CN116823293A - Electronic contract tracing and checking method and system - Google Patents
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Abstract
The application discloses an electronic contract tracing and checking method and system, which are applied to the technical field of data processing, wherein the method comprises the following steps: and analyzing and marking the topic type and the risk content by acquiring the electronic contract text information, and determining the risk factors. And obtaining a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a block chain, and constructing a contract tracing code. And analyzing and extracting the contract tracing code to obtain a preset identification data chain. Decoding a preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords. And comparing the contract party user information, contract risk keywords with the received electronic contract content to determine a verification result. The technical problems that in the prior art, the verification mode of the electronic contract is comparatively backward, stored electronic contract information is easy to tamper and the safety is low are solved.
Description
Technical Field
The application relates to the field of data processing, in particular to an electronic contract tracing and checking method and system.
Background
Electronic contract is a contract that parties of the contract establish through the form of an electronic information network, such that parties of the contract make clear an electronic agreement on rights and obligations. In the prior art, the electronic contract is traced and verified by storing the electronic contract pictures, and the electronic contract pictures are verified by the picture information stored by multiple parties, however, the pictures are very likely to be maliciously tampered in the picture storing process, contract disputes are easily caused, and the problem of lower tracing and verifying safety exists.
Therefore, in the prior art, the verification method of the electronic contract is relatively backward, and the stored electronic contract information is easy to tamper and has low security.
Disclosure of Invention
The application solves the technical problems that the verification mode of the electronic contract is comparatively backward, the stored electronic contract information is easy to tamper and the safety is lower in the prior art by providing the electronic contract tracing verification method and the electronic contract tracing verification system. The security verification of the electronic contract is realized, and the security of the electronic contract information storage is ensured.
The application provides an electronic contract tracing and checking method, which comprises the steps of obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis marking on topic types and risk contents on the semantic information; carrying out risk factor analysis on the text semantic information based on the topic type and the risk content to determine risk factors; acquiring a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a block chain, and constructing a contract tracing code; analyzing and extracting the contract tracing code to obtain a preset identification data chain; decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords; and comparing the contractual user information, the contractual risk key words and the received electronic contract content to determine a verification result.
The application also provides an electronic contract tracing and checking system, which comprises: the content analysis labeling module is used for obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis labeling on topic types and risk contents on the semantic information; the risk factor acquisition module is used for carrying out risk factor analysis on the text semantic information based on the topic type and the risk content to determine risk factors; the contract tracing code construction module is used for obtaining a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a blockchain, and constructing a contract tracing code; the identification data chain acquisition module is used for analyzing and extracting the contract tracing code to acquire a preset identification data chain; the decoding analysis module is used for decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords; and the comparison and verification module is used for comparing the contractual user information, the contract risk keywords with the received electronic contract content to determine a verification result.
The application also provides an electronic device, comprising:
a memory for storing executable instructions;
and the processor is used for realizing the electronic contract tracing and checking method provided by the embodiment of the application when executing the executable instructions stored in the memory.
The embodiment of the application provides a computer readable storage medium which stores a computer program, and when the program is executed by a processor, the electronic contract tracing and checking method provided by the embodiment of the application is realized.
According to the electronic contract tracing and checking method and system provided by the application, the risk factors are extracted by carrying out semantic analysis on the electronic contract text, and the contract tracing codes are carried out. And decoding the contract traceability code to obtain check content, and comparing the check content with the electronic contract content. The security verification of the electronic contract is realized, and the security of the electronic contract information storage is ensured.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly described below. It is apparent that the figures in the following description relate only to some embodiments of the present disclosure and are not limiting of the present disclosure.
Fig. 1 is a schematic flow chart of an electronic contract tracing and checking method provided by an embodiment of the application;
fig. 2 is a schematic flow chart of obtaining early warning information by the electronic contract tracing verification method according to the embodiment of the application;
fig. 3 is a schematic flow chart of obtaining circulation verification information by the electronic contract tracing verification method according to the embodiment of the application;
fig. 4 is a schematic structural diagram of a system of an electronic contract tracing verification method according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a system electronic device of an electronic contract tracing verification method according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a content analysis labeling module 11, a risk factor acquisition module 12, a contract traceability code construction module 13, an identification data chain acquisition module 14, a decoding analysis module 15 and a comparison verification module 16.
Detailed Description
Example 1
The present application will be further described in detail with reference to the accompanying drawings, for the purpose of making the objects, technical solutions and advantages of the present application more apparent, and the described embodiments should not be construed as limiting the present application, and all other embodiments obtained by those skilled in the art without making any inventive effort are within the scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with one another without conflict.
In the following description, the terms "first", "second", "third" and the like are merely used to distinguish similar objects and do not represent a particular ordering of the objects, it being understood that the "first", "second", "third" may be interchanged with a particular order or sequence, as permitted, to enable embodiments of the application described herein to be practiced otherwise than as illustrated or described herein.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application only.
While the present application makes various references to certain modules in a system according to embodiments of the present application, any number of different modules may be used and run on a user terminal and/or server, the modules are merely illustrative, and different aspects of the system and method may use different modules.
A flowchart is used in the present application to describe the operations performed by a system according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in order precisely. Rather, the various steps may be processed in reverse order or simultaneously, as desired. Also, other operations may be added to or removed from these processes.
As shown in fig. 1, an embodiment of the present application provides an electronic contract traceback verification method, where the method includes:
s10: obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis and labeling on topic types and risk contents of the semantic information;
s20: carrying out risk factor analysis on the text semantic information based on the topic type and the risk content to determine risk factors;
specifically, an electronic contract is a contract that parties of the contract establish through the form of an electronic information network, so that parties of the contract make clear an electronic agreement on rights and obligations. Acquiring text information in the electronic contract, carrying out semantic analysis on the text information in the electronic contract to obtain text semantic information, and analyzing and labeling the topic type and the risk content in the acquired semantic information. The subject type is a subject of electronic contract signing, such as a loan contract, a lease contract and the like, wherein the risk content comprises specific risk content, such as a loan contract, for example, wherein the risk content is clause content of the loan contract, which has risks except general notes. When semantic analysis is performed, semantic information can be acquired in a semantic analysis mode commonly used in the prior art, and risk factor analysis is performed on text semantic information based on the acquired semantic information by using topic types and risk contents to determine risk factors. When the risk factors are determined, acquiring a risk factor database contained in the theme type and the risk content through big data, inputting the acquired text semantic information into the database to inquire the corresponding theme type and the risk factors contained in the risk content, and determining the risk factors in the theme type and the risk content.
The method S10 provided by the embodiment of the application further comprises the following steps:
s11: constructing a risk annotation training library;
s12: obtaining a risk type dataset;
s13: respectively performing risk type data traversal extraction from the risk annotation training library by using the risk type data set to obtain a risk type training data set;
s14: and training a neural network model by using the risk type training data set, training and converging the model by using the labeling information of the subject type and the related content to obtain the identification labeling model, and constructing an identification labeling model library of each risk type.
Specifically, a risk annotation training library is constructed, wherein the risk annotation training library comprises semantic information of each topic contract and corresponding risk contents. The risk labeling training library acquires specific risk contents of each topic type contract by means of big data and constructs the risk labeling training library. Acquiring a risk type data set, wherein the risk type data set comprises contract risk types corresponding to each topic type, and the risk types existing in loan contracts comprise credit risks, specific risk contents comprise debtors, creditors and corresponding clauses, and the risk types corresponding to different topic contracts are different. Further, performing risk type data traversal extraction from the risk annotation training database by using the risk type data set respectively, namely extracting contract content of corresponding risk types and risk related content of corresponding annotations in the risk annotation training database according to each risk type in the risk type data set to obtain the risk type training data set. And finally, training a neural network model by using the risk type training data set, taking the topic type and semantic information as training data, and taking the labeling information of the risk content as identification data to train models of different risk types. And obtaining the identification marking models when the output result meets a certain accuracy, and obtaining the identification marking models of all risk types to form an identification marking model library.
