Method and system for generating code based on interface document, computer equipment and medium

Abstract

The invention relates to a method and a system for generating a docking code based on an interface document, computer equipment and a storage medium. The method comprises the following steps: acquiring the interface document of a capital business system needing to be docked by an internet financial system; extracting a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule; generating a capital JSON structural body according to each first keyword and the corresponding first parameter; on the basis of a first hash value processing result of the capital JSON structural body and a second hash value processing result of a preset standard JSON structural body, converting each first parameter and generating a standard parameter structural body; and mapping each parameter in the capital JSON structural body to the standard parameter structural body one by one, and generating a docking code required for accessing the Internet financial system to the capital business system. Through the steps of the method, human errors can be avoided, and the docking efficiency and adaptability between Internet financial systems are improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of Internet financial technology, and in particular to a method, system, computer device and storage medium for generating a docking code based on an interface document. Background Art

[0002] In the field of Internet finance, when the Internet finance system is connected with the interface of the investor's business system, due to the different interface rules between the Internet finance system and the investor's business system, technical personnel are required to carefully read the interface documents of the investor's business system every time they are connected, and manually write code to complete the system connection based on the interface rules in the documents and the existing parameters of the Internet finance system.

[0003] However, this traditional manual coding method requires a lot of time and energy from technical personnel, and the codes obtained by this method are not only greatly affected by human factors, but also prone to errors and uneven in quality, making it difficult to ensure the reliability and stability of the system and code operation. Secondly, since the codes obtained by different technicians in the manual coding method are different in code style and structure, the difficulty and cost of system maintenance and upgrades increase. In addition, with the increase in the number of capital business systems, or in the case of frequent docking of multiple capital business system interfaces, the manual coding method will not only lead to an increase in labor costs, but also make it difficult for technical personnel to adapt due to the frequent changes in the capital business system interface rules, which seriously affects the progress and delivery time of the project. Summary of the invention

[0004] In response to the above-mentioned deficiencies or shortcomings, the present application provides a method, system, computer device and storage medium for generating docking code based on interface documents, which can avoid human errors and improve the docking efficiency and adaptability between Internet financial systems.

[0005] According to a first aspect, the present application provides a method for generating a docking code based on an interface document, comprising:

[0006] Obtain the interface documents of the capital business system that the Internet financial system needs to connect with;

[0007] Extracting a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule;

[0008] Generate the capital party JSON structure according to each first keyword and its corresponding first parameter;

[0009] Based on the first hash value processing result of the capital JSON structure and the second hash value processing result of the preset standard JSON structure, each first parameter is converted to generate a standard parameter structure;

[0010] Map each parameter in the investor's JSON structure to the standard parameter structure one by one, and generate the docking code required for the Internet financial system to access the investor's business system.

[0011] In some embodiments, before obtaining the interface document of the capital-side business system that the Internet financial system needs to connect to, the method further includes:

[0012] Obtain multiple standard parameters of the Internet financial system and their corresponding standard keywords;

[0013] Extract the target historical code, parse the target historical code and obtain the historical document;

[0014] Extracting multiple supplementary keywords and their corresponding supplementary parameters from the historical documents according to various standard parameters;

[0015] Generate a standard keyword library based on the extracted supplementary keywords and standard keywords;

[0016] A corresponding weight value is set for each standard keyword in the standard keyword library. Each weight value is determined based on the historical usage habits of the corresponding standard keyword, the position in the code and document, and the human error correction habits.

[0017] In some embodiments, the standard JSON structure is generated according to the standard keyword library, the first hash value processing result includes the hash value of each first keyword in the capital JSON structure, and the second hash value processing result includes the hash value of each standard keyword in the standard JSON structure; based on the hash value processing results of the capital JSON structure and the preset standard JSON structure, each first parameter is converted and a standard parameter structure is generated, including:

[0018] Compare the hash value of each first keyword in the investor's JSON structure with the hash value of the corresponding standard keyword in the standard JSON structure one by one;

[0019] According to the consistency comparison result, determine the first parameter of each hash value matching and the first parameter of each hash value not matching in the JSON structure of the capital party;

[0020] Convert the first parameter matched by each hash value into the corresponding standard parameter;

[0021] Performing similarity check and manual marking on first parameters whose hash values ​​do not match each other to convert them into corresponding standard parameters;

[0022] A standard parameter structure is generated based on the weight values ​​of the converted first parameters and their corresponding standard keywords.

[0023] In some embodiments, performing similarity check and manual marking on first parameters whose hash values ​​do not match to convert them into corresponding standard parameters includes:

[0024] Performing Hamming distance calculation on each first parameter whose hash value does not match, and / or introducing text similarity algorithm rules to perform similarity score calculation, to obtain each Hamming distance and / or each similarity score corresponding to each first parameter whose hash value does not match;

[0025] Convert each first parameter that does not match the hash value into a corresponding standard parameter according to each Hamming distance and / or each similarity score;

[0026] If there are still one or more first parameters that cannot be converted to standard parameters, they are manually marked to complete the conversion to standard parameters;

[0027] Among them, each Hamming distance represents the degree of difference between the first keyword corresponding to the first parameter that each hash value does not match and the multiple standard keywords corresponding to it in the standard JSON structure, and each similarity score reflects the degree of similarity between the first keyword corresponding to the first parameter that each hash value does not match and the various standard keywords in the standard keyword library.

[0028] In some embodiments, if the Hamming distance calculation is performed only on the first parameters whose hash values ​​do not match, and the first parameters whose hash values ​​do not match are converted into corresponding standard parameters according to the Hamming distances, the method includes:

[0029] According to the set Hamming distance threshold, determine the number of Hamming distances within the Hamming distance threshold among the Hamming distances corresponding to the first parameters that do not match the hash values;

[0030] Determine one or more first parameters and their corresponding first keywords of a class whose Hamming distance quantity is not less than a set quantity precision within a Hamming distance threshold, and determine the standard parameter with the minimum Hamming distance from each first keyword of the class;

[0031] The first parameter corresponding to each first keyword of the first category is converted into a standard parameter corresponding to the minimum Hamming distance.

[0032] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter with unmatched hash values ​​is converted into a corresponding standard parameter according to each Hamming distance and each similarity score, the method includes:

[0033] Filter one or more second-category first keywords whose number of corresponding standard parameters within the Hamming distance threshold is less than the set number precision, and the first parameters corresponding to each second-category first keyword will not be converted into the standard parameter with the smallest corresponding Hamming distance;

[0034] The text similarity algorithm rule is introduced to calculate and obtain the similarity score of each second category first keyword;

[0035] According to the set score threshold, from the similarity scores of the first keywords of the second category, determine the first keywords of the second category whose corresponding similarity scores are higher than the score threshold;

[0036] The first parameters corresponding to the second-category first keywords that are higher than the score threshold are converted into corresponding standard parameters.

[0037] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter that does not match the hash value is converted into a corresponding standard parameter only according to each similarity score, the method includes:

[0038] According to the set score threshold, from the respective similarity scores corresponding to the first parameters whose hash values ​​do not match, three categories of first keywords whose corresponding similarity scores are higher than the score threshold are determined;

[0039] The first parameters corresponding to the three types of first keywords that are higher than the score threshold are converted into standard parameters with the highest corresponding similarity scores.

[0040] According to a second aspect, the present application provides a system for generating a docking code based on an interface document, the system comprising:

[0041] The document recognition module is used to obtain the interface documents of the capital business system that the Internet financial system needs to connect with;

[0042] A keyword extraction module, used to extract a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule;

[0043] A parameter body extraction module, used to generate a capital party JSON structure body according to each first keyword and its corresponding first parameter;

[0044] A standard parameter generation module, used for converting each first parameter and generating a standard parameter structure based on the first hash value processing result of the capital party JSON structure and the second hash value processing result of the preset standard JSON structure;

[0045] The code generation module is used to map each parameter in the investor's JSON structure to the standard parameter structure one by one, and generate the docking code required for the Internet financial system to access the investor's business system.

[0046] According to a third aspect, the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for generating a docking code based on an interface document in any one of the above embodiments are implemented.

[0047] According to a fourth aspect, the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of any one of the methods for generating a docking code based on an interface document in the above-mentioned embodiments are implemented.

[0048] The above-mentioned method for generating docking code based on interface document can be applied to a docking device, which first obtains the interface document of the capital side business system, and the interface document is used to complete the docking between the Internet financial system and the capital side business system. Then, according to the preset standard rules, the first keyword and its corresponding first parameter are extracted from the interface document, and the capital side JSON structure is generated according to each first keyword and its corresponding first parameter. Then, based on the first hash value processing result of the capital side JSON structure and the second hash value processing result of the preset standard JSON structure, the docking device converts each first parameter and generates a standard parameter structure. Finally, the docking device maps each parameter in the capital side JSON structure to the standard parameter structure one by one, and generates the docking code required for the Internet financial system to access the capital side business system. Therefore, since the docking device automatically realizes the generation of the docking code, it can avoid human errors and improve the docking efficiency and adaptability between Internet financial systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of an application environment of a method for generating a docking code based on an interface document in one or more embodiments of the present application;

[0050] Figure 2 A schematic flow chart of a method for generating a docking code based on an interface document in one or more embodiments of the present application;

[0051] Figure 3 A schematic diagram of a flow chart of a method for generating a standard keyword library in one or more embodiments of the present application;

[0052] Figure 4 A schematic flow chart of a method for generating a standard parameter structure in one or more embodiments of the present application;

[0053] Figure 5 A flowchart of a method for performing similarity checking and manual marking on first parameters with mismatched hash values ​​to convert them into corresponding standard parameters in one or more embodiments of the present application;

[0054] Figure 6 A flowchart of a method for converting first parameters that do not match each hash value into corresponding standard parameters based only on the Hamming distance of the first parameters in one or more embodiments of the present application;

[0055] Figure 7 A flowchart of a method for converting first parameters that do not match each hash value into corresponding standard parameters according to each Hamming distance and each similarity score in one or more embodiments of the present application;

[0056] Figure 8 A flowchart of a method for converting first parameters that do not match each hash value into corresponding standard parameters based only on each similarity score in one or more embodiments of the present application;

[0057] Fig. 9 A schematic diagram of a system structure for generating a docking code based on an interface document in one or more embodiments of the present application;

[0058] Fig.10 A structural diagram of a computer device in one or more embodiments of the present application. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0060] The present application provides a method for generating a docking code based on an interface document, which is applied to Figure 1 In the application environment shown. Figure 1 As shown, the docking device 100 is used to implement a method of generating a docking code based on an interface document of the present application. Specifically, the docking device 100 obtains the interface document of the investor's business system 200, and the interface document is used to access the investor's business system 200; then the docking device 100 extracts the first keyword and its corresponding first parameter from the interface document according to its own preset standard rules, and generates an investor's JSON structure according to each first keyword and its corresponding first parameter. Then, based on the first hash value processing result of the investor's JSON structure and the second hash value processing result of its own preset standard JSON structure, the docking device 100 converts each first parameter and generates a standard parameter structure. Finally, the docking device 100 maps each parameter in the investor's JSON structure to the standard parameter structure one by one, generates the docking code required for the Internet financial system 300 to access the investor's business system 200, and provides feedback to the user through the code generation application 400.

[0061] According to a first aspect, the present application provides a method for generating a docking code based on an interface document, such as Figure 2 As shown, this method is applied to Figure 1 The following steps are taken as an example of the docking device:

[0062] Step S210: Obtain the interface document of the capital-side business system that the Internet financial system needs to connect to.

[0063] The interface document includes multiple first keywords of the capital party and their corresponding first parameters. The first keyword is a Chinese field and can correspond to a first parameter. For example, the first parameter corresponding to the first keyword "transaction serial number" in the interface document is "transSerialNo", and the first parameter corresponding to another first keyword "loan note number" is "loanSerialNo".

[0064] In some embodiments, before obtaining the interface document of the capital side business system that the Internet financial system needs to connect to, such as Figure 3 As shown, the above method also includes the following steps:

[0065] Step S310: Acquire multiple standard parameters of the Internet financial system and their corresponding standard keywords.

[0066] The standard keyword is a Chinese field, which can correspond to a standard parameter. For example, the standard keyword can be "apply repayment payment number", and the corresponding standard parameter is "repayApplyNo"; another standard keyword can be: "loan number", and the corresponding standard parameter is "loanNo".

[0067] Step S320: extract the target historical code, parse the target historical code and obtain the historical document.

[0068] The docking device can extract the target historical code from the Internet financial system or retrieve it from its own stored data. The target historical code is specifically related to the capital interface document and is the code generated or used by the docking device. The historical document parsed by the docking device from the target historical code is used to record supplementary keywords that do not exist in the current interface document but can reflect human error correction and modification habits, new additions or introduction habits, etc.

[0069] Step S330: extracting a plurality of supplementary keywords and their corresponding supplementary parameters from the historical document according to various standard parameters.

[0070] Among them, the supplementary keyword refers to the supplementary field for the standard keyword, and the supplementary field does not exist in this interface document. For example, suppose the supplementary keyword extracted by the docking device from the historical document is "account name", the corresponding supplementary parameter is "accountName", and the value of the supplementary parameter is Zhang San (ie "accountName": "Zhang San"). This reflects that we habitually add the information of "Zhang San" in the "Account Name" column. However, the first keyword "account name" may exist in this interface document, but "account name" does not exist, so the docking device can avoid the problem of missing description information for the first keyword by extracting the supplementary keyword.

[0071] Step S340: Generate a standard keyword library based on the extracted supplementary keywords and standard keywords.

[0072] As described above, the known docking device generates a standard keyword library based on the above two standard keywords and one supplementary keyword, which includes at least "application repayment payment number", "loan number" and "account name", and also includes other standard keywords and supplementary keywords. In addition, the standard keyword library should also include the corresponding relationship between each standard keyword and supplementary keyword and the standard parameter.

[0073] Step S350: setting a corresponding weight value for each standard keyword in the standard keyword library. Each weight value is determined based on the historical usage habits of the corresponding standard keyword, the position in the code and document, and the human error correction habits.

[0074] Specifically, the weight value of the standard keyword is determined by its historical usage habits, its position in the code and document, and human error correction habits. For example, "repayApplyNo" in the standard keyword library is the only application repayment identifier of the Internet financial system, which is relatively important, and its weight value should be set higher (can be 100%); and "loanNo" is also unique and used to identify a specific loan, which is relatively important, and its weight value should also be set higher (can be 100%); however, "accountName" is only used to identify the account holder, which is not important, and its weight value should be set lower (can be 50%).

[0075] In the above-mentioned standard keyword library generation method, due to the combination of human error correction and change habits, new addition or introduction habits and other information, the subsequently generated codes follow the previous code style and structure, reducing the difficulty and cost of maintenance and upgrading of the Internet financial system and improving the adaptability between Internet financial systems.

[0076] Step S220: extracting the first keyword and its corresponding first parameter from the interface document according to a preset standard rule.

[0077] Among them, the above-mentioned standard rules refer to the mechanism determined by the above-mentioned standard keyword library. According to the mechanism, the docking device can purposefully extract the first keyword and its corresponding first parameter in the interface document. The standard rules generally include multiple groups of mapping relationships of "first keyword"-"first parameter", "standard keyword"-"standard parameter", and the corresponding weight value of each standard keyword setting. For example, it is known that in the above-mentioned standard rules, there is a mapping relationship "apply repayment payment number"-"repayApplyNo"-"transaction serial number"-"transSerialNo", and it is known that "transSerialNo" exists in the interface document, then the docking device can extract the first keyword "transaction serial number" and its corresponding first parameter "transSerialNo" from the interface document according to the standard rules.

[0078] In addition, the mechanism also has the following functions: first, it is used to set corresponding weight values ​​for each standard keyword, and define how the standard parameters corresponding to these standard keywords are mapped to the specific business parameter values ​​in the Internet financial system. For example, "repayApplyNo" corresponding to "apply repayment payment number" can be "repayApplyNo": "SHUHE6" when mapped to the specific business parameters in the Internet financial system. If the Internet financial system also introduces multiple sets of text similarity algorithm rules, the above standard rules should also include the weight scores assigned to each set of text similarity algorithm rules. In short, the standard rules are a bridge connecting the standard keyword library and the specific business parameters in the Internet financial system. It ensures the smooth execution of the business processes of the Internet financial system through the weight values ​​set for each standard keyword and the mapping logic.

[0079] Step S230: Generate an investor JSON structure according to each first keyword and its corresponding first parameter.

[0080] Specifically, in the JSON structure of the capital party generated by the docking device, each first keyword can be represented as 1 "key", and 1 "key" corresponds to one or more objects, each of which can contain a first parameter and its corresponding value. For example, in the JSON structure of the capital party, the first keyword "transaction serial number" is represented as 1 "key", corresponding to 1 object, and the object only contains 1 first parameter "transSerialNo" and its corresponding value "XIANREPAY20240816000000481977". Another first keyword can be "status", represented as 1 "key", corresponding to 1 object, and the object contains 1 first parameter "status" and its corresponding multiple values: "100 (indicating: transaction completed)", "110 (indicating: settlement completed)" and "111 (indicating: feedback received)".

[0081] Step S240: Based on the first hash value processing result of the capital-side JSON structure and the second hash value processing result of the preset standard JSON structure, each first parameter is converted to generate a standard parameter structure.

[0082] Specifically, the docking device generally uses the same set of hash value algorithms to obtain the first hash value processing result and the second hash value processing result. Among them, the main difference between the standard parameter structure and the standard JSON structure is that the capital JSON structure is converted and generated by each first parameter extracted by the docking device, while the standard JSON structure is generated by the docking device according to each standard parameter extracted from the standard keyword library.

[0083] In some embodiments, the standard JSON structure is generated according to the standard keyword library, the first hash value processing result includes the hash value of each first keyword in the capital JSON structure, and the second hash value processing result includes the hash value of each standard keyword in the standard JSON structure; based on the hash value processing results of the capital JSON structure and the preset standard JSON structure, each first parameter is converted and a standard parameter structure is generated, such as Figure 4 As shown, the above method comprises the following steps:

[0084] Step S410: performing consistency comparison between the hash value of each first keyword in the capital party JSON structure and the hash value of the corresponding standard keyword in the standard JSON structure.

[0085] For example, suppose the docking device uses the MD5 hash value algorithm to calculate the hash value of the first keyword "transaction serial number" in the JSON structure of the capital party, and the hash value obtained is: "e59ff4a3b3a7a5f7f7b1b3d7e7b7b7b7"; and the MD5 hash value algorithm is used to calculate the hash value of the corresponding standard keyword "application repayment payment number" in the standard JSON structure, and the hash value obtained is: "e5b9e7e0b4c7e2f7a3f9b6e7a9c5a7f", at this time, it can be determined that the hash values ​​of "transaction serial number" and "application repayment payment number" are inconsistent. However, if the docking device uses the MD5 hash value algorithm to calculate the hash value of the first keyword "status" in the JSON structure of the capital party, and the hash value of the corresponding standard keyword "status" in the standard JSON structure, the same hash value can be obtained, both of which are: "8f9bea9a3f7b5c8d6f0b7d8e1e2e3e4", and the hash values ​​of the two are consistent. In this way, the docking device can complete the consistency comparison step between each first keyword Hash value and each standard keyword Hash value one by one.

[0086] Step S420: According to the consistency comparison result, determine the first parameters of each hash value matching and the first parameters of each hash value not matching in the capital party JSON structure.

[0087] For example, if the hash values ​​of "transaction serial number" and "application repayment payment number" are inconsistent, it can be determined that there is a first parameter "transSerialNo" with a mismatched hash value in the JSON structure of the capital party. If the hash values ​​of "status" are consistent, it can be determined that there is a first parameter "status" with a matching hash value in the JSON structure of the capital party: "100, 110, 111". Among them, the first parameter "status": "100, 110, 111" means that the first parameter "status" has been assigned a value of "100, 110, 111".

[0088] Step S430: Convert the first parameters matching each hash value into corresponding standard parameters.

[0089] For example, the docking device may convert the first parameter "status" matching the hash value: "100, 110, 111" into the standard parameter "status".

[0090] Step S440: performing similarity check and manual marking on each first parameter whose hash value does not match to convert it into a corresponding standard parameter.

[0091] For example, the docking device converts the first parameter "transSerialNo" whose hash value does not match into "repayApplyNo" by similarity checking and manual marking.

[0092] Step S450: Generate a standard parameter structure based on the converted first parameters and the weight values ​​set by their corresponding standard keywords.

[0093] For example, after the first parameter "transSerialNo" is converted to "repayApplyNo", its corresponding standard keyword should become "application repayment payment number". And after the first parameter "status": "100, 110, 111" is converted to the standard parameter "status", its corresponding standard keyword is still "status". As mentioned above, it is known that the weight value set for "application repayment payment number" is 100%, and the weight value set for "status" is 50%. Finally, the docking device can generate a standard parameter structure based on "repayApplyNo-100%", "status-50%" and other "first parameter-corresponding weight value".

[0094] In the above-mentioned method for generating a standard parameter structure, the difference in hash values ​​between the first keyword of each group and the standard keyword is taken into consideration, and the "first parameter-corresponding weight value" is combined to generate a standard parameter structure, thereby improving the matching degree between the subsequently generated code and the interface document, avoiding human errors, and improving the docking efficiency between Internet financial systems.

[0095] In some embodiments, similarity checks and manual markings are performed on the first parameters whose hash values ​​do not match to convert them into corresponding standard parameters, such as Figure 5 As shown, the above method comprises the following steps:

[0096] Step S510: performing Hamming distance calculation on each first parameter whose hash value does not match, and / or introducing text similarity algorithm rules to perform similarity score calculation, to obtain each Hamming distance and / or each similarity score corresponding to each first parameter whose hash value does not match.

[0097] Specifically, when the docking device performs similarity check on each first parameter whose hash value does not match, it can only perform Hamming distance calculation, or only introduce text similarity algorithm rules to perform similarity score calculation, or perform Hamming distance calculation and introduce text similarity algorithm rules to perform similarity score calculation. Moreover, before performing Hamming distance calculation, the docking device needs to formulate corresponding values ​​for each first parameter whose hash value does not match and the corresponding multiple standard keywords.

[0098] Among them, each Hamming distance represents the degree of difference between the first keyword corresponding to the first parameter that does not match each hash value and the multiple standard keywords corresponding to it in the standard JSON structure, and each similarity score reflects the degree of similarity between the first keyword corresponding to the first parameter that does not match each hash value and the various standard keywords in the standard keyword library.

[0099] For example, it is known that the first parameter with the unmatched hash value is "transSerialNo", and the corresponding keyword is "transaction serial number", and the Hamming distance between it and the corresponding standard keyword "application repayment payment number" in the standard JSON structure should be 6; and the Hamming distance between "transaction serial number" and another standard keyword "status" should be 8. In this way, the multiple Hamming distances between any first parameter with unmatched hash value and its corresponding one can be determined.

[0100] Step S520: converting each first parameter whose hash value does not match into a corresponding standard parameter according to each Hamming distance and / or each similarity score.

[0101] Specifically, assuming that the docking device only performs Hamming distance calculation, it is only necessary to perform the conversion operation of the first parameter according to each Hamming distance. If the docking device only introduces the text similarity algorithm rule to perform the similarity score calculation, it is only necessary to perform the conversion operation of the first parameter according to each similarity score. If the docking device performs both Hamming distance calculation and text similarity algorithm rules to perform the similarity score calculation, it is necessary to first perform the first conversion operation according to each Hamming distance, and then perform the second conversion operation according to each similarity score.

[0102] For example, it is known that the Hamming distances between the first keyword "transaction serial number" corresponding to the first parameter and "application repayment payment number" and "status" are 6 and 8 respectively. The docking device can select the smallest Hamming distance to perform the conversion operation, and the "transaction serial number" will be converted to "application repayment payment number". However, since the larger the Hamming distance, the greater the difference between the first keyword and the standard keyword, the docking device generally does not select the largest Hamming distance to perform the conversion operation to avoid the problem of too low precision of the generated code.

[0103] Step S530: If there are still one or more first parameters that cannot be converted into standard parameters, they are manually marked to complete the conversion into standard parameters.

[0104] Specifically, there may be first parameters that cannot be converted into standard parameters due to the fact that the difference between the Hamming distances under some first keywords is too small, there are too many similarities, or due to the fact that the difference between the similarity scores under some first keywords is too small, there are too many similarities, etc. In this case, the docking device needs to present these first parameters that cannot be converted to the user, so that the user can manually mark these first parameters that cannot be converted to complete the conversion of the standard parameters.

[0105] In the above-mentioned method of converting the first parameter into the corresponding standard parameter, the Hamming distance difference between each first keyword and its multiple standard keywords is taken into account, and the text similarity algorithm rules are introduced to perform the similarity score calculation. Finally, the final conversion of the standard parameter is completed through manual marking, which improves the matching degree between the subsequently generated code and the interface document, avoids the generation of erroneous code, and improves the docking efficiency between Internet financial systems.

[0106] In some embodiments, if the Hamming distance calculation is performed only on the first parameters whose hash values ​​do not match, and the first parameters whose hash values ​​do not match are converted into corresponding standard parameters according to the Hamming distances, such as Figure 6 As shown, the above method comprises the following steps:

[0107] Step S610: according to the set Hamming distance threshold, determining the number of Hamming distances within the Hamming distance threshold among the Hamming distances corresponding to the first parameters that do not match the hash values.

[0108] Specifically, the Hamming distance threshold is a value set according to the conversion accuracy requirement.

[0109] For example, assuming that the Hamming distance threshold is set to 7, it is known that the Hamming distances between the first keyword "transaction serial number" and "application repayment payment number" and "status" are 6 and 8 respectively, and the Hamming distances between "transaction serial number" and other standard keywords are not less than 7, then it can be determined that the number of Hamming distances within the Hamming distance threshold 6 is 1.

[0110] Step S620: determine one or more first parameters and their corresponding first keywords within the Hamming distance threshold whose Hamming distance quantity is not less than the set quantity precision, and determine the standard parameter with the minimum Hamming distance from each first keyword.

[0111] Specifically, the number precision is also a value set according to the conversion precision requirement. If the number of Hamming distances within the Hamming distance threshold is too small, it means that the conversion between the first keyword and its corresponding standard keywords is no longer completed by the Hamming distance calculation method. On the contrary, if the number of Hamming distances within the Hamming distance threshold is not less than the set number precision, it means that the conversion between the first keyword and its corresponding standard keywords is completed by the Hamming distance calculation method.

[0112] For example, as mentioned above, assuming that the number precision is set to 5, and the number of Hamming distances within the Hamming distance threshold of 6 is 1, it means that the conversion between "transaction serial number" and its corresponding standard keywords is not applicable to the Hamming distance calculation method. Assuming that the number precision is set to 1, the number of Hamming distances within the Hamming distance threshold of 6 is not less than 1, indicating that the conversion between "transaction serial number" and its corresponding standard keywords is applicable to the Hamming distance calculation method, and "transaction serial number" belongs to the first category of the above-mentioned keywords.

[0113] Step S630: converting the first parameters corresponding to the first keywords of each category into standard parameters corresponding to the minimum Hamming distance.

[0114] For example, if it is known that "transaction serial number" belongs to a category of first keywords, the docking device converts the first parameter "transSerialNo" corresponding to "transaction serial number" into the standard parameter "repayApplyNo" corresponding to the minimum Hamming distance (6). Similarly, the docking device converts the first parameters of the remaining categories of first keywords into the standard parameters corresponding to the minimum Hamming distance in this way.

[0115] In the above-mentioned method of converting the first parameter into the corresponding standard parameter, since not only the Hamming distance difference between each first keyword and its multiple standard keywords is considered, but also the applicability of the Hamming distance calculation method is judged, the matching degree between the subsequently generated code and the interface document is improved, and the docking efficiency between Internet financial systems is further improved.

[0116] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter whose hash value does not match is converted into a corresponding standard parameter according to each Hamming distance and each similarity score, such as Figure 7 As shown, the above method comprises the following steps:

[0117] Step S710: Filter one or more second-category first keywords whose number of corresponding standard parameters within the Hamming distance threshold is less than the set number precision, and the first parameters corresponding to each second-category first keyword will not be converted into the standard parameter with the smallest corresponding Hamming distance.

[0118] Specifically, the second type of first keyword refers to the first keyword that is converted in a manner that does not apply the Hamming distance calculation as described above.

[0119] Step S720: introducing text similarity algorithm rules to calculate and obtain similarity scores of the first keywords of each second category.

[0120] The text similarity algorithm rule may be one of the TF-IDF (Term Frequency-Inverse Document Frequency) rule, the cosine similarity rule, the Jaccard similarity rule, and the edit distance rule. For example, assuming that "transaction serial number" belongs to the first keyword of the second category, if the TF-IDF method is used to calculate the similarity scores between it and "application repayment payment number" and "status", the similarity scores are 1 / 3 and 0 respectively.

[0121] Step S730: According to the set score threshold, from the similarity scores of the second-category first keywords, determine the second-category first keywords whose corresponding similarity scores are higher than the score threshold.

