portrait of the target user is obtained, and the purpose of improving the accuracy of wind control identification on the user is achieved.
Fig. 3 is a schematic structural diagram of an electronic device implementing the network behavior data-based wind control identification method according to the present invention.
The electronic device may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program, such as a wind control identification program based on network behavior data, stored in the memory 11 and executable on the processor 10.
In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same function or different functions, and includes one or more Central Processing Units (CPUs), a microprocessor, a digital Processing chip, a graphics processor, a combination of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device by running or executing programs or modules stored in the memory 11 (for example, executing a wind Control identification program based on network behavior data, etc.), and calling data stored in the memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, removable hard disks, multimedia cards, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disks, optical disks, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, for example a removable hard disk of the electronic device. The memory 11 may also be an external storage device of the electronic device in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in the electronic device and various types of data, such as codes of a wind control identification program based on network behavior data, but also temporarily store data that has been output or will be output.
The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), which are typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable, among other things, for displaying information processed in the electronic device and for displaying a visualized user interface.
Fig. 3 shows only an electronic device having components, and those skilled in the art will appreciate that the structure shown in fig. 3 does not constitute a limitation of the electronic device, and may include fewer or more components than those shown, or some components may be combined, or a different arrangement of components.
For example, although not shown, the electronic device may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management and the like are realized through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The network behavior data based wind control identification program stored in the memory 11 of the electronic device is a combination of a plurality of computer programs, and when running in the processor 10, can realize:
acquiring project application information of a target user;
determining identity information of the target user from the project application information;
judging whether the target user has a registration behavior in a first target website according to the identity information, and if the target user has the registration behavior in the first target website, acquiring first information of the first target website; and
judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and if the posting behavior or the comment behavior of the target user exists in the second target website, acquiring the posting content or the comment content of the target user;
inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user, and generating a credit rating of the target user according to the wind control portrait.
Specifically, the processor 10 may refer to the description of the relevant steps in the embodiment corresponding to fig. 1 for a specific implementation method of the computer program, which is not described herein again.
Further, the electronic device integrated module/unit, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in a non-volatile computer-readable storage medium. The computer readable storage medium may be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
The present invention also provides a computer-readable storage medium, storing a computer program which, when executed by a processor of an electronic device, may implement:
acquiring project application information of a target user;
determining identity information of the target user from the project application information;
judging whether the target user has a registration behavior in a first target website according to the identity information, and if the target user has the registration behavior in the first target website, acquiring first information of the first target website; and
judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and if the posting behavior or the comment behavior of the target user exists in the second target website, acquiring the posting content or the comment content of the target user;
inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user, and generating a credit rating of the target user according to the wind control portrait.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A wind control identification method based on network behavior data is characterized by comprising the following steps:
acquiring project application information of a target user;
determining identity information of the target user from the project application information;
judging whether the target user has a registration behavior in a first target website according to the identity information, and if the target user has the registration behavior in the first target website, acquiring first information of the first target website; and
judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and if the posting behavior or the comment behavior of the target user exists in the second target website, acquiring the posting content or the comment content of the target user;
inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user, and generating a credit rating of the target user according to the wind control portrait.
2. The method according to claim 1, wherein the determining identity information of the target user from the project application information comprises:
extracting the real name or communication contact information of the user from the project application information;
when the item application information does not have the network nickname of the user, searching a first network nickname matched with the real name or the communication contact information in the network; and
searching a network for a second network nickname associated with the first network nickname;
and determining one or more of the real name, the communication contact information, the first network nickname and the second network nickname as the identity information of the target user.
3. The method for wind-controlled identification based on network behavior data according to claim 1, wherein the determining whether the target user has a registration behavior at the first target website according to the identity information comprises:
sending an interface calling request to the first target website, wherein the interface calling request comprises the identity information, so that the first target website searches whether registration information related to the identity information exists in a database of the first target website according to the identity information;
acquiring a registration information query result returned by the first target website;
and if the registration information query result is that the registered information exists, determining that the target user has a registration behavior in the first target website.
4. The method according to claim 1, wherein the first target website or the second target website comprises a financial forum, a consumer forum, a social APP, and an online credit APP, and wherein the financial forum comprises an online credit forum, a credit card forum, and an investment forum.
5. The method for wind-controlled identification based on network behavior data according to claim 1, wherein the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword comprises:
constructing a retrieval text by using the identity information and preset keywords;
crawling a text which is the same as or similar to the retrieval text in the page of the second target website according to the retrieval text to obtain a crawler result;
and if the crawler result is not empty, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
6. The method for wind-controlled identification based on network behavior data according to claim 1, wherein the determining whether the posting behavior or the comment behavior of the target user exists in the second target website according to the identity information and the preset keyword comprises:
searching in the second target website through the identity information and preset keywords to obtain search information;
acquiring a plurality of key entities from the search reply by using a preset natural language processing method;
distributing weights to the key entities based on a preset weight distribution table;
and if the sum of the search weights in the search information is greater than a first preset threshold value, determining that the posting behavior or the comment behavior of the target user exists in the second target website.
7. The method for wind-controlled identification based on network behavior data of any one of claims 1 to 6, wherein the obtaining of the posted content or comment content of the target user comprises:
obtaining a plurality of posting contents or a plurality of comment contents according to posting behaviors or comment behaviors of the target user;
acquiring a plurality of content features from each posting content or each comment content by using a preset feature extraction method;
if the sum of the weights of the content features is smaller than a second preset threshold value, deleting the posted content or the comment content corresponding to the content features;
if the sum of the weights of the content features is larger than a second preset threshold value, the posting content or the comment content corresponding to the content features is reserved.
8. A device for identifying wind control based on network behavior data, the device comprising:
the application information acquisition module is used for acquiring project application information of a target user;
the identity information confirmation module is used for determining the identity information of the target user from the project application information;
the website information acquisition module is used for judging whether the target user has a registration behavior in a first target website according to the identity information, and acquiring first information of the first target website if the target user has the registration behavior in the first target website;
the interactive information acquisition module is used for judging whether the posting behavior or the comment behavior of the target user exists in a second target website or not according to the identity information and preset keywords, and acquiring the posting content or the comment content of the target user if the posting behavior or the comment behavior of the target user exists in the second target website;
and the wind control portrait creating module is used for inputting one or more items of the first information, the posting content and the comment content into a pre-constructed wind control recognition model to obtain a wind control portrait of the target user and generating a credit rating of the target user according to the wind control portrait.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of network behavior data based wind control identification according to any of claims 1 to 7.
10. A computer-readable storage medium comprising a storage data area storing created data and a storage program area storing a computer program; wherein the computer program when executed by a processor implements a method of network behavior data based wind control identification according to any of claims 1 to 7.
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| CN202110728032.3A CN113362162A (en) | 2021-06-29 | 2021-06-29 | Wind control identification method and device based on network behavior data, electronic equipment and medium |
| PCT/CN2021/109487 WO2023272862A1 (en) | 2021-06-29 | 2021-07-30 | Risk control recognition method and apparatus based on network behavior data, and electronic device and medium |
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| CN117408805B (en) * | 2023-12-15 | 2024-03-22 | 杭银消费金融股份有限公司 | Credit wind control method and system based on stability modeling |
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