Intelligent signature method and device, computer equipment and readable storage medium

Abstract

The invention relates to the technical field of electronic signature, and discloses an intelligent signature method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a pre-configured signature process, wherein the signature process comprises an intelligent signature node; when the signature process is carried out to the intelligent signature node, historical signature behavior information of the user is obtained, and the historical signature behavior information comprises a plurality of signature positions and operation types and seal types corresponding to the signature positions; scoring the operation type and the seal type of each signature position by using a preset weighting algorithm to obtain a plurality of scoring results, and taking the signature position with the highest scoring result as the optimal signature position at the intelligent signature node; and obtaining signing information in the flow form, and signing the flow form according to the optimal signing position and the signing information. According to the method and the device, the file signature efficiency in the workflow is effectively improved, and the accuracy and normalization of signature operation are ensured.

Description

Technical Field

[0001] The present invention relates to the field of electronic signature technology, and in particular to an intelligent signature method, device, computer equipment and readable storage medium. Background Art

[0002] In the traditional office model, document signing and stamping were heavily reliant on manual labor. This process was not only time-consuming and significantly slowed workflow, but the uncontrollable nature of manual operations also led to errors and omissions in signatures, severely impacting work efficiency and document processing accuracy.

[0003] With the advent of the digital office era, electronic signature technology has emerged, improving the signature process to a certain extent. However, existing technologies generally suffer from the drawback of insufficient intelligence. For example, in the seal selection process, it is impossible to accurately match the actual needs of users; in the signature positioning process, there is a lack of intelligent judgment based on file characteristics and user habits, making it difficult to fully meet the diversified and personalized needs of modern office scenarios; and many systems lack deep integration with electronic signature technology, resulting in users having to complete the signature operation in an external system and then manually upload the signature file, which requires users to switch between multiple systems and reduces work efficiency.

[0004] Therefore, existing signature technologies have technical problems such as inability to accurately match user needs, complex signature processes, and low efficiency. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and to provide an intelligent signature method, apparatus, computer device and readable storage medium.

[0006] The present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an intelligent signature method, the method comprising:

[0008] Obtain a pre-configured signature process, wherein the signature process includes an intelligent signature node;

[0009] When the signature process reaches the smart signature node, the user's historical signature behavior information is obtained, and the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position;

[0010] Scoring the operation type and seal type of each signature position using a preset weighted algorithm to obtain multiple scoring results, and taking the signature position with the highest scoring result as the optimal signature position at the intelligent signature node;

[0011] The contract information in the process form is obtained, and the process form is signed according to the optimal signature position and the contract information.

[0012] In an optional embodiment, the operation type includes manual operation and automatic operation, the seal type includes keyword seal, interleaving seal, page header seal and page footer seal, and the operation type and seal type of each signature position are scored using a preset weighted algorithm to obtain multiple scoring results, including:

[0013] Obtaining a first preset weight for each of the operation types, and obtaining a second preset weight for each of the seal types;

[0014] The first preset weight and the second preset weight of each signature position are coupled and calculated by a multiplication operator to generate a composite behavior feature value of each signature position, and the composite behavior feature value of each signature position is used as a scoring result of each signature position.

[0015] In an optional embodiment, after taking the composite behavior feature value of each signature position as the scoring result of each signature position, the method further includes:

[0016] Based on the dimensions of the seal types, constructing an operation frequency statistical matrix of the user, wherein the operation frequency statistical matrix records the number of operations performed by the user under each seal type;

[0017] Constructing a composite behavior characteristic value matrix of the user, wherein the composite behavior characteristic value matrix records the composite behavior characteristic values of the user under each of the seal types;

[0018] A behavior profile of the user is constructed based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix.

[0019] In an optional embodiment, after constructing the user's behavior profile based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix, the method further includes:

[0020] Obtaining a first seal type corresponding to the number of operations exceeding a preset frequency threshold in the operation frequency statistical matrix;

[0021] Obtaining a second seal type corresponding to a composite behavior feature value exceeding a preset feature value threshold among the composite behavior feature values of the first seal type;

[0022] According to the second seal type, early warning information is generated.

