CN113821474A - Data processing method, device, equipment and storage medium - Google Patents
Data processing method, device, equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/11—File system administration, e.g. details of archiving or snapshots
- G06F16/116—Details of conversion of file system types or formats
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/14—Details of searching files based on file metadata
- G06F16/148—File search processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/17—Details of further file system functions
- G06F16/1734—Details of monitoring file system events, e.g. by the use of hooks, filter drivers, logs
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
Abstract
The invention discloses a data processing method, a data processing device, data processing equipment and a storage medium. Wherein the method is applied to a trusted Artificial Intelligence (AI) system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the method comprises the following steps: acquiring target information of a buyer and data description information of a seller, and determining intention data description according to the target information and the data description information; generating an initial file to be executed according to the intention data description and the target information; checking the initial file to be executed to obtain a target file after checking feedback; obtaining data authorization of the buyer and the seller to the target file, and executing the target file based on the data authorization.
Description
Technical Field
The present invention relates to the field of internet and block chain technologies, and in particular, to a data processing method, apparatus, device, and storage medium.
Background
The current data filtering scheme mainly screens according to established rules, achieves data filtering, improves data matching degree, and optimizes user experience and the like. However, data filtering in the data kettle needs combined verification, and is a verification process with an angle and a problem, a needed conclusion is obtained, and data details cannot be taken out of the kettle. No effective solution to this problem is currently available.
Disclosure of Invention
In order to solve the existing technical problems, the present invention mainly aims to provide a data processing method, apparatus, device and storage medium.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
in a first aspect, the invention provides a data processing method, which is applied to a trusted Artificial Intelligence (AI) system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the method comprises the following steps:
acquiring target information of a buyer and data description information of a seller, and determining intention data description according to the target information and the data description information;
generating an initial file to be executed according to the intention data description and the target information;
checking the initial file to be executed to obtain a target file after checking feedback;
obtaining data authorization of the buyer and the seller to the target file, and executing the target file based on the data authorization.
In the above solution, the determining an intention data description according to the target information and the data description information includes:
comparing the data field of the target information with the data field of the data description information to obtain a comparison result;
under the condition that the comparison result shows that the data field of the target information is the same as the data field of the data description information, judging whether the target information is a subset of the data description information;
in a case where the target information is a subset of the data description information, the intention data description corresponding to the target information is determined in the data description information.
In the above solution, the generating an initial file to be executed according to the intention data description and the target information includes:
judging whether each piece of required content in the target information exists and a check function cannot be generated;
under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description;
obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function;
and generating an initial file to be executed based on the judgment statement.
In the above scheme, the checking the initial file to be executed to obtain the target file after the check feedback includes:
analyzing the initial file to be executed to obtain the data format of the initial file;
judging whether the data format conforms to the data format described by the intention data;
under the condition that the data format does not conform to the data format described by the intention data, carrying out format conversion on fields in the initial file to obtain a first target file;
judging whether the first target file has preset check information or not, and obtaining a judgment result;
and determining the target file after the feedback is checked according to the judgment result.
In the above scheme, the preset check information includes sensitive information and filtering information; the judging whether the first target file has preset checking information or not to obtain a judgment result includes:
judging whether the first target file has the sensitive information or not;
under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file;
and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
In the foregoing solution, the determining, according to the determination result, the target file after the feedback check includes:
taking the second target file as the target file under the condition that the judgment result shows that the second target file meets the filtering information;
and under the condition that the judgment result shows that the second target file does not meet the filtering information, filtering the second target file to determine the target file.
In the above solution, the obtaining of the data authorization of the buyer and the seller to the target file includes:
obtaining a first data authorization of the buyer to the target file and a second data authorization of the buyer to the target file;
determining the data grant based on the first data grant and the second data grant.
In a second aspect, the present invention further provides a data processing apparatus, which is applied to a trusted artificial intelligence AI system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the device comprises: the system comprises a determining unit, a generating unit, a checking unit and an executing unit, wherein the determining unit is used for obtaining target information of a buyer and data description information of a seller and determining intention data description according to the target information and the data description information;
the generating unit is used for generating an initial file to be executed according to the intention data description and the target information;
the checking unit is used for checking the initial file to be executed and obtaining a target file after checking feedback;
the execution unit is used for obtaining the data authorization of the buyer and the seller to the target file and executing the target file based on the data authorization.