[0122] Among them, the score threshold is a value set according to the code generation accuracy requirements. For example, assuming that the score threshold is set to 1, it is known that the similarity scores between the first keyword "transaction serial number" and "application repayment payment number" and "status" are 1 / 3 and 0 respectively, and the similarity scores between "transaction serial number" and other standard keywords are not greater than 1, then it can be determined that the similarity scores corresponding to "transaction serial number" are not higher than the score threshold 1. However, if the score threshold is set to 1 / 4, then it can be determined that the similarity score corresponding to "transaction serial number" is higher than the score threshold 1 / 4, so it can be determined that "transaction serial number" belongs to the second category of first keywords that are higher than the score threshold.

[0123] Step S740: converting the first parameters corresponding to the second-category first keywords that are higher than the score threshold into corresponding standard parameters.

[0124] For example, if it is known that "transaction serial number" belongs to the second category first keyword that is higher than the score threshold, the docking device converts the first parameter "transSerialNo" corresponding to "transaction serial number" into the standard parameter "repayApplyNo" corresponding to the minimum Hamming distance (6). Similarly, the docking device converts the first parameters corresponding to the other two categories of first keywords into the standard parameters corresponding to the minimum Hamming distance in this way.

[0125] In the above-mentioned method of converting the first parameter into the corresponding standard parameter, since not only the Hamming distance difference between each first keyword and its multiple standard keywords is considered, but also the text similarity algorithm rules are introduced to perform the similarity score calculation, the matching degree between the subsequently generated code and the interface document is improved, the generation of erroneous codes is avoided, and the docking efficiency between Internet financial systems is further improved.

[0126] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and only the first parameters with unmatched hash values ​​are converted into corresponding standard parameters according to the respective similarity scores, such as Figure 8 As shown, the above method comprises the following steps:

[0127] Step S810: according to the set score threshold, from the similarity scores corresponding to the first parameters whose hash values ​​do not match, three types of first keywords whose corresponding similarity scores are higher than the score threshold are determined.

[0128] Specifically, the three categories of first keywords refer to the three categories of first keywords whose corresponding similarity scores are higher than the score threshold when the conversion operation is performed only according to the respective similarity scores.

[0129] Step S820: converting the first parameters corresponding to the three types of first keywords that are higher than the score threshold into standard parameters with the highest corresponding similarity scores.

[0130] For example, assuming that the score threshold is set to 1 / 10, and the similarity scores between the first keyword "transaction serial number" and "application repayment payment number", "status" and "account name" are known to be 1 / 3, 0, and 1 / 9 respectively, it can be determined that "transaction serial number" belongs to the three categories of first keywords, and the standard parameters with similarity scores higher than the score threshold (1 / 10) are "application repayment payment number" and "account name". Among them, the standard keyword with the highest similarity score should be "application repayment payment number (similarity score 1 / 3)", and the docking device will convert the first parameter "transSerialNo" corresponding to "transaction serial number" into the standard parameter "repayApplyNo" corresponding to "application repayment payment number".

[0131] In the above-mentioned method of converting the first parameter into the corresponding standard parameter, since not only the text similarity algorithm rules are introduced to perform the similarity score calculation, but also the standard parameter with the highest corresponding similarity score is selected for conversion, the matching degree between the subsequently generated code and the interface document is improved, and the docking efficiency between Internet financial systems is further improved.

[0132] Step S250: Map each parameter in the investor's JSON structure to the standard parameter structure one by one, and generate the docking code required for the Internet financial system to access the investor's business system.

[0133] Among them, each parameter includes the first keyword and its corresponding first parameter extracted by the docking device from the interface document according to the above standard rules. The docking device first parses the JSON structure provided by the capital party, and then maps it one by one to the standard parameter structure of the Internet financial system according to each parameter. Finally, the docking device can generate the corresponding docking code according to the mapping result, and display it to the user through the code generation application. The code generated in this way can avoid human errors and improve the docking efficiency and adaptability between Internet financial systems.

[0134] In one embodiment of the present application, the docking device first obtains the interface document of the capital party's business system, and the first keywords included in the interface document are "transaction serial number" and "loan number", and the corresponding first parameters are "transSerialNo" and "loanSerialNo", and the values ​​corresponding to the two first parameters are "XIANREPAY20240816000000481977" and "HXJ20240718000003000461". Then, the first keyword and its corresponding first parameter are extracted from the interface document according to the preset standard rules. Among them, the standard rules include the first mapping relationship "application repayment payment number"-"repayApplyNo"-"transaction serial number"-"transSerialNo", the second mapping relationship "loan number"-"loanSerialNo"-"loan number"-"loanNo", the third mapping relationship "status"-"status" and the supplementary fourth mapping relationship "account name"-"account name"-"accountName"; in addition, the standard rules also include the weight values ​​corresponding to the settings of each standard keyword. Furthermore, if it is known that "transSerialNo" exists in the interface document, the docking device can extract the first keyword "transaction serial number" and its corresponding first parameter "transSerialNo" from the interface document according to the standard rule. Then the docking device generates the capital side JSON structure according to the "transaction serial number" and its "transSerialNo".

[0135] Then, after the hash value processing, the docking device finds that the first hash value processing result of the capital party JSON structure is "e59ff4a3b3a7a5f7f7b1b3d7e7b7b7b7", while the second hash value processing result of the standard JSON structure is "e5b9e7e0b4c7e2f7a3f9b6e7a9c5a7f". The hash values ​​of the two do not match. The docking device needs to introduce the text similarity algorithm rules to perform the similarity score calculation, and then convert "transSerialNo" to "repayApplyNo" and generate a standard parameter structure. Finally, the docking device maps each parameter in the capital party JSON structure to the standard parameter structure one by one, and generates the docking code required for the Internet financial system to access the capital party's business system. In this way, the docking code is automatically generated, which can avoid human errors and improve the docking efficiency and adaptability between Internet financial systems.

[0136] It should be noted that, with respect to the various steps included in the method for generating a docking code based on an interface document provided in any of the above embodiments, unless otherwise clearly stated in this document, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of these steps may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0137] According to a second aspect, the present application provides a system for generating a docking code based on an interface document, such as Fig. 9 As shown, the system includes:

[0138] The document recognition module 110 is used to obtain the interface document of the capital-side business system that the Internet financial system needs to connect with;

[0139] A keyword extraction module 120, configured to extract a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule;

[0140] The parameter body extraction module 130 is used to generate a capital party JSON structure body according to each first keyword and its corresponding first parameter;

[0141] A standard parameter generation module 140, configured to convert each first parameter and generate a standard parameter structure based on a first hash value processing result of the capital party JSON structure and a second hash value processing result of a preset standard JSON structure;

[0142] The code generation module 150 is used to map each parameter in the investor's JSON structure to a standard parameter structure one by one, and generate the connection code required for the Internet financial system to access the investor's business system.

[0143] In some embodiments, before obtaining the interface document of the capital provider business system that the Internet financial system needs to connect to, the keyword extraction module 120 is further used to:

[0144] Acquire multiple standard parameters of the Internet financial system and their corresponding standard keywords; extract target historical codes, parse the target historical codes and obtain historical documents; extract multiple supplementary keywords and their corresponding supplementary parameters from the historical documents according to various standard parameters; generate a standard keyword library based on the extracted supplementary keywords and various standard keywords; set corresponding weight values ​​for each standard keyword in the standard keyword library, and each weight value is determined according to the historical usage habits of the corresponding standard keyword, the position in the code and the document, and the human error correction habits.

[0145] In some embodiments, the standard JSON structure is generated according to the standard keyword library, the first hash value processing result includes the hash value of each first keyword in the capital JSON structure, and the second hash value processing result includes the hash value of each standard keyword in the standard JSON structure; based on the hash value processing results of the capital JSON structure and the preset standard JSON structure, each first parameter is converted and a standard parameter structure is generated, and the standard parameter generation module 140 is further used to:

[0146] The hash value of each first keyword in the investor's JSON structure is compared with the hash value of the corresponding standard keyword in the standard JSON structure one by one for consistency; based on the consistency comparison result, the first parameters that match each hash value in the investor's JSON structure and the first parameters that do not match each hash value are determined; each first parameter that matches the hash value is converted into a corresponding standard parameter; each first parameter that does not match the hash value is subjected to similarity verification and manual marking to convert it into a corresponding standard parameter; a standard parameter structure is generated based on the weight values ​​set for each first parameter after the conversion and its corresponding standard keyword.

[0147] In some embodiments, the standard parameter generation module 140 is further configured to:

[0148] Performing Hamming distance calculation on each first parameter whose hash value does not match, and / or introducing text similarity algorithm rules to perform similarity score calculation, to obtain each Hamming distance and / or each similarity score corresponding to each first parameter whose hash value does not match;

[0149] Convert each first parameter that does not match the hash value into a corresponding standard parameter according to each Hamming distance and / or each similarity score;

[0150] If there are still one or more first parameters that cannot be converted to standard parameters, they are manually marked to complete the conversion to standard parameters;

[0151] Among them, each Hamming distance represents the degree of difference between the first keyword corresponding to the first parameter that does not match each hash value and the multiple standard keywords corresponding to it in the standard JSON structure, and each similarity score reflects the degree of similarity between the first keyword corresponding to the first parameter that does not match each hash value and the various standard keywords in the standard keyword library.

[0152] In some embodiments, if the Hamming distance calculation is performed only on the first parameters whose hash values ​​do not match, and the first parameters whose hash values ​​do not match are converted into corresponding standard parameters according to the Hamming distances, the standard parameter generation module 140 is further used to:

[0153] According to the set Hamming distance threshold, the number of Hamming distances within the Hamming distance threshold is determined among the Hamming distances corresponding to the first parameters whose hash values ​​do not match; one or more first parameters and their corresponding first keywords of a class whose number of Hamming distances within the Hamming distance threshold is not less than the set number precision are determined, and the standard parameter with the minimum Hamming distance is determined from each first keyword of the class; the first parameter corresponding to each first keyword of the class is converted into the standard parameter with the minimum corresponding Hamming distance.

[0154] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter with unmatched hash values ​​is converted into a corresponding standard parameter according to each Hamming distance and each similarity score, the standard parameter generation module 140 is further used to:

[0155] One or more second-category first keywords whose number of corresponding standard parameters within the Hamming distance threshold is less than the set number precision are screened, and the first parameters corresponding to each second-category first keyword will not be converted into the standard parameter with the smallest corresponding Hamming distance; the text similarity algorithm rule is introduced to calculate the similarity score of each second-category first keyword; according to the set score threshold, from the similarity scores of each second-category first keyword, the second-category first keyword whose corresponding similarity score is higher than the score threshold is determined; the first parameters corresponding to the second-category first keywords higher than the score threshold are converted into the corresponding standard parameters.

[0156] In some embodiments, if a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter with unmatched hash values ​​is converted into a corresponding standard parameter only according to each similarity score, the standard parameter generation module 140 is further used to:

[0157] According to the set score threshold, three types of first keywords whose corresponding similarity scores are higher than the score threshold are determined from the similarity scores corresponding to the first parameters whose hash values ​​do not match; and the first parameters corresponding to the three types of first keywords higher than the score threshold are converted into standard parameters with the highest corresponding similarity scores.

[0158] For the specific limitations of the system suitable for generating docking codes based on interface documents, please refer to the limitations of the method suitable for generating docking codes based on interface documents above, which will not be repeated here. The various modules in the above-mentioned system suitable for generating docking codes based on interface documents can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0159] According to a third aspect, the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for generating a docking code based on an interface document in any one of the above embodiments are implemented.

[0160] According to a fourth aspect, the present application provides a computer device, such as Fig.10 As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of any one of the methods for generating a docking code based on an interface document in the above-mentioned embodiments are implemented.

[0161] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data related to the generation of docking codes based on interface documents. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, any of the above methods for generating docking codes based on interface documents is implemented.

[0162] Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (RamCus), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0163] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0164] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

[0165] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

Claims

1. A method for generating a docking code based on an interface document, characterized in that: include: Obtain the interface documents of the capital business system that the Internet financial system needs to connect with; Extracting a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule; Generate an investor JSON structure according to each of the first keywords and the first parameters corresponding thereto; Based on the first hash value processing result of the investor JSON structure and the second hash value processing result of the preset standard JSON structure, convert each of the first parameters and generate a standard parameter structure; Map each parameter in the investor's JSON structure to the standard parameter structure one by one, and generate the docking code required for the Internet financial system to access the investor's business system.

2. The method according to claim 1, characterized in that Before obtaining the interface document of the capital-side business system that the Internet financial system needs to connect to, the method further includes: Acquire multiple standard parameters of the Internet financial system and their corresponding standard keywords; Extracting target historical codes, parsing the target historical codes and obtaining historical documents; Extracting a plurality of supplementary keywords and their corresponding supplementary parameters from the historical document according to each of the standard parameters; Generate a standard keyword library based on the extracted supplementary keywords and the standard keywords; A corresponding weight value is set for each standard keyword in the standard keyword library, and each weight value is determined according to the historical usage habits of the corresponding standard keyword, the position in the code and document, and the human error correction habits.

3. The method according to claim 2, characterized in that The standard JSON structure is generated according to the standard keyword library, the first hash value processing result includes the hash value of each of the first keywords in the capital JSON structure, and the second hash value processing result includes the hash value of each of the standard keywords in the standard JSON structure; Based on the hash value processing results of the capital JSON structure and the preset standard JSON structure, each of the first parameters is converted to generate a standard parameter structure, including: Comparing the hash value of each of the first keywords in the investor JSON structure with the hash value of the corresponding standard keyword in the standard JSON structure one by one; According to the consistency comparison result, determine the first parameter in the JSON structure of the capital party where each hash value matches and the first parameter where each hash value does not match; Convert the first parameters matched by the respective hash values ​​into corresponding standard parameters; Performing similarity check and manual marking on the first parameters whose hash values ​​do not match each other to convert them into corresponding standard parameters; A standard parameter structure is generated based on the weight values ​​set by the first parameters and their corresponding standard keywords after the conversion.

4. The method according to claim 3, characterized in that The performing similarity check and manual marking on the first parameters whose hash values ​​do not match to convert them into corresponding standard parameters includes: Performing Hamming distance calculation on the first parameters whose hash values ​​do not match, and / or introducing text similarity algorithm rules to perform similarity score calculation, to obtain respective Hamming distances and / or respective similarity scores corresponding to the first parameters whose hash values ​​do not match; Converting the first parameters that do not match the hash values ​​into corresponding standard parameters according to the Hamming distances and / or the similarity scores; If there are still one or more first parameters that cannot be converted into the standard parameters, manually marking them to complete the conversion of the standard parameters; Among them, each Hamming distance represents the degree of difference between the first keyword corresponding to the first parameter that each hash value does not match and the multiple standard keywords corresponding to it in the standard JSON structure, and each similarity score reflects the degree of similarity between the first keyword corresponding to the first parameter that each hash value does not match and each of the standard keywords in the standard keyword library.

5. The method according to claim 4, characterized in that If the Hamming distance calculation is performed only on the first parameters that do not match the respective hash values, and the first parameters that do not match the respective hash values ​​are converted into corresponding standard parameters according to the respective Hamming distances, the method includes: According to a set Hamming distance threshold, determining the number of Hamming distances within the Hamming distance threshold among the Hamming distances corresponding to the first parameters that do not match the hash values; Determine one or more first parameters and a class of first keywords corresponding to the parameters whose Hamming distance quantity within the Hamming distance threshold is not less than the set quantity precision, and determine the standard parameter with the minimum Hamming distance from each of the first keywords of the class; The first parameters corresponding to the first keywords of each category are converted into standard parameters with the smallest corresponding Hamming distance.

6. The method according to claim 5, characterized in that If a text similarity algorithm rule is introduced to perform similarity score calculation, and the first parameters that do not match the hash values ​​are converted into corresponding standard parameters according to the Hamming distances and the similarity scores, the method includes: Screening one or more second-category first keywords whose number of corresponding standard parameters within the Hamming distance threshold is less than the set number precision, and the first parameters corresponding to each of the second-category first keywords will not be converted into the standard parameters with the smallest corresponding Hamming distance; Introducing the text similarity algorithm rule to calculate and obtain the similarity score of each of the second category first keywords; According to the set score threshold, from the similarity scores of the first keywords of the second category, determine the first keywords of the second category whose corresponding similarity scores are higher than the score threshold; The first parameters corresponding to the second category first keywords that are higher than the score threshold are converted into corresponding standard parameters.

7. The method according to claim 4, characterized in that If a text similarity algorithm rule is introduced to perform similarity score calculation, and each first parameter whose hash value does not match is converted into a corresponding standard parameter only according to each similarity score, the method includes: According to the set score threshold, from the respective similarity scores corresponding to the first parameters whose hash values ​​do not match, determine three types of first keywords whose corresponding similarity scores are higher than the score threshold; The first parameters corresponding to the three types of first keywords that are higher than the score threshold are converted into standard parameters with the highest corresponding similarity scores.

8. A system for generating docking code based on an interface document, characterized in that: The system comprises: The document recognition module is used to obtain the interface documents of the capital business system that the Internet financial system needs to connect with; A keyword extraction module, used to extract a first keyword and a first parameter corresponding to the first keyword from the interface document according to a preset standard rule; A parameter body extraction module, used to generate a capital party JSON structure body according to each of the first keywords and the first parameters corresponding thereto; A standard parameter generation module, configured to convert each of the first parameters and generate a standard parameter structure based on a first hash value processing result of the capital party JSON structure and a second hash value processing result of a preset standard JSON structure; The code generation module is used to map each parameter in the investor's JSON structure to the standard parameter structure one by one, and generate the docking code required for the Internet financial system to access the investor's business system.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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