[0023] In an optional embodiment, the method further comprises:

[0024] Counting the occurrence frequencies of the signature positions, sorting the occurrence frequencies of the signature positions in descending order, and obtaining the signature positions corresponding to the first preset number of occurrence frequencies;

[0025] A signature position template library of the user is generated according to the signature positions corresponding to the first preset number of occurrence frequencies.

[0026] In an optional embodiment, the method further comprises:

[0027] Extracting the signature-related text from the user's historical signature behavior information, obtaining key contents related to the keyword seal from the signature-related text, and counting the word frequency and word length of each key content;

[0028] Calculating the number of words contained in each key content using a space segmentation method, and training a natural language processing model based on the word frequency and word length of each key content and the number of words contained in each key content;

[0029] The trained natural language processing model is used to predict the candidate signature positions at the intelligent signature node.

[0030] In a second aspect, the present invention provides an intelligent signature device, comprising:

[0031] A first acquisition module is used to acquire a pre-configured signature process, wherein the signature process includes an intelligent signature node;

[0032] A second acquisition module is configured to acquire the user's historical signature behavior information when the signature process reaches the smart signature node, wherein the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position;

[0033] A scoring module is used to score the operation type and seal type of each signature position using a preset weighted algorithm to obtain multiple scoring results, and use the signature position with the highest scoring result as the optimal signature position at the smart signature node;

[0034] The signature module is used to obtain the contract information in the process form and sign the process form according to the optimal signature position and the contract information.

[0035] In an optional embodiment, the operation type includes manual operation and automatic operation, the seal type includes keyword seal, interleaving seal, page header seal and page footer seal, and the scoring module further includes:

[0036] An acquisition submodule, configured to acquire a first preset weight for each of the operation types and a second preset weight for each of the seal types;

[0037] The calculation submodule is used to couple the first preset weight and the second preset weight of each signature position through a multiplication operator to generate a composite behavior feature value of each signature position, and use the composite behavior feature value of each signature position as the scoring result of each signature position.

[0038] In a third aspect, a computer device is provided in an embodiment of the present disclosure, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the intelligent signature method described in the first aspect when executing the computer program.

[0039] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the intelligent signature method described in the first aspect are implemented.

[0040] Beneficial effects of this application:

[0041] The intelligent signature method provided by the embodiment of the present application obtains a pre-configured signature process, which includes an intelligent signature node; when the signature process reaches the intelligent signature node, the user's historical signature behavior information is obtained, and the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position; the operation type and seal type of each signature position are scored using a preset weighted algorithm to obtain multiple scoring results, and the signature position with the highest scoring result is used as the best signature position at the intelligent signature node; the contract information in the process form is obtained, and the process form is signed according to the best signature position and the contract information. The present application realizes intelligent selection and positioning of seals based on the user's historical behavior habits and file characteristics, and encapsulates complex signature logic and rules by combining intelligent signatures with workflows. Users can quickly build a signature workflow that meets their needs through simple dragging and configuration, which improves the efficiency of file signing in the workflow and ensures the accuracy and standardization of signature operations.

[0042] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. Similar components are numbered similarly in the various drawings.

[0044] Figure 1 A flowchart of an intelligent signature method provided by an embodiment of the present application is shown;

[0045] Figure 2 A flowchart of another intelligent signature method provided by an embodiment of the present application is shown;

[0046] Figure 3 A flowchart of another intelligent signature method provided by an embodiment of the present application is shown;

[0047] Figure 4 A schematic diagram of the structure of an intelligent signature device provided in an embodiment of the present application is shown;

[0048] Figure 5 A structural diagram of a computer device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0049] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0050] It should be noted that the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Therefore, features defined as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used in the template description herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0052] Example 1

[0053] like Figure 1 FIG. 1 is a flow chart of an intelligent signature method according to an embodiment of the present application. The intelligent signature method provided by the embodiment of the present application includes the following steps:

[0054] Step S110: obtaining a pre-configured signature process, wherein the signature process includes an intelligent signature node.