In the above scheme, the determining unit is further configured to compare a data field of the target information with a data field of the data description information to obtain a comparison result; under the condition that the comparison result shows that the data field of the target information is the same as the data field of the data description information, judging whether the target information is a subset of the data description information; in a case where the target information is a subset of the data description information, the intention data description corresponding to the target information is determined in the data description information.
In the above scheme, the generating unit is further configured to determine whether each piece of demand content in the target information has a check function that cannot be generated; under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description; obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function; and generating an initial file to be executed based on the judgment statement.
In the above scheme, the checking unit is further configured to analyze the initial file to be executed, and obtain a data format of the initial file; judging whether the data format conforms to the data format described by the intention data; under the condition that the data format does not conform to the data format described by the intention data, carrying out format conversion on fields in the initial file to obtain a first target file; judging whether the first target file has preset check information or not, and obtaining a judgment result; and determining the target file after the feedback is checked according to the judgment result.
In the above scheme, the preset check information includes sensitive information and filtering information; the checking unit is further configured to determine whether the first target file has the sensitive information; under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file; and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
In the foregoing solution, the checking unit is further configured to, when the determination result indicates that the second target file meets the filtering information, take the second target file as the target file; and under the condition that the judgment result shows that the second target file does not meet the filtering information, filtering the second target file to determine the target file.
In the above solution, the executing unit is further configured to obtain a first data authorization of the target file by the buyer and a second data authorization of the target file by the buyer; determining the data grant based on the first data grant and the second data grant.
In a third aspect, an embodiment of the present invention provides a storage medium, where a computer program is stored on the storage medium; the computer program, when executed by a processor, implements the steps of any of the methods described above.
In a fourth aspect, an embodiment of the present invention provides a data processing apparatus, where the data processing apparatus includes: a processor and a memory for storing a computer program operable on the processor, wherein the processor is operable to perform the steps of any of the above methods when executing the computer program.
The embodiment of the invention provides a data processing method, a data processing device, data processing equipment and a storage medium. Wherein, the method is applied to a credible artificial intelligence AI system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the method comprises the following steps: acquiring target information of a buyer and data description information of a seller, and determining intention data description according to the target information and the data description information; generating an initial file to be executed according to the intention data description and the target information; checking the initial file to be executed to obtain a target file after checking feedback; obtaining data authorization of the buyer and the seller to the target file, and executing the target file based on the data authorization. By adopting the technical scheme of the embodiment of the invention, intention data description is determined according to the target information and the data description information; generating an initial file to be executed according to the intention data description and the target information; checking the initial file to be executed to obtain a target file after checking feedback; and obtaining data authorization of the buyer and the seller to the target file, executing the target file based on the data authorization, conveniently carrying out inspection with angles and problems, and obtaining a needed conclusion.
Drawings
Fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a data processing apparatus according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a hardware entity structure of a data processing device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the following describes specific technical solutions of the present invention in further detail with reference to the accompanying drawings in the embodiments of the present invention. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present invention. As shown in fig. 1, the method is applied to an trusted Artificial Intelligence (AI) system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the method comprises the following steps:
s101: target information of a buyer and data description information of a seller are obtained, and intention data description is determined according to the target information and the data description information.
It should be noted that the trusted AI system at least includes a buyer AI agent and a seller AI agent; wherein the buyer AI agent can be understood as an agent of the data demander; the seller AI agent may be understood to be an agent of the data operator. For ease of understanding, the buyer AI agent may be denoted agent A; the vendor AI agent may be denoted agent B.
Obtaining target information of a buyer and data description information of a seller; the target information may be determined according to an actual situation, which is not limited herein, and as an example, the target information may be demand information; the data description information may be determined according to actual conditions, and is not limited herein, and as an example, the data description information may be data description information performed on data provided by a seller.
Determining the intention data description according to the target information and the data description information may be determining attribute information representing the target information and the data description information according to the target information and the data description information, and determining the intention data description according to the attribute information; the attribute information may be determined according to an actual situation, and is not limited herein, and as an example, the attribute information may include at least an affiliation of a data field, the target information, and the data description information.
For ease of understanding, a practical application scenario is illustrated here. In practical application, a machine agent A of the buyer obtains the requirement of the buyer; the seller's machine agent B obtains the data description information of the seller's data; the buyer's machine agent a looks for seller data descriptions that may be in compliance with the buyer's requirements. And confirming the intention data by comparing whether the data fields and the required data items are subsets of the data description.
S102: and generating an initial file to be executed according to the intention data description and the target information.
It should be noted that, the generating of the initial file to be executed according to the intention data description and the target information may be to form checking data to be executed according to the intention data description, and generate the initial file to be executed according to the checking data and the target information. The check data may be determined according to an actual situation, and is not limited herein, and as an example, the check data may include at least a check function, a judgment statement, and the like. As an example, the forming of the check data to be executed according to the intention data description, and the generating of the initial file to be executed according to the check data and the target information may be to determine whether or not each required content in the target information has a check function that cannot be generated; under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description; obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function; and generating an initial file to be executed based on the judgment statement.
S103: and checking the initial file to be executed to obtain a target file after checking feedback.
It should be noted that, the checking of the initial file to be executed is performed, and the target file after the checking feedback is obtained may be a target file after the checking feedback is obtained by performing a command check to be rechecked on the initial file to be executed. The command check to be re-checked may be determined according to an actual situation, and is not limited herein, and as an example, the command check to be re-checked may include data format check, sensitive information check, filtering requirement check, and the like.
In practical application, the initial file to be executed may be a data item application to be checked; the seller machine agent B of the data description receives the data item application to be checked sent by A, carries out format conversion on necessary data items according to code analysis, and checks whether the program is in need of a rechecking command.
S104: obtaining data authorization of the buyer and the seller to the target file, and executing the target file based on the data authorization.
It should be noted that obtaining the data authorization of the target file by the buyer and the seller can be understood as obtaining the common authorization of the target file by the buyer and the seller.
Authorizing execution of the target file based on the data may be authorizing execution of the target file program based on the data.
A, B in actual application collectively authorize and execute the program, and return the execution result.
According to the data processing method provided by the embodiment of the invention, intention data description is determined according to the target information and the data description information; generating an initial file to be executed according to the intention data description and the target information; checking the initial file to be executed to obtain a target file after checking feedback; and obtaining data authorization of the buyer and the seller to the target file, executing the target file based on the data authorization, conveniently carrying out inspection with angles and problems, and obtaining a needed conclusion.
In an optional embodiment of the invention, the determining an intention data description according to the target information and the data description information comprises: comparing the data field of the target information with the data field of the data description information to obtain a comparison result; under the condition that the comparison result shows that the data field of the target information is the same as the data field of the data description information, judging whether the target information is a subset of the data description information; in a case where the target information is a subset of the data description information, the intention data description corresponding to the target information is determined in the data description information.
It should be noted that, comparing the data field of the target information with the data field of the data description information, and obtaining the comparison result may be comparing the data field of the target information with the data field of the data description information, and obtaining the comparison result that the data field of the target information is the same as the data field of the data description information or the data field of the target information is different from the data field of the data description information.
In a case that the comparison result indicates that the data field of the target information is the same as the data field of the data description information, determining whether the target information is a subset of the data description information may be determining whether the target information belongs to the subset of the data description information, and determining whether the target information belongs to the subset of the data description information or not, where the comparison result indicates that the data field of the target information is the same as the data field of the data description information.
In a case where the target information is a subset of the data description information, determining that the intention data description corresponding to the target information in the data description information may be determining that data description information related to the target information in the data description information is the intention data description in a case where the target information is the subset of the data description information.
In an optional embodiment of the present invention, the generating an initial file to be executed according to the intention data description and the target information includes: judging whether each piece of required content in the target information exists and a check function cannot be generated; under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description; obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function; and generating an initial file to be executed based on the judgment statement.
It should be noted that, it is determined whether each piece of demand content in the target information cannot generate the check function, as long as it is considered that the demand information in the target information of the buyer may have a situation that the check function cannot be generated due to imperfection; generally, if the required information in the target information of the buyer is perfect and needs no supplement, the checking function can be generated. In practical applications, the check function may also be referred to as a demand function.
The generating of the judgment statement may be that, in a case where there is no requirement content in the target information that cannot generate a check function, a data description similar to the check function is matched in the intention data description based on the check function, and a judgment statement is generated according to the similar data description, in a case where there is no requirement content in the target information that cannot generate a check function, and a data description similar to the check function is matched in the intention data description based on the check function. For convenience of understanding, the check functions may be named according to the english keywords corresponding to the requirements, and the annotation text of the requirements is added to each check function. For example, if the requirement is a diabetic patient data set, then the inspection function may be named "CheckDiabetes ()" and a comment "/" is placed before the function that requires a diabetic patient data set. And (4) matching the data set description of the intention data set according to the specific content of the requirement in each check function to generate a judgment statement. For example, it is checked whether the function is a Diabetes patient data set, and whether a case (disease) contains Diabetes statements is determined, and a comment is added.
The step of obtaining the supplemental information of the buyer may be feeding back to a buyer agent node for supplementation when each required content in the target information cannot generate the checking function, so as to obtain the supplemental information of the buyer. The supplemental information may be determined according to actual conditions, and is not limited herein, and as an example, the supplemental information may be a specific description of content required by the buyer.
Updating the target information according to the supplementary information, wherein the obtaining of the updated target information can be supplementing the supplementary information to the target information to obtain the updated target information; the supplementary information can perfect the content of the requirement that the target information can not generate the check function, so that the updated target information can generate the check function.
Judging whether each piece of demand content in the updated target information has the check function which cannot be generated or not, if so, continuing to supplement until each piece of demand content in the target information which is updated for many times does not have the check function which cannot be generated, wherein the process of generating the check function is a circular process.
Generating an initial file to be executed based on the judgment statement; the initial file may be determined according to an actual situation, which is not limited herein, and as an example, the initial file may be a program file.
For convenience of understanding, a practical application scenario is illustrated here, and the buyer's machine agent a forms, for each intent data set, a corresponding application (which is an executable program) for checking data items to be executed, for a certain intent data description and buyer's requirement. And newly building an executable program file, and filling the executable program according to the data description of the requirement and intention data set. The specific process is as follows:
firstly, generating a check function aiming at each requirement, naming the check function according to English keywords corresponding to the requirement, and adding required annotation texts on each check function. For example, if the requirement is a diabetic patient data set, then the inspection function may be named "CheckDiabetes ()" and a comment "/" is placed before the function that requires a diabetic patient data set.
Secondly, inside each check function, the data set description of the intention data set is matched according to the specific content of the requirement, and a judgment statement is generated. For example, it is checked whether the function is a Diabetes patient data set, and whether a case (disease) contains Diabetes statements is determined, and a comment is added.
Thirdly, if the demand function which can not be generated exists, the demand function is fed back to the buyer node for supplementation. And if all the programs are generated successfully, sending the program to be executed to the agent of the data set for checking.
In an optional embodiment of the present invention, the checking the initial file to be executed to obtain a target file after the checking feedback includes: analyzing the initial file to be executed to obtain the data format of the initial file; judging whether the data format conforms to the data format described by the intention data; under the condition that the data format does not conform to the data format described by the intention data, carrying out format conversion on fields in the initial file to obtain a first target file; judging whether the first target file has preset check information or not, and obtaining a judgment result; and determining the target file after the feedback is checked according to the judgment result.
It should be noted that, the initial file to be executed is analyzed to obtain the data format of the initial file; the initial file may be determined according to an actual situation, and is not limited herein. As an example, the initial file may be a program file. The data format may be determined according to actual conditions, and is not limited herein. As an example, the data format may be that a certain numeric parameter type is defined in a program as Integer type or floating point type Float, etc.
Determining whether the data format conforms to the data format of the intended data description may be determining whether the data format is the same as the data format of the intended data description, so as to obtain a result that the data format is the same as the data format of the intended data description or the data format is different from the data format of the intended data description.
And under the condition that the data format does not conform to the data format described by the intention data, performing format conversion on the field in the initial file to obtain a first target file, wherein under the condition that the data format is different from the data format described by the intention data, performing format conversion on the field in the initial file to obtain a converted initial file, namely the first target file.
Judging whether the first target file has preset check information or not, wherein the obtained judgment result can be a judgment result of judging whether the first target file has the preset check information or not, and a judgment result of whether the first target file has the preset check information or not is obtained; the preset check information may be determined according to an actual situation, and is not limited herein, and as an example, the preset check information may at least include sensitive information, filtering information, and the like. As an example, whether the first target file has preset check information is determined, and the obtained determination result may be to determine whether the first target file has the sensitive information; under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file; and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
And determining the target file after the feedback check according to the judgment result, wherein the target file after the feedback check can be checked under the condition that the first target file has preset check information, and the target file after the feedback check is determined. As an example, the target file is subjected to an inspection process, it is determined that the target file after the inspection feedback may be a target file subjected to format conversion, a converted target file is obtained, and whether the converted target file has a command to be reviewed is checked.
In practical application, the target file may be a data item application file to be checked, and the seller machine agent B described in data receives the data item application file to be checked sent by a, performs format conversion on necessary data items according to code analysis, and checks whether the program has a command to be reviewed.
In an optional embodiment of the present invention, the preset check information includes sensitive information and filtering information; the judging whether the first target file has preset checking information or not to obtain a judgment result includes: judging whether the first target file has the sensitive information or not; under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file; and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
It should be noted that the sensitive information may be determined according to an actual situation, which is not limited herein, and as an example, the sensitive information may be whether a program requiring network communication exists; whether there is a store or copy instruction; the program requires address information, address, name, etc. as sensitive data for the seller to mark. The filtering information may be determined according to an actual situation, and is not limited herein, and as an example, the filtering information may be output bytes controlled within a preset range; as an example, the preset range may be a prescribed range; for example, when checking whether an entry is present, the output byte is controlled to be within 8 bytes, and when checking the statistics field, the output byte is controlled to be within 512 bytes.
The determining whether the first target file has the sensitive information may be checking whether the first target file has the sensitive information to obtain a result that the first target file has the sensitive information or the first target file does not have the sensitive information.
And prompting the seller to review and process the sensitive information in the first target file under the condition that the first target file has the sensitive information, and feeding the first target file back to a seller agent node under the condition that the second target file is determined to be the first target file with the sensitive information, and prompting the seller to review and process the sensitive information in the first target file so as to determine the second target file. As an example, the seller is prompted to review and process the sensitive information in the first object file, and then to determine that the second object file can be the sensitive data in the first object file requiring address information, address, name, and the like marked by the seller, the seller is prompted with the check command to wait for the review. The seller may request that the detailed address be obscured, leaving the general geographic information as a second destination file.
The determining whether the second target file satisfies the filtering information, and the determining result that the second target file satisfies the filtering information or the second target file does not satisfy the filtering information may be determining whether the second target file satisfies the filtering information or the second target file does not satisfy the filtering information. As an example, the checking whether the second target file satisfies the filtering information may be checking whether the size of the output value of each check function in the second target file is within a specified range, for example, when checking whether an entry is present, the output byte is controlled to be within 8 bytes, and when checking the statistics field, the output byte is controlled to be within 512 bytes.
In practical application, the first target file is taken as a program to be executed for example description, the program to be executed is analyzed, whether a data format accords with a data format in a data set is checked, and if the data format does not accord with the data format, data format conversion is carried out. For example, if a numeric parameter type is defined as Integer in the program but floating point type Float in the data set, then the fields in the program are formatted. The sensitive information is checked, and if so, the sensitive information is fed back to the seller node, and the buyer AI is allowed to execute the program. For example: whether a program needing network communication exists or not; whether there is a store or copy instruction; and when the required address information, address, name and the like in the program are sensitive data marked by the seller, prompting the inspection command to the seller to wait for the repeat. The seller may request that the detailed address be hidden, leave general geographic information, and so on. It is checked whether the filtering requirements are met. Each check function checks whether the size of the output value is within a specified range, for example, when checking whether an item is present, the output byte is controlled within 8 bytes, and when checking the statistic field, the output byte is controlled within 512 bytes.
In an optional embodiment of the present invention, the determining, according to the determination result, a target file after checking feedback includes: taking the second target file as the target file under the condition that the judgment result shows that the second target file meets the filtering information; and under the condition that the judgment result shows that the second target file does not meet the filtering information, filtering the second target file to determine the target file.
In this embodiment, when the determination result indicates that the second target file does not satisfy the filtering information, the second target file is filtered to determine the target file; the filtering process may be determined according to actual conditions, and is not limited herein, and as an example, the filtering process may be to control the size of the output value of the second target file within a specified range. For example, when checking whether the entry is an entry, the output byte is controlled to be within 8 bytes, and when checking the statistic field, the output byte is controlled to be within 512 bytes.
In an optional embodiment of the present invention, the obtaining of the data authorization of the target file by the buyer and the seller comprises: obtaining a first data authorization of the buyer to the target file and a second data authorization of the buyer to the target file; determining the data grant based on the first data grant and the second data grant.
In this embodiment, obtaining the first data authorization of the target file by the buyer and the second data authorization of the target file by the buyer may be obtaining the authorization of the target file by the machine agent of the buyer and the authorization of the target file by the machine agent of the buyer.
Determining the data authorization from the first data authorization and the second data authorization may be based on the authorization of the target file by the buyer's machine agent and the authorization of the target file by the buyer's machine agent to determine a common authorization for both the buyer's machine agent and the buyer's machine agent.
According to the data processing method provided by the embodiment of the invention, the data filtering in the data kettle is combined with the verified intelligent contract, the verification process with angles and problems is carried out, the needed conclusion is obtained, and the data without details is taken out of the kettle.
The embodiment of the invention considers that the current data filtering scheme is mainly used for screening according to the established rule, thereby realizing the data filtering, improving the data matching degree, optimizing the user experience and the like. However, data filtering in the data kettle is an intelligent contract combined with verification, is a verification process with an angle and problems, and can obtain a needed conclusion, and cannot take data details out of the kettle. And filtering the data. When the intelligent contract of the verifier is executed, if the data is not directly available, how to process the data is fed back to the AI agent of the seller for further processing. For understanding the embodiment of the present invention, an exemplary data processing method in the embodiment of the present invention is specifically a method of data filtering. The method comprises the following specific steps:
in the first step, the buyer's machine agent A looks for seller data descriptions that may be matched according to the buyer's needs. And confirming the intention data by comparing whether the data fields and the required data items are subsets of the data description.
In the second step, A, for the description of the certain intention data and the buyer's requirement, a corresponding application (which is an executable program) of the inspection data item to be executed is formed for each intention data set. And newly building an executable program file, and filling the executable program according to the data description of the requirement and intention data set.
(1) And generating a check function aiming at each requirement, naming the check function according to the English keyword corresponding to the requirement, and adding required annotation texts on each check function. For example, if the requirement is a diabetic patient data set, then the inspection function may be named "CheckDiabetes ()" and a comment "/" is placed before the function that requires a diabetic patient data set.
(2) And (4) matching the data set description of the intention data set according to the specific content of the requirement in each check function to generate a judgment statement. For example, it is checked whether the function is a Diabetes patient data set, and whether a case (disease) contains Diabetes statements is determined, and a comment is added.
(3) And if the demand function which cannot be generated exists, feeding back the demand function to the buyer node for supplementation. And if all the programs are generated successfully, sending the program to be executed to the agent of the data set for checking.
Thirdly, the seller machine agent B described by the data receives the data item application to be checked sent by the A, carries out format conversion on necessary data items according to code analysis, and checks whether the program is to be checked.
(1) And analyzing the program to be executed, checking whether the data format accords with the data format in the data set, and if not, converting the data format. For example, if a numeric parameter type is defined as Integer in the program but floating point type Float in the data set, then the fields in the program are formatted.
(2) The sensitive information is checked, and if so, the sensitive information is fed back to the seller node, and the buyer AI is allowed to execute the program. For example: whether a program needing network communication exists or not; whether there is a store or copy instruction; and when the required address information, address, name and the like in the program are sensitive data marked by the seller, prompting the inspection command to the seller to wait for the repeat. The seller may request that the detailed address be hidden, leave general geographic information, and so on.
(3) It is checked whether the filtering requirements are met. Each check function checks whether the size of the output value is within a specified range, for example, when checking whether an item is present, the output byte is controlled within 8 bytes, and when checking the statistic field, the output byte is controlled within 512 bytes.
(4) And B, the program version after the feedback is checked is given to A, and the program does not allow the A to edit and is a read-only program.
In a fourth step, A, B co-authorizes and executes the program, returning the execution results.
It should be noted that the terms appearing herein have been described in detail above, and are not repeated herein.
Fig. 2 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present invention, and as shown in fig. 2, the apparatus 200 is applied to a trusted artificial intelligence AI system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the apparatus 200 comprises: a determination unit 201, a generation unit 202, a check unit 203 and an execution unit 204, wherein the determination unit 201 is used for obtaining target information of a buyer and data description information of a seller and determining intention data description according to the target information and the data description information;
the generating unit 202 is configured to generate an initial file to be executed according to the intention data description and the target information;
the checking unit 203 is configured to check the initial file to be executed, and obtain a target file after checking feedback;
the executing unit 204 is configured to obtain data authorization of the target file by the buyer and the seller, and execute the target file based on the data authorization.
In other embodiments, the determining unit 201 is further configured to compare the data field of the target information with the data field of the data description information to obtain a comparison result; under the condition that the comparison result shows that the data field of the target information is the same as the data field of the data description information, judging whether the target information is a subset of the data description information; in a case where the target information is a subset of the data description information, the intention data description corresponding to the target information is determined in the data description information.
In other embodiments, the generating unit 202 is further configured to determine whether each required content in the target information has a function that cannot be generated; under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description; obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function; and generating an initial file to be executed based on the judgment statement.
In other embodiments, the checking unit 203 is further configured to analyze the initial file to be executed, and obtain a data format of the initial file; judging whether the data format conforms to the data format described by the intention data; under the condition that the data format does not conform to the data format described by the intention data, carrying out format conversion on fields in the initial file to obtain a first target file; judging whether the first target file has preset check information or not, and obtaining a judgment result; and determining the target file after the feedback is checked according to the judgment result.
In other embodiments, the preset check information includes sensitive information and filtering information; the checking unit 203 is further configured to determine whether the first target file has the sensitive information; under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file; and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
In another embodiment, the checking unit 203 is further configured to, when the determination result indicates that the second target file meets the filtering information, take the second target file as the target file; and under the condition that the judgment result shows that the second target file does not meet the filtering information, filtering the second target file to determine the target file.
In other embodiments, the executing unit 204 is further configured to obtain a first data authorization of the target file by the buyer and a second data authorization of the target file by the buyer; determining the data grant based on the first data grant and the second data grant.
The above description of the apparatus embodiments, similar to the above description of the method embodiments, has similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the apparatus according to the invention, reference is made to the description of the embodiments of the method according to the invention for understanding.
It should be noted that, in the embodiment of the present invention, if the data processing method is implemented in the form of a software functional module and sold or used as a standalone product, the data processing method may also be stored in a computer readable storage medium. With this understanding, technical embodiments of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a control server (which may be a personal computer, a server, or a network server) to perform all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a magnetic disk, or an optical disk. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
Correspondingly, an embodiment of the present invention provides a data processing apparatus, including a memory and a processor, where the memory stores a computer program operable on the processor, and the processor executes the computer program to implement the steps in the control method provided in the above embodiment.
Correspondingly, the embodiment of the invention provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the control method provided by the above-mentioned embodiment.
Here, it should be noted that: the above description of the storage medium and device embodiments is similar to the description of the method embodiments above, with similar advantageous effects as the method embodiments. For technical details not disclosed in the embodiments of the storage medium and the apparatus according to the invention, reference is made to the description of the embodiments of the method according to the invention.
It should be noted that fig. 3 is a schematic diagram of a hardware entity structure of a data processing apparatus in an embodiment of the present invention, and as shown in fig. 3, the hardware entity of the data processing apparatus 300 includes: a processor 301 and a memory 303, optionally the data processing device 300 may further comprise a communication interface 302.
It will be appreciated that the memory 303 can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 303 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The method disclosed in the above embodiments of the present invention may be applied to the processor 301, or implemented by the processor 301. The processor 301 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 301. The Processor 301 may be a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Processor 301 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed by the embodiment of the invention can be directly implemented by a hardware decoding processor, or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 303, and the processor 301 reads the information in the memory 303 and performs the steps of the aforementioned methods in conjunction with its hardware.
In an exemplary embodiment, the Device may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, Programmable Logic Devices (PLDs), Complex Programmable Logic Devices (CPLDs), Field-Programmable Gate arrays (FPGAs), general purpose processors, controllers, Micro Controllers (MCUs), microprocessors (microprocessors), or other electronic components for performing the foregoing methods.
In the embodiments provided in the present invention, it should be understood that the disclosed method and apparatus can be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another observation, or some features may be omitted, or not performed. In addition, the communication connections between the components shown or discussed may be through interfaces, indirect couplings or communication connections of devices or units, and may be electrical, mechanical or other.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
Alternatively, the integrated unit according to the embodiment of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. With this understanding, technical embodiments of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a device (which may be a personal computer, a server, or a network device) to perform all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.
The data processing method, apparatus, device and storage medium described in the embodiments of the present invention are only examples of the embodiments of the present invention, but are not limited thereto, and the data processing method, apparatus, device and storage medium are all within the protection scope of the present invention.