The method S10 provided by the embodiment of the application further comprises the following steps:
s15: determining a topic type according to the semantic information, analyzing a risk type based on the topic type, and determining a contract risk type;
s16: matching from the identification marking model library of each risk type by utilizing the contract risk type to obtain a matching type identification marking model;
s17: inputting the semantic information into a matching type identification labeling model, and carrying out the identification labeling of the dangerous content.
Specifically, the topic type is determined according to the semantic information, then risk type analysis is performed based on the topic type, and a contract risk type specific to the topic type is determined. Further, matching is carried out from the identification marking model library of each risk type by using the contract risk type, and a matching type identification marking model is obtained. And finally, inputting the semantic information into a matching type identification labeling model to finish labeling the contents involved in the contract.
As shown in fig. 2, the method S20 provided by the embodiment of the present application further includes:
s21: carrying out correlation tracing on the risk factors to construct risk factor information;
s22: inputting the risk factor information into a risk assessment model for risk assessment to obtain risk assessment information;
s23: judging whether the risk assessment information meets the early warning requirement, and sending early warning information when the risk assessment information meets the early warning requirement.
Specifically, the risk factors are subjected to correlation tracing, and risk factor information is constructed, wherein all the correlation information of the risk factors is obtained when the risk factor correlation tracing is performed. Taking a borrowing contract as an example, the marked risk-related content is a borrowing term, and the corresponding acquired risk factor is borrower information, so that when the information correlation of the borrower is traced, the information such as work, income, property and the like associated with the borrower needs to be acquired. And then, inputting the acquired risk factor information into a risk assessment model for risk assessment to obtain risk assessment information. Judging whether the risk assessment information meets the early warning requirement, namely meeting certain abnormal early warning requirements, and if the borrower does not have the conditions of fixed income and the like in the borrowing contract, indicating that the borrower has abnormal conditions, and when the risk assessment information meets the conditions, sending the early warning information, wherein specific early warning conditions can be set according to actual electronic contract contents, so that automatic early warning reminding of the contract contents is realized.
The method S22 provided by the embodiment of the application further comprises the following steps:
s221: acquiring risk target information;
s222: performing risk related information tracing and acquiring according to the risk target information;
s223: constructing an evaluation chain according to the time sequence of acquiring the related risk information, wherein the evaluation chain comprises a plurality of sub-evaluation sections, and each sub-evaluation section corresponds to one time sequence of the risk related information;
the method S22 provided by the embodiment of the application further comprises the following steps:
s224: performing risk assessment on the risk related information through each sub-assessment section to obtain first assessment information, performing risk correlation analysis on the risk related information of the first sub-assessment section and the risk related information of the second sub-assessment section, and determining a first risk information relationship;
s225: inputting the first risk information relation and the first evaluation information into a second sub-evaluation section, and performing fusion calculation with the second evaluation information to obtain second section risk information;
s226: with such a push, the risk assessment of all sub-assessment sections is completed, and the section risk information of the assessment chain end point is taken as the risk assessment information.
Specifically, risk target information is obtained, wherein the risk target information is a target corresponding to the risk factor, and risk related information is obtained in a tracing mode according to the risk target information. An evaluation chain is constructed according to the time sequence of acquiring the related risk information, and a plurality of sub-evaluation sections are included in the evaluation chain. Each sub-evaluation segment corresponds to risk related information of the time series. And carrying out risk assessment on the risk related information through each sub-assessment section to obtain first assessment information, carrying out risk correlation analysis on the risk related information of the first sub-assessment section and the risk related information of the second sub-assessment section, and determining a first risk information relation. I.e. whether each evaluation segment in the time sequence has a contact or not, and acquiring a first risk information relationship. Further, the first risk information relation and the first evaluation information are input into a second sub-evaluation section, and fusion calculation is carried out on the first risk information relation and the first evaluation information and the second evaluation information, so that the risk information of the second section is obtained. And carrying out fusion calculation on the risk information according to the relation among the risk information according to the time sequence. And finally acquiring the risk information of the sections of the evaluation chain end point as the risk evaluation information until the risk information of the multiple evaluation sections is evaluated.
S30: acquiring a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a block chain, and constructing a contract tracing code;
s40: analyzing and extracting the contract tracing code to obtain a preset identification data chain;
s50: decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords;
s60: and comparing the contractual user information, the contractual risk key words and the received electronic contract content to determine a verification result.
Specifically, a preset traceability identification code is obtained, wherein the preset traceability identification code is a preset traceability identification code which is preset and ordered according to a certain risk category. And generating each risk identification information based on the preset traceability identification code and the risk factor, modifying the preset traceability identification code according to the risk identification information, and storing by using the blockchain to construct the contract traceability code. Analyzing and extracting the contract traceability code to obtain a preset identification data chain, and further decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information, contract risk keywords, namely risk content information and specific evaluation information. And finally, comparing the received electronic contract contents with the contract party user information and the contract risk key words to determine a verification result, and judging whether the electronic contract contents are consistent with the contents recorded in the contract party user information and the contract risk key words, so that the safety verification of the electronic contract is finished, and the safety of the electronic contract information storage is ensured.
The method S30 provided by the embodiment of the application further comprises the following steps:
s31: ordering the risk assessment information according to the risk category ordering requirement of a preset traceability identification code, and filling the non-existing risk categories according to preset characters;
s32: according to a verification code generation rule of a preset traceability identification code, extracting verification code elements of corresponding categories from each risk category to generate a risk category verification code;
s33: based on the risk identification information sequencing, generating a risk category verification code of a second risk category by using a risk category verification code of a first risk category and a verification code element of the second risk category, generating a risk category verification code of a third risk category by using a risk category verification code of the second risk category and a verification code element of the third risk category, and so on, generating a risk category verification code of an nth risk category by using a risk category verification code of an nth-1 risk category and a verification code element of the nth risk category;
s34: and each risk category corresponds to a storage interval, the blockchain storage is completed, a unique sequence is generated according to time information, place information and an authentication company generated by the blockchain, and the contract traceability code is generated based on the sequence.
Specifically, the risk assessment information is ranked according to the risk category ranking requirement of the preset traceability identification code, namely, the risk assessment information is ranked according to a fixed risk category ranking mode. And filling the risk categories which are not existing in the risk categories, namely the risk categories which are not evaluated, according to preset characters. According to verification code generation rules of preset traceability identification codes, the verification code generation rules comprise filling non-existing risk categories according to preset characters, filling different characters of the existing risk categories according to different risk assessment information, and the risk assessment information is exemplified by filling 0 when no risk exists, filling 1 when smaller risk exists, and different verification code generation rules can be set according to specific risk assessment information. And extracting verification code elements of the corresponding categories, namely corresponding risk assessment information, from each risk category to generate a risk category verification code. And then, based on the risk identification information sorting, generating a risk category verification code of a second risk category by using a risk category verification code of the first risk category and a verification code element of the second risk category, generating a risk category verification code of a third risk category by using a risk category verification code of the second risk category and a verification code element of the third risk category, and so on, generating a risk category verification code of an nth risk category by using a risk category verification code of an nth-1 risk category and a verification code element of the nth risk category, wherein each risk category verification code corresponds to one kind of risk content until verification code acquisition of all risk content is completed. Each risk category corresponds to a storage interval, block chain storage is completed, a unique sequence is generated according to time information, place information and an authentication company generated by the block chain, the contract tracing code is generated based on the sequence, specific evaluation information of each risk content in the contract can be clearly obtained through tracing operation of the contract tracing code, and follow-up evaluation of the contract is facilitated.
As shown in fig. 3, the method S60 provided by the embodiment of the present application further includes:
s61: acquiring a contract transmission flow node;
s62: analyzing node risk values according to the contract transmission flow nodes to determine risk values;
s63: when the risk value reaches a preset condition, obtaining an associated superior node of the node;
s64: and comparing the contract information of the related superior node with the accepted electronic contract content to obtain circulation verification information.
Specifically, the contract transmission flow node is obtained, and as the electronic contract needs to be transmitted to all parties in the network environment, the content in the electronic contract is prevented from being tampered in the transmission process. And analyzing the node risk value of the contract transmission flow node to determine the risk value. The risk value may be obtained according to potential risk factors during data transmission, including but not limited to transmission by strange devices, repeated transmission, and the like. When the risk value reaches a preset condition, the associated superior node of the node is obtained, namely the superior node corresponding to the transmission source is obtained. And comparing the contract information of the related superior node with the received electronic contract content to obtain circulation verification information, so that the security of the electronic contract in the circulation process is ensured, and the electronic contract is prevented from being tampered by others in the circulation process.
According to the technical scheme provided by the embodiment of the application, the electronic contract text information is obtained, the topic type and the risk content are analyzed and marked, and the risk factors are determined. And obtaining a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a block chain, and constructing a contract tracing code. And analyzing and extracting the contract tracing code to obtain a preset identification data chain. Decoding a preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords. And comparing the contract party user information, contract risk keywords with the received electronic contract content to determine a verification result. The technical problems that in the prior art, the verification mode of the electronic contract is comparatively backward, stored electronic contract information is easy to tamper and the safety is low are solved. The security verification of the electronic contract is realized, and the security of the electronic contract information storage is ensured.
Example 2
Based on the same inventive concept as the electronic contract tracing verification method in the foregoing embodiment, the present application further provides a system of the electronic contract tracing verification method, which may be implemented by hardware and/or software, and may be generally integrated in an electronic device, for executing the method provided by any embodiment of the present application. As shown in fig. 4, the system includes:
the content analysis labeling module 11 is used for obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis labeling on topic types and risk contents on the semantic information;
a risk factor obtaining module 12, configured to perform risk factor analysis on text semantic information based on the topic type and the risk content, and determine a risk factor;
the contract tracing code construction module 13 is configured to obtain a preset tracing identifier, generate each risk identification information based on the preset tracing identifier and the risk factor, store each risk identification information by using a blockchain, and construct a contract tracing code;
the identification data chain acquisition module 14 is used for analyzing and extracting the contract tracing code to acquire a preset identification data chain;
the decoding analysis module 15 is configured to decode the preset identification data chain to obtain a risk identification information set, where the risk identification information set includes contractual user information and a contractual risk keyword;
and the comparison and verification module 16 is used for comparing the contractual user information, the contractual risk keywords and the received electronic contract content to determine a verification result.
Further, the risk factor acquisition module 12 is further configured to:
carrying out correlation tracing on the risk factors to construct risk factor information;
inputting the risk factor information into a risk assessment model for risk assessment to obtain risk assessment information;
judging whether the risk assessment information meets the early warning requirement, and sending early warning information when the risk assessment information meets the early warning requirement.
Further, the risk factor acquisition module 12 is further configured to:
acquiring risk target information;
performing risk related information tracing and acquiring according to the risk target information;
constructing an evaluation chain according to the time sequence of acquiring the related risk information, wherein the evaluation chain comprises a plurality of sub-evaluation sections, and each sub-evaluation section corresponds to one time sequence of the risk related information;
performing risk assessment on the risk related information through each sub-assessment section to obtain first assessment information, performing risk correlation analysis on the risk related information of the first sub-assessment section and the risk related information of the second sub-assessment section, and determining a first risk information relationship;
inputting the first risk information relation and the first evaluation information into a second sub-evaluation section, and performing fusion calculation with the second evaluation information to obtain second section risk information;
with such a push, the risk assessment of all sub-assessment sections is completed, and the section risk information of the assessment chain end point is taken as the risk assessment information.
Further, the contract traceability code construction module 13 is further configured to:
ordering the risk assessment information according to the risk category ordering requirement of a preset traceability identification code, and filling the non-existing risk categories according to preset characters;
according to a verification code generation rule of a preset traceability identification code, extracting verification code elements of corresponding categories from each risk category to generate a risk category verification code;
based on the risk identification information sequencing, generating a risk category verification code of a second risk category by using a risk category verification code of a first risk category and a verification code element of the second risk category, generating a risk category verification code of a third risk category by using a risk category verification code of the second risk category and a verification code element of the third risk category, and so on, generating a risk category verification code of an nth risk category by using a risk category verification code of an nth-1 risk category and a verification code element of the nth risk category;
and each risk category corresponds to a storage interval, the blockchain storage is completed, a unique sequence is generated according to time information, place information and an authentication company generated by the blockchain, and the contract traceability code is generated based on the sequence.
Further, the content analysis labeling module 11 is further configured to:
constructing a risk annotation training library;
obtaining a risk type dataset;
respectively performing risk type data traversal extraction from the risk annotation training library by using the risk type data set to obtain a risk type training data set;
and training a neural network model by using the risk type training data set, training and converging the model by using the labeling information of the subject type and the related content to obtain the identification labeling model, and constructing an identification labeling model library of each risk type.
Further, the content analysis labeling module 11 is further configured to:
determining a topic type according to the semantic information, analyzing a risk type based on the topic type, and determining a contract risk type;
matching from the identification marking model library of each risk type by utilizing the contract risk type to obtain a matching type identification marking model;
inputting the semantic information into a matching type identification labeling model, and carrying out the identification labeling of the dangerous content.
Further, the comparison and verification module 16 is further configured to:
acquiring a contract transmission flow node;
analyzing node risk values according to the contract transmission flow nodes to determine risk values;
when the risk value reaches a preset condition, obtaining an associated superior node of the node;
and comparing the contract information of the related superior node with the accepted electronic contract content to obtain circulation verification information.
The electronic contract tracing and checking system provided by the embodiment of the application can execute the electronic contract tracing and checking system method provided by any embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
The included units and modules are only divided according to the functional logic, but are not limited to the above-mentioned division, so long as the corresponding functions can be realized; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present application.
Example 3
Fig. 5 is a schematic structural diagram of an electronic device provided in a third embodiment of the present application, and shows a block diagram of an exemplary electronic device suitable for implementing an embodiment of the present application. The electronic device shown in fig. 5 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present application. As shown in fig. 5, the electronic device includes a processor 31, a memory 32, an input device 33, and an output device 34; the number of processors 31 in the electronic device may be one or more, in fig. 5, one processor 31 is taken as an example, and the processors 31, the memory 32, the input device 33 and the output device 34 in the electronic device may be connected by a bus or other means, in fig. 5, by bus connection is taken as an example.
The memory 32 is used as a computer readable storage medium for storing software programs, computer executable programs and modules, such as program instructions/modules corresponding to an electronic contract traceback verification method in an embodiment of the present application. The processor 31 executes various functional applications of the computer device and data processing by running software programs, instructions and modules stored in the memory 32, i.e., implements an electronic contract traceback verification method as described above.
Note that the above is only a preferred embodiment of the present application and the technical principle applied. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, while the application has been described in connection with the above embodiments, the application is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the application, which is set forth in the following claims.
Claims (10)
1. An electronic contract traceability verification method is characterized by comprising the following steps:
obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis labeling of topic types and risk contents on the semantic information;
carrying out risk factor analysis on the text semantic information based on the topic type and the risk content to determine risk factors;
acquiring a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a block chain, and constructing a contract tracing code;
analyzing and extracting the contract tracing code to obtain a preset identification data chain;
decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords;
and comparing the contractual user information, the contractual risk key words and the received electronic contract content to determine a verification result.
2. The method of claim 1, wherein after the determining the risk factor, the method further comprises:
carrying out correlation tracing on the risk factors to construct risk factor information;
inputting the risk factor information into a risk assessment model for risk assessment to obtain risk assessment information;
judging whether the risk assessment information meets the early warning requirement, and sending early warning information when the risk assessment information meets the early warning requirement.
3. The method of claim 2, wherein the inputting the risk factor information into the risk assessment model for risk assessment, obtaining risk assessment information, comprises:
acquiring risk target information;
performing risk related information tracing and acquiring according to the risk target information;
constructing an evaluation chain according to the time sequence of acquiring the related risk information, wherein the evaluation chain comprises a plurality of sub-evaluation sections, and each sub-evaluation section corresponds to one time sequence of the risk related information;
performing risk assessment on the risk related information through each sub-assessment section to obtain first assessment information, performing risk correlation analysis on the risk related information of the first sub-assessment section and the risk related information of the second sub-assessment section, and determining a first risk information relationship;
inputting the first risk information relation and the first evaluation information into a second sub-evaluation section, and performing fusion calculation with the second evaluation information to obtain second section risk information;
with such a push, the risk assessment of all sub-assessment sections is completed, and the section risk information of the assessment chain end point is taken as the risk assessment information.
4. The method of claim 1, wherein storing each risk identification information using a blockchain to construct a contract traceback code comprises:
ordering the risk assessment information according to the risk category ordering requirement of a preset traceability identification code, and filling the non-existing risk categories according to preset characters;
according to a verification code generation rule of a preset traceability identification code, extracting verification code elements of corresponding categories from each risk category to generate a risk category verification code;
based on the risk identification information sequencing, generating a risk category verification code of a second risk category by using a risk category verification code of a first risk category and a verification code element of the second risk category, generating a risk category verification code of a third risk category by using a risk category verification code of the second risk category and a verification code element of the third risk category, and so on, generating a risk category verification code of an nth risk category by using a risk category verification code of an nth-1 risk category and a verification code element of the nth risk category;
and each risk category corresponds to a storage interval, the blockchain storage is completed, a unique sequence is generated according to time information, place information and an authentication company generated by the blockchain, and the contract traceability code is generated based on the sequence.
5. The method of claim 1, wherein before the semantic information is subject type and risk content is analyzed and labeled, the method comprises:
constructing a risk annotation training library;
obtaining a risk type dataset;
respectively performing risk type data traversal extraction from the risk annotation training library by using the risk type data set to obtain a risk type training data set;
and training a neural network model by using the risk type training data set, training and converging the model by using the labeling information of the subject type and the related content to obtain the identification labeling model, and constructing an identification labeling model library of each risk type.
6. The method according to claim 5, wherein the analyzing and labeling the topic type and the risk content of the semantic information comprises:
determining a topic type according to the semantic information, analyzing a risk type based on the topic type, and determining a contract risk type;
matching from the identification marking model library of each risk type by utilizing the contract risk type to obtain a matching type identification marking model;
inputting the semantic information into a matching type identification labeling model, and carrying out the identification labeling of the dangerous content.
7. The method of claim 1, wherein the method further comprises:
acquiring a contract transmission flow node;
analyzing node risk values according to the contract transmission flow nodes to determine risk values;
when the risk value reaches a preset condition, obtaining an associated superior node of the node;
and comparing the contract information of the related superior node with the accepted electronic contract content to obtain circulation verification information.
8. An electronic contract traceback verification system, the system comprising:
the content analysis labeling module is used for obtaining electronic contract text information, carrying out semantic analysis on the text information to obtain text semantic information, and carrying out analysis labeling on topic types and risk contents on the semantic information;
the risk factor acquisition module is used for carrying out risk factor analysis on the text semantic information based on the topic type and the risk content to determine risk factors;
the contract tracing code construction module is used for obtaining a preset tracing identification code, generating each risk identification information based on the preset tracing identification code and the risk factor, storing each risk identification information by using a blockchain, and constructing a contract tracing code;
the identification data chain acquisition module is used for analyzing and extracting the contract tracing code to acquire a preset identification data chain;
the decoding analysis module is used for decoding the preset identification data chain to obtain a risk identification information group, wherein the risk identification information group comprises contractual user information and contract risk keywords;
and the comparison and verification module is used for comparing the contractual user information, the contract risk keywords with the received electronic contract content to determine a verification result.
9. An electronic device, the electronic device comprising:
a memory for storing executable instructions;
a processor for implementing an electronic contract traceback verification method as claimed in any one of claims 1 to 7 when executing executable instructions stored in said memory.
10. A computer readable medium on which a computer program is stored, characterized in that the program, when being executed by a processor, implements an electronic contract traceback verification method as claimed in any one of claims 1-7.
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