A method, device and medium for identifying fake enterprises

Abstract

The present application provides a method, device and medium for identifying false enterprises, by receiving enterprise reporting information uploaded by the enterprise to be certified. Among them, the enterprise reporting information includes at least enterprise registration information and enterprise transaction records. The enterprise reporting information is identified to determine a number of false information to be identified in the enterprise reporting information. Comparison information corresponding to each false information to be identified is obtained, and the matching value between each false information to be identified and the corresponding comparison information is calculated. When the matching value does not reach the first preset threshold, the false information to be identified is determined to be false information. Based on each false information, the enterprise to be certified is determined to be a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform. Through the above method, enterprises can be helped to identify false enterprises on the network platform to ensure enterprise safety.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method, device and medium for identifying a fake enterprise. Background Art

[0002] With the development of Internet technology, people can exchange information without space restrictions, and the Internet has brought great convenience to people. At the same time, various enterprises can also process business through the Internet, such as corporate procurement, corporate sales, corporate bidding and other businesses, which can all be completed through the Internet. The Internet has greatly improved the office efficiency of enterprises.

[0003] While the Internet helps enterprises, it also has some information security issues. When enterprises purchase goods through the Internet, they cannot be sure whether the supplier providing the goods is authentic and reliable. Therefore, some purchasing enterprises will choose to cooperate with a single supplier that they are familiar with, resulting in the fact that the authentic and reliable supplier cannot get the opportunity to cooperate. The trusted supplier may not be able to meet the needs of the purchasing enterprise, and the purchasing enterprise has to seek other suppliers. How to determine the authentic and reliable enterprises on the Internet platform has become a technical problem. Summary of the invention

[0004] The embodiments of the present application provide a method, device and medium for identifying fake enterprises, which are used to determine authentic and reliable enterprises on a network platform.

[0005] In one aspect, the present application provides a method for identifying a fake enterprise, the method comprising:

[0006] Receive enterprise reporting information uploaded by the enterprise to be certified. The enterprise reporting information includes at least enterprise registration information and enterprise transaction records. Identify the enterprise reporting information and determine a number of false information to be identified in the enterprise reporting information. Obtain comparison information corresponding to each false information to be identified, and calculate the matching value between each false information to be identified and the corresponding comparison information. If the matching value does not reach the first preset threshold, determine that the false information to be identified is false information. According to each false information, determine that the enterprise to be certified is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform.

[0007] In one implementation of the present application, based on the enterprise reported information, the enterprise information corresponding to the enterprise reported information is determined. The enterprise information is compared with the enterprise reported information. If the enterprise information is successfully compared with the enterprise reported information, some false information to be identified in the enterprise reported information is determined.

[0008] In one implementation of the present application, the enterprise registration information in the enterprise reporting information is identified according to preset rules to obtain several groups of text information, extract keywords from each group of text information, and compare each keyword with the text information in the enterprise information.

[0009] In one implementation of the present application, based on the false information to be identified, the enterprise transaction record generated by the first node on the blockchain platform is determined. And the second node corresponding to the third-party agency is determined to upload the enterprise registration information corresponding to the first node. The enterprise transaction record generated by the first node on the blockchain platform and the enterprise registration information corresponding to the first node uploaded by the second node corresponding to the third-party agency are used as comparison information. Each piece of false information to be identified is compared with the comparison information one by one to generate a comparison result. According to the comparison result, the matching value between each piece of false information to be identified and the corresponding comparison information is calculated.

[0010] In one implementation of the present application, authentication information sent by a first terminal is obtained. The first terminal corresponds to a terminal that has been registered on a pre-established network platform. The authentication information includes a corporate identity. Based on the authentication information, the historical authentication record of the enterprise of interest corresponding to the first terminal is determined to determine whether the enterprise of interest is an enterprise to be authenticated. In the case that the enterprise of interest is an enterprise to be authenticated, authentication prompt information is generated and sent to the terminal corresponding to the enterprise of interest to prompt the enterprise of interest to upload the enterprise reporting information. Feedback information from the enterprise of interest is obtained. In the case that the feedback information is a rejection of authentication, a rejection of authentication record is generated and recorded in the corresponding database.

[0011] In one implementation of the present application, platform registration information sent by the second terminal is obtained. The platform registration information includes at least the company name, company address, and company type. The second terminal corresponds to a terminal that is not registered on the network platform. According to the platform registration information, authentication is initiated to a third-party organization. If the platform registration information authentication is successful, the registration account information corresponding to the second terminal is generated and sent to the second terminal, so that the second terminal uses the network platform according to the registration account information.

[0012] In one implementation of the present application, communication data between enterprises on a network platform is obtained. Keywords in the communication data are extracted. Based on a pre-trained neural network model, it is determined whether there is negative information in the keywords. In the case where there is negative information in the keywords, a prompt message is sent to the corresponding terminal of the enterprise that issued the negative information to remind the enterprise that issued the negative information. In the case where it is determined that the number of times the enterprise that issued the negative information has issued the negative information is greater than a second preset threshold, an announcement message is generated. Among them, the announcement information is information published on the network platform.

[0013] In one implementation of the present application, the enterprise type corresponding to the terminal currently using the network platform is obtained, the corresponding false enterprises on the network platform are filtered according to the enterprise type, and the enterprise corresponding to the enterprise type is pushed to the terminal currently using the network platform.

[0014] On the other hand, the present application provides a false enterprise identification device, the device comprising:

[0015] At least one processor. And a memory in communication with the at least one processor. The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to implement the function:

[0016] Receive enterprise reporting information uploaded by the enterprise to be certified. The enterprise reporting information includes at least enterprise registration information and enterprise transaction records. Identify the enterprise reporting information and determine a number of false information to be identified in the enterprise reporting information. Obtain comparison information corresponding to each false information to be identified, and calculate the matching value between each false information to be identified and the corresponding comparison information. If the matching value does not reach the first preset threshold, determine that the false information to be identified is false information. According to each false information, determine that the enterprise to be certified is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform.

[0017] On the other hand, the present application provides a non-volatile computer storage medium for false enterprise identification, storing computer executable instructions, wherein the computer executable instructions are configured as follows:

[0018] Receive enterprise reporting information uploaded by the enterprise to be certified. The enterprise reporting information includes at least enterprise registration information and enterprise transaction records. Identify the enterprise reporting information and determine a number of false information to be identified in the enterprise reporting information. Obtain comparison information corresponding to each false information to be identified, and calculate the matching value between each false information to be identified and the corresponding comparison information. If the matching value does not reach the first preset threshold, determine that the false information to be identified is false information. According to each false information, determine that the enterprise to be certified is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform.

[0019] Through the above-mentioned scheme, this application prevents enterprises from encountering fake enterprises when conducting procurement, sales, bidding, etc. through online platforms, which may cause loss of profits to the enterprises, provide security for the online business of the enterprises, and ensure the experience of enterprises in online platform transactions. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0021] Figure 1 A schematic diagram of a flow chart of a method for identifying a fake enterprise in an embodiment of the present application;

[0022] Figure 2 Another schematic diagram of a flow chart of a method for identifying a fake enterprise in an embodiment of the present application;

[0023] Figure 3 Another schematic diagram of a flow chart of a method for identifying a fake enterprise in an embodiment of the present application;

[0024] Figure 4 Another schematic diagram of a flow chart of a method for identifying a fake enterprise in an embodiment of the present application;

[0025] Figure 5 Another schematic diagram of a flow chart of a method for identifying a fake enterprise in an embodiment of the present application;

[0026] Figure 6 This is a structural diagram of a fake enterprise identification device in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0028] When conducting business through online platforms, enterprises cannot identify fake enterprises by themselves. Once they conduct transactions with fake enterprises, they will suffer huge losses. Therefore, it is the responsibility of online platforms to identify fake enterprises before transactions occur and avoid losses to other enterprises.

[0029] Based on this, the present application provides a method, device and medium for identifying fake enterprises, which are used to determine real and reliable enterprises on a network platform.

[0030] The following describes in detail various embodiments of the present application in conjunction with the accompanying drawings.

[0031] The present application embodiment provides a method for identifying a fake enterprise, such as Figure 1 As shown, the method may include steps S101-S105:

[0032] S101. The server receives enterprise reporting information uploaded by the enterprise to be authenticated.

[0033] Among them, the information reported by the enterprise includes at least the enterprise registration information and enterprise transaction records.

[0034] In the embodiment of the present application, enterprises that have not undergone the certification of fake enterprises on the network platform are regarded as enterprises to be certified. When the enterprises to be certified conduct bidding and tendering through the network platform, they can upload the enterprise reporting information to complete the certification and improve the credibility of the enterprise. The enterprise reporting information may include enterprise registration information and enterprise transaction records. The enterprise transaction records can be offline records or online records.

[0035] It should be noted that the server as the executor of the fake enterprise identification method is an exemplary existence and is not limited to the server. This application does not make any specific limitations on this.

[0036] S102. The server identifies the information reported by the enterprise and determines some false information in the information reported by the enterprise to be identified.

[0037] In the embodiment of the present application, the server can obtain the false information to be identified by the following method, such as Figure 2 As shown, the specific steps include:

[0038] S201. The server determines the enterprise information corresponding to the enterprise reported information based on the enterprise reported information.

[0039] The server can determine the enterprise information corresponding to the enterprise registration information based on the enterprise registration information in the enterprise reporting information. The enterprise information can be obtained by the server from a third-party organization or can be information pre-stored by the enterprise in the server. If the enterprise reporting information includes the business name of the enterprise, the server can obtain the pre-stored business name of the corresponding enterprise.

[0040] S202. The server compares the enterprise information with the information reported by the enterprise.

[0041] In one embodiment of the present application, the server may identify the enterprise registration information in the enterprise reporting information according to preset rules to obtain several groups of text information.

[0042] The server extracts keywords from each set of text information.

[0043] The server compares each keyword with the text information in the enterprise information.

[0044] Specifically, the server can input all the text in the enterprise's reported information into a neural network model according to a pre-set neural network model. The neural network model can be preset with a certain type of recognized text, such as "address", "business number", "company name", etc. The neural network model recognizes this type of text in the enterprise's reported information.

[0045] When the neural network model recognizes this type of text, the length of the text information after this type of text can be determined. For example, after "Company Name" is "First False Enterprise", and after "First False Enterprise" is the "Address" text recognized by the neural network model, the length of the "Company Name" text information is determined to be 6, and the first group of text information is the "First False Enterprise" corresponding to the "Company Name".

[0046] The server extracts the keywords "first", "false", and "enterprise" from the text information, and compares the keywords with the text information in the enterprise information. In the enterprise information, there may be "first false company", and "enterprise" and "company" are different, so the comparison between the two is unsuccessful, and the enterprise reported information and enterprise information cannot completely match, so the enterprise needs to modify the enterprise reported information.

[0047] S203. When the comparison between the enterprise information and the enterprise reported information is successful, the server determines some false information in the enterprise reported information to be identified.

[0048] The server compares the enterprise information with the enterprise reported information one by one. If the comparison is successful, the enterprise registration information and enterprise transaction records in the enterprise reported information, such as enterprise name, business number, enterprise type, and transaction records between the enterprise and other enterprises on the online platform, will be identified as false information.

[0049] S103: The server obtains comparison information corresponding to each piece of false information to be identified, and calculates a matching value between each piece of false information to be identified and the corresponding comparison information.

[0050] In order to ensure the rationality and accuracy of false enterprise identification, in the embodiment of the present application, the pre-built network platform can be a blockchain platform to calculate the matching value between each false information to be identified and the corresponding comparison information, such as Figure 3 As shown, the specific steps include:

[0051] S301. The server determines the enterprise transaction record generated by the first node on the blockchain platform based on the false information to be identified.

[0052] After obtaining the false information to be identified of the first node, the server can obtain the enterprise transaction records generated by the first node in the blockchain platform, and the first node corresponds to the enterprise to be authenticated. The enterprise may forge enterprise transaction records. This application records the enterprise transaction records through the decentralization and immutability of the blockchain to prevent enterprise-to-enterprise transaction records from being forged.

[0053] S302. The server determines that the second node corresponding to the third-party organization uploads the enterprise registration information corresponding to the first node.

[0054] In an embodiment of the present application, the second node corresponding to the third-party organization can upload the enterprise registration information corresponding to the first node to the blockchain of the present application.

[0055] In one embodiment of the present application, the enterprise registration information may also be obtained by the server from a third-party organization, corresponding to the first node, and uploaded to the blockchain. The enterprise registration information in the third-party organization may be from an official registration department.