It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The methods disclosed in the several method embodiments provided by the present invention can be combined arbitrarily without conflict to obtain new method embodiments.
Features disclosed in several of the product embodiments provided by the invention may be combined in any combination to yield new product embodiments without conflict.
The features disclosed in the several method or apparatus embodiments provided by the present invention may be combined arbitrarily, without conflict, to arrive at new method embodiments or apparatus embodiments.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present invention, and all such changes or substitutions are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A data processing method is characterized in that the method is applied to a credible artificial intelligence AI system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the method comprises the following steps:
acquiring target information of a buyer and data description information of a seller, and determining intention data description according to the target information and the data description information;
generating an initial file to be executed according to the intention data description and the target information;
checking the initial file to be executed to obtain a target file after checking feedback;
obtaining data authorization of the buyer and the seller to the target file, and executing the target file based on the data authorization.
2. The method of claim 1, wherein determining intent data descriptions based on the goal information and the data description information comprises:
comparing the data field of the target information with the data field of the data description information to obtain a comparison result;
under the condition that the comparison result shows that the data field of the target information is the same as the data field of the data description information, judging whether the target information is a subset of the data description information;
in a case where the target information is a subset of the data description information, the intention data description corresponding to the target information is determined in the data description information.
3. The method according to claim 2, wherein the generating an initial file to be executed according to the intent data description and the target information comprises:
judging whether each piece of required content in the target information exists and a check function cannot be generated;
under the condition that each piece of demand content in the target information does not have the check function which cannot be generated, generating a judgment statement based on the fact that the check function is matched with the intention data description;
obtaining supplementary information of the buyer in the case that each required content in the target information cannot generate a check function; updating target information according to the supplementary information to obtain updated target information; judging whether each piece of demand content in the updated target information cannot generate a check function or not until each piece of demand content in the updated target information cannot generate the check function;
and generating an initial file to be executed based on the judgment statement.
4. The method according to claim 1, wherein the checking the initial file to be executed to obtain a target file after checking feedback comprises:
analyzing the initial file to be executed to obtain the data format of the initial file;
judging whether the data format conforms to the data format described by the intention data;
under the condition that the data format does not conform to the data format described by the intention data, carrying out format conversion on fields in the initial file to obtain a first target file;
judging whether the first target file has preset check information or not, and obtaining a judgment result;
and determining the target file after the feedback is checked according to the judgment result.
5. The method according to claim 4, wherein the preset inspection information includes sensitive information and filtering information; the judging whether the first target file has preset checking information or not to obtain a judgment result includes:
judging whether the first target file has the sensitive information or not;
under the condition that the first target file has the sensitive information, prompting the seller to review and process the sensitive information in the first target file and determining a second target file;
and judging whether the second target file meets the filtering information or not, and obtaining a judgment result that the second target file meets the filtering information or the second target file does not meet the filtering information.
6. The method according to claim 5, wherein the determining the target file after checking the feedback according to the determination result comprises:
taking the second target file as the target file under the condition that the judgment result shows that the second target file meets the filtering information;
and under the condition that the judgment result shows that the second target file does not meet the filtering information, filtering the second target file to determine the target file.
7. The method of claim 6, wherein obtaining data authorization of the target file by the buyer and the seller comprises:
obtaining a first data authorization of the buyer to the target file and a second data authorization of the buyer to the target file;
determining the data grant based on the first data grant and the second data grant.
8. A data processing device is characterized by being applied to a credible Artificial Intelligence (AI) system; the trusted AI system comprises at least a buyer AI agent and a seller AI agent; the device comprises: a determination unit, a generation unit, an examination unit and an execution unit, wherein,
the determining unit is used for obtaining target information of a buyer and data description information of a seller and determining intention data description according to the target information and the data description information;
the generating unit is used for generating an initial file to be executed according to the intention data description and the target information;
the checking unit is used for checking the initial file to be executed and obtaining a target file after checking feedback;
the execution unit is used for obtaining the data authorization of the buyer and the seller to the target file and executing the target file based on the data authorization.
9. A storage medium, characterized in that the storage medium has stored thereon a computer program; the computer program when executed by a processor implements the steps of the method of any one of claims 1 to 7.
10. A data processing apparatus, characterized in that the data processing apparatus comprises: a processor and a memory for storing a computer program operable on the processor, wherein the processor is operable to perform the steps of the method of any of claims 1 to 7 when the computer program is executed.
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Application publication date: 20211221 |