[0055] In this embodiment, a powerful visual interface is provided. Users can drag and drop various controls in the form and configure them to achieve flexible workflow design. In the workflow, it supports dragging the "Smart Signature" node to the appropriate position and completing the relevant configuration, while generating the workflow XML configuration information. The specific configuration content includes:

[0056] (1) Configure each node userTask (user task) of the workflow and add the tag type of the smart signature to signTask to clearly distinguish its function.

[0057] (2) Add node attribute configuration, including the type of signature required, such as (keywords, interleaving), etc., to provide a basis for subsequent accurate signature.

[0058] (3) Add node form configuration and fill in the form control information of the contract document, which is suitable for subsequent signature selection files.

[0059] Through a visual interface and flexible configuration, the above steps allow users to quickly build a signature process that meets their needs, lowering the technical threshold and improving work efficiency. At the same time, clear node marking and detailed attribute configuration lay the foundation for subsequent intelligent signature processing, ensuring the accuracy and reliability of the signature process.

[0060] Step S120: When the signature process reaches the smart signature node, the user's historical signature behavior information is obtained. The historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position.

[0061] Understandably, through the rapid configuration of the low-code platform and the normal operation of the workflow module, when the signature process reaches the "intelligent signature node", the intelligent signature business processing is carried out, and the user's historical signature behavior information is automatically obtained. The historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each of the signature positions. With the efficient configuration capabilities of the low-code platform and the stable operation of the workflow module, the system can smoothly carry out the signature business processing when it reaches the intelligent signature node.

[0062] Among them, the operation type includes manual operation and automatic operation, and the seal type includes keyword seal, interleaving seal, page header seal and page footer seal. It should be noted that the specific operation type and seal type can be determined according to actual conditions, and the embodiment of the application does not limit this.

[0063] In an optional implementation, the ROUND function can also be used to standardize the horizontal and vertical coordinates of the signature position to two decimal places to improve the accuracy and consistency of the signature, eliminate coordinate drift caused by device resolution differences, and improve the quality and reliability of the signature.

[0064] The above steps capture the user's historical signature behavior, providing rich data support for subsequent intelligent signature location selection. By analyzing historical data, the system can better understand the user's signature habits and preferences, thereby providing a signature solution that better meets the user's needs.

[0065] Step S130 , using a preset weighted algorithm to score the operation type and seal type of each signature position to obtain multiple scoring results, and taking the signature position with the highest scoring result as the best signature position at the smart signature node.

[0066] Specifically, in this embodiment, an operation type weight matrix and a seal type weight matrix are pre-established, wherein the operation type weight matrix is used to define the weight ratios corresponding to manual operation types and automatic operation types, respectively, and the seal type weight matrix is used to perform differentiated configurations for various typical seal usage scenarios.

[0067] For example, if the weight ratio of manual operation type to automatic operation type is 2:1, it means that the manual operation type (marked as 0) is assigned a weight value of 2, reflecting the value of manual decision-making; the automatic operation type (marked as 1) is assigned a weight value of 1, reflecting the regularity of programmed execution.

[0068] For example, the interline seal type (marked as 1) corresponds to a weight of 3, which ensures the integrity of the document; the keyword seal type (marked as 2) corresponds to the highest weight of 5, because it involves the verification of the core content of the document; the header seal type (marked as 3) corresponds to a weight of 2, and the footer seal type (marked as 4) corresponds to a weight of 1, which mainly serves as an identification.

[0069] It should be noted that this embodiment adopts a flexible default value mechanism. When an undefined type identifier is detected, a baseline weight value of 1 is automatically assigned to the operation type and seal type. The specific weight value can be determined according to actual conditions, and this embodiment of the application does not limit this.

[0070] The first preset weight for each operation type is obtained from the operation type weight matrix, and the second preset weight for each seal type is obtained from the seal type weight matrix. The first and second preset weights for each signature position are then coupled together using a multiplication operator to generate a composite behavioral feature value for each signature position, i.e., the scoring result, accurately quantifying the value of the user's operation.