[0056] S303. The server uses the enterprise transaction record generated by the first node on the blockchain platform and the enterprise registration information corresponding to the first node uploaded by the second node corresponding to the third-party organization as comparison information.

[0057] The server uses the enterprise transaction records generated by the blockchain platform and the enterprise registration information uploaded by the second node as the comparison information of the first node's false information to be identified. If the false information to be identified includes at least the first transaction record, the second transaction record, the enterprise name, and the enterprise type, the server uses the information in the blockchain that matches the first transaction record, the second transaction record, the enterprise name, and the enterprise type as the comparison information.

[0058] S304. The server compares each piece of false information to be identified with the comparison information one by one and generates a comparison result.

[0059] The server can compare the false information to be identified with the comparison information one by one, such as comparing the first transaction record corresponding to the false information to be identified with the specific information of the first transaction record in the comparison information, such as A and B on X month X day, and generate a comparison result. The server will then compare the second transaction record in the false information to be identified, and so on, until all the information in the false information to be identified is compared.

[0060] S305. The server calculates the matching value between each piece of false information to be identified and the corresponding comparison information according to the comparison result.

[0061] After the server has completed the one-to-one comparison between the information to be identified and the comparison information, it determines the comparison result and calculates the matching value based on the comparison result between each information to be identified and the comparison information.

[0062] In another embodiment of the present application, based on the enterprise transaction records in the false information to be identified, the server can also determine whether transaction record B is generated from the enterprise that has transactions with the enterprise to be authenticated. When the enterprise that has transactions with the enterprise to be authenticated determines that transaction record B is generated, the comparison result of transaction record B is determined to be accurate. Specifically, there is a transaction record x with enterprise b in the enterprise transaction record of enterprise a to be authenticated, and enterprise b is an authenticated enterprise. Determine whether transaction record x is generated from the corresponding node of enterprise b. If there is transaction record x in the corresponding node of enterprise b, then transaction record x is a real transaction, and transaction record x in the false information to be identified is generated, with an accurate comparison result and a matching value of 1.

[0063] S104: When the matching value does not reach the first preset threshold, the server determines that the false information to be identified is false information.

[0064] In the embodiment of the present application, the false information to be identified of the enterprise to be authenticated may not be generated on the network platform, but may exist in offline transactions. The server determines the matching value of the false information to be identified of the enterprise to be authenticated, and compares it with the first preset threshold value. The first preset threshold value may be 1, that is, when the matching value is not 1, the false information to be identified is regarded as false information.

[0065] S105. The server determines that the enterprise to be authenticated is a false enterprise based on each piece of false information, generates corresponding false enterprise prompt information and publishes it on a pre-built network platform.

[0066] The server will filter out the false information based on the fact that the corporate transaction records in the false information may contain offline transactions, and the network platform cannot know whether the corporate transaction records are false. In this case, the server will filter out the false information whose corporate transaction records cannot obtain corresponding comparison information through the network platform.

[0067] The server determines whether the matching values ​​of other false information after screening and elimination are all 1. If the matching values ​​of other false information are not all 1, the enterprise to be authenticated is authenticated as a false enterprise. In order to remind other enterprises to know the false enterprise, the server can generate false enterprise prompt information, such as "Friendly reminder: the nth enterprise is a false enterprise", etc., and publish it on the network platform. In addition, the server can remind the corresponding bidding and bidding enterprises of the false enterprise and the trading enterprise that the false enterprise is a false enterprise.

[0068] Through the above scheme, this application can ensure that fake enterprises can be identified on the network platform. When enterprises conduct procurement through the network platform, they can determine whether the enterprise is a fake enterprise based on the information reported by the enterprise. Determine the rationality and legality of procurement behavior and avoid other enterprises being deceived by fake enterprises during transactions. By identifying fake enterprises, the network platform can also create a green and healthy network platform.

[0069] When an enterprise views other enterprises through the network platform and selects other enterprises for purchase, the enterprise needs to ensure that the transaction enterprise is a real enterprise before sending the purchase transaction behavior to enhance the trust between enterprises. Therefore, this application provides the following embodiments, such as Figure 4 As shown, it specifically includes steps S401-S405:

[0070] S401: The server obtains authentication information sent by the first terminal.

[0071] The first terminal corresponds to a terminal that has been registered on a pre-built network platform; and the authentication information includes an enterprise logo.

[0072] In the embodiment of the present application, the first terminal corresponds to a terminal that has been registered on a pre-built network platform. The first terminal can determine whether the other party is a fake enterprise before selecting a seller enterprise or a buyer enterprise for a transaction. The first terminal can send the enterprise identification of the seller or buyer enterprise to be authenticated to the server.

[0073] In another embodiment of the present application, after obtaining the authentication information sent by the first terminal, the server can first determine whether the enterprise corresponding to the first terminal is a false enterprise or an enterprise to be authenticated, so as to ensure the security and integrity of the network platform.

[0074] S402: The server determines the historical authentication record of the enterprise of interest corresponding to the first terminal according to the authentication information to determine whether the enterprise of interest is an enterprise to be authenticated.

[0075] The server determines whether there is a historical authentication record for the enterprise of interest according to the enterprise identifier in the authentication information, and if there is a historical authentication record, determines the result of the historical authentication record, such as whether the enterprise of interest is a false enterprise or a non-false enterprise; if there is no historical authentication record, the enterprise of interest is an enterprise to be authenticated.

[0076] When there is a historical authentication record for the enterprise of interest, the server may send the historical authentication record result of the historical authentication record to the first terminal.

[0077] S403: When the enterprise of interest is an enterprise to be authenticated, the server generates authentication prompt information and sends it to a corresponding terminal of the enterprise of interest to prompt the enterprise of interest to upload the enterprise reporting information.

[0078] When the interested enterprise is a to-be-certified enterprise, the server may generate to-be-certified prompt information, which is used to prompt the interested enterprise to perform the authentication. The server prompts the interested enterprise to upload the enterprise reporting information so that the server can perform the authentication work of steps S101-S105.

[0079] S404: The server obtains feedback information from the enterprise of interest.

[0080] After receiving the prompt information for authentication, the corresponding terminal of the interested enterprise can choose to agree to the authentication or refuse the authentication, and send the agreement or refusal of authentication as feedback information to the server.

[0081] S405: When the feedback information is authentication rejection, the server generates an authentication rejection record and records it in a corresponding database.

[0082] In the embodiment of the present application, if the interested enterprise agrees to the certification, the enterprise reporting information can be uploaded to perform the certification work of steps S101-S105. If the interested enterprise refuses the certification, the server can record the refusal of certification and add it to the refusal record of the interested enterprise, and the refusal record of certification is stored in the database of the server.

[0083] In one embodiment of the present application, in order to ensure the accuracy of enterprise information, the network platform can set a corresponding number of times for the enterprise to refuse authentication. If the corresponding number is exceeded, authentication cannot be refused. Thus, the server can obtain the number of authentication rejection records of the interested enterprise in the database. When the number of authentication rejection records exceeds a third preset threshold, such as 3 times, the server can send an interface for uploading enterprise reporting information to the corresponding terminal of the interested enterprise, and determine whether the corresponding terminal of the interested enterprise has performed corresponding operations on the uploaded enterprise reporting information. In the case that the interested enterprise does not perform corresponding operations on the uploaded enterprise reporting information, the account of the interested enterprise is controlled to be deregistered from the network platform within a preset time period.

[0084] In the actual enterprise network platform, when an enterprise uses the network platform, it first needs to register an account on the network platform. Some criminals may use the names of some large enterprises and other information to register the network platform in advance. In order to prevent such behavior, this application can be constrained through the following embodiments, such as Figure 5 As shown, the following steps are included:

[0085] S501. The server obtains platform registration information sent by the second terminal.

[0086] The platform registration information at least includes the enterprise name, enterprise address, and enterprise type; the second terminal corresponds to a terminal that is not registered on the network platform.

[0087] When the second terminal registers on the network platform, it can send the company name, company address, and company type of the registered company to the server.

[0088] S502: The server initiates authentication to a third-party organization based on the platform registration information.

[0089] The server obtains the information of the corresponding enterprise from the third-party organization based on the platform registration information, such as the enterprise name in the platform registration information, or forwards the platform registration information sent by the second terminal to the third-party organization to authenticate the enterprise corresponding to the second terminal. The third-party organization can be an organization that detects enterprise information or an official enterprise registration organization.

[0090] S503: When the platform registration information is successfully authenticated, the server generates registration account information corresponding to the second terminal and sends it to the second terminal, so that the second terminal uses the network platform according to the registration account information.

[0091] Through the above scheme, preliminary information authentication of enterprises can be carried out before enterprises register on the network platform, which can resist some enterprises from registering accounts corresponding to other company names and other bad behaviors, avoid disputes on the network platform, and avoid the emergence of fake enterprises. At the same time, it can also improve the experience of enterprises using the network platform that can identify fake enterprises.

[0092] When server companies communicate through online platforms, they may convey negative information, fraudulent information, etc. There is a possibility that such companies are fake companies, so it is necessary to monitor such communication information, and at the same time avoid damage to the interests of one party's company.

[0093] Specifically, the server first obtains the communication data between enterprises on the network platform. It should be noted that the communication data can be text information or voice information. Then, the server extracts keywords from the communication data. For example, the server generates text from the text information or voice information and determines whether each word in the text contains "purchase" or "quantity".

[0094] The server determines whether there is negative information in the keyword based on a pre-trained neural network model. The server can input the keyword into the pre-trained neural network model, and the pre-trained neural network model can be trained using words that are likely to appear in online and offline purchasing processes as sample data.

[0095] Finally, when there is negative information in the keyword, the server sends a prompt message to the corresponding terminal of the enterprise that issued the negative information to remind the enterprise that issued the negative information.

[0096] When the server determines that the number of times the enterprise that issues negative information issues negative information is greater than a second preset threshold, the server generates announcement information. The announcement information is information published on the network platform. After reminding the enterprise that issues negative information, if it still sends negative information, the server can announce the enterprise's behavior of issuing negative information on the network platform.

[0097] In the embodiment of the present application, when an enterprise browses through the network platform and chooses to purchase and sell products related to its own enterprise, the network platform can filter and push enterprises for the enterprise:

[0098] First, the server obtains the enterprise type corresponding to the terminal currently using the network platform.

[0099] Then, the server filters the corresponding fake enterprises on the network platform according to the enterprise type, and pushes the enterprises corresponding to the enterprise type to the terminal currently using the network platform. Filtering out fake enterprises and pushing enterprises corresponding to the enterprise type of the browsing enterprise can improve the efficiency of enterprises' purchase or sales on the network platform and improve the experience of enterprises.

[0100] Through the above scheme, this application can identify authentic and reliable enterprises on the online platform, improve the trust of enterprises trading on the online platform, and ensure a good online platform user experience.

[0101] Figure 6 A fake enterprise identification device provided in an embodiment of the present application includes:

[0102] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to implement the function:

[0103] Receive enterprise reporting information uploaded by the enterprise to be certified. The enterprise reporting information includes at least enterprise registration information and enterprise transaction records. Identify the enterprise reporting information and determine a number of false information to be identified in the enterprise reporting information. Obtain comparison information corresponding to each false information to be identified, and calculate the matching value between each false information to be identified and the corresponding comparison information. If the matching value does not reach the first preset threshold, determine that the false information to be identified is false information. According to each false information, determine that the enterprise to be certified is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform.

[0104] The embodiment of the present application also provides a non-volatile computer storage medium for false enterprise identification, which stores computer executable instructions, and the computer executable instructions are set to:

[0105] Receive enterprise reporting information uploaded by the enterprise to be certified. The enterprise reporting information includes at least enterprise registration information and enterprise transaction records. Identify the enterprise reporting information and determine a number of false information to be identified in the enterprise reporting information. Obtain comparison information corresponding to each false information to be identified, and calculate the matching value between each false information to be identified and the corresponding comparison information. If the matching value does not reach the first preset threshold, determine that the false information to be identified is false information. According to each false information, determine that the enterprise to be certified is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on a pre-built network platform.

[0106] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0107] The devices, media and methods provided in the embodiments of the present application correspond one to one, and therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0108] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0109] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for identifying fake enterprises, the method is applied to a pre-built network platform, characterized in that: The method comprises: Receiving enterprise reporting information uploaded by the enterprise to be certified; wherein the enterprise reporting information at least includes enterprise registration information and enterprise transaction records; Identify the information reported by the enterprise and determine some false information in the information reported by the enterprise to be identified; Obtaining comparison information corresponding to each piece of false information to be identified, and calculating a matching value between each piece of false information to be identified and the corresponding comparison information; When the matching value does not reach the first preset threshold, determining that the false information to be identified is false information; According to each of the false information, determine that the enterprise to be authenticated is a false enterprise, so as to generate corresponding false enterprise prompt information and publish it on the pre-built network platform; Among them, according to the information reported by the enterprise, several pieces of false information to be identified in the information reported by the enterprise are determined, specifically including: Determining enterprise information corresponding to the enterprise reported information according to the enterprise reported information; Comparing the enterprise information with the information reported by the enterprise; In the case where the enterprise information is successfully compared with the enterprise reported information, determining some false information to be identified in the enterprise reported information; The step of comparing the enterprise information with the enterprise reported information specifically includes: According to preset rules, the enterprise registration information in the enterprise reporting information is identified to obtain a plurality of groups of text information; the text information is obtained by identifying a preset type of text through a preset neural network model; Extract keywords from each group of text information; Comparing each of the keywords with the text information in the enterprise information; Wherein, the method further comprises: Acquire authentication information sent by a first terminal; wherein the first terminal corresponds to a terminal registered on the pre-built network platform; and the authentication information includes an enterprise identification; Determine, according to the authentication information, a historical authentication record of the enterprise of interest corresponding to the first terminal, so as to determine whether the enterprise of interest is the enterprise to be authenticated; In the case where the enterprise of interest is the enterprise to be certified, generating certification prompt information and sending it to the terminal corresponding to the enterprise of interest to prompt the enterprise of interest to upload the enterprise reporting information; Obtaining feedback information from the interested enterprises; In the case where the feedback information is a rejection of authentication, generating a rejection of authentication record and recording it in a corresponding database; Wherein, the method further comprises: Obtaining communication data between enterprises on the network platform; extracting keywords from the communication data; Based on a pre-trained neural network model, determining whether there is negative information in the keyword; In the case where negative information exists in the keyword, a prompt message is sent to the corresponding terminal of the enterprise that issued the negative information to remind the enterprise that issued the negative information; When it is determined that the number of times the enterprise that issues negative information issues negative information is greater than a second preset threshold, an announcement information is generated; wherein the announcement information is information published on the network platform.

2. The method according to claim 1, characterized in that: The pre-built network platform is a blockchain platform, and the blockchain platform includes a plurality of first nodes, and the first nodes correspond to the enterprise to be authenticated; Obtaining comparison information corresponding to each of the false information to be identified, and calculating a matching value between each of the false information to be identified and the corresponding comparison information, specifically includes: Determining, based on the false information to be identified, the enterprise transaction record generated by the first node on the blockchain platform; and Determine a second node corresponding to a third-party organization to upload the enterprise registration information corresponding to the first node; and using the enterprise transaction record generated by the first node on the blockchain platform and the enterprise registration information corresponding to the first node uploaded by the second node corresponding to the third-party institution as the comparison information; Compare each of the false information to be identified with the comparison information one by one to generate a comparison result; According to the comparison result, the matching value between each piece of false information to be identified and the corresponding comparison information is calculated.

3. The method according to claim 1, characterized in that: The method further comprises: Acquire platform registration information sent by the second terminal; wherein the platform registration information at least includes the enterprise name, enterprise address and enterprise type; the second terminal corresponds to a terminal that is not registered on the network platform; Initiate authentication with a third-party organization based on the platform registration information; When the authentication of the platform registration information is successful, the registration account information corresponding to the second terminal is generated and sent to the second terminal, so that the second terminal uses the network platform according to the registration account information.

4. The method according to claim 1, characterized in that: The method further comprises: Obtaining the enterprise type corresponding to the terminal currently using the network platform; According to the enterprise type, corresponding false enterprises on the network platform are filtered, and enterprises corresponding to the enterprise type are pushed to the terminal currently using the network platform.

5. A false enterprise identification device, characterized in that: The device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a false enterprise identification method as described in any one of claims 1-4 above.

6. A non-volatile computer storage medium for false enterprise identification, storing computer executable instructions, characterized in that: The computer executable instructions can execute a false enterprise identification method as described in any one of claims 1 to 4 above.

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