[0071] For example, when a combination of a manual operation type (weight 2) and a keyword chapter type (weight 5) is detected, a composite feature value of 2×5=10 points will be generated.

[0072] Preferably, the signature position with the highest score result is used as the best signature position at the smart signature node, and a preview file is generated for users to quickly generate.

[0073] Through a scientific weighting algorithm and weight matrix, the system comprehensively considers the importance of operation type and seal type to signature placement, accurately selecting the optimal signature location. Scoring and recommendations based on actual user operation data meet the personalized needs of different users, providing signature solutions that align with user habits and business scenarios, thereby enhancing the user experience.

[0074] In an optional embodiment, as Figure 2 As shown, after taking the composite behavior feature value of each signature position as the scoring result of each signature position, the method further includes:

[0075] Step S131: constructing a user's operation frequency statistical matrix based on the dimensions of the seal type, wherein the operation frequency statistical matrix records the number of operations performed by the user under each seal type;

[0076] Step S132, constructing a composite behavior eigenvalue matrix of the user, wherein the composite behavior eigenvalue matrix records the composite behavior eigenvalues of the user under each of the seal types;

[0077] Step 133: construct a behavior profile of the user based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix.

[0078] Understandably, a hash map structure is constructed using the user's unique identifier as an index for quickly accessing and updating user behavior features. When a user action is first detected (e.g., the unique identifier appears for the first time), a user behavior feature container is created to avoid premature resource usage. Then, based on the seal type dimension, a user operation frequency statistics matrix is constructed. This operation frequency statistics matrix records the number of operations performed by the user under each seal type. A composite behavior feature value matrix is also constructed for the user. This composite behavior feature value matrix records the composite behavior feature values of the user under each seal type.

[0079] After each user operation, the operation frequency and the sum of the composite behavior characteristic values of the corresponding seal type are continuously updated through superimposed calculations, reflecting the changes in user behavior in real time and constructing a user behavior portrait (such as recent operation trends), ensuring the real-time and accuracy of the user portrait.

[0080] By building user behavioral profiles, the above steps enable a comprehensive understanding of users' signature patterns and habits, providing strong support for subsequent signature recommendations and risk warnings. By analyzing user operation frequency and composite behavioral characteristics, the system can better understand user behavior patterns and provide personalized signature services. Furthermore, the real-time updated behavioral profiles can promptly reflect changes in user behavior, ensuring the adaptability and effectiveness of the signature solution.

[0081] In an optional embodiment, as Figure 3 As shown, after constructing the user's behavior profile based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix, the following further comprises:

[0082] Step S134, obtaining the first seal type corresponding to the number of operations exceeding a preset frequency threshold in the operation frequency statistical matrix;

[0083] Step S135, obtaining a second seal type corresponding to a composite behavior feature value exceeding a preset feature value threshold among the composite behavior feature values of the first seal type;

[0084] Step S136: Generate warning information according to the second seal type.

[0085] In a comprehensible way, user profiles are converted into interpretable analytical results to drive business decision-making and early warning systems. The first seal type corresponding to the number of operations exceeding a preset frequency threshold in the operation frequency statistical matrix is obtained, and the second seal type corresponding to the composite behavioral feature value of the first seal type exceeding a preset feature value threshold is obtained. The purpose is to prevent malicious operations, such as high-frequency, high-weight operation combinations, and prompt the system for further review.

[0086] Through the risk warning mechanism described above, the system can promptly detect potential malicious operations or abnormal behavior, take preventive measures in advance, and ensure the security and reliability of the signature process. This data-based early warning method can effectively reduce the probability of risk and improve the overall security of the system.

[0087] In a preferred embodiment, the frequency of occurrence of each signature position is counted, and the frequency of occurrence of each signature position is sorted in descending order, and the signature positions corresponding to the first preset number (for example, the first 10) of occurrence frequencies are obtained to form a hotspot map;

[0088] Based on the coordinate distribution pattern of the signature positions corresponding to the preset number of occurrence frequencies, a signature position template library for the user is generated, which reduces the user's manual adjustment operations, solves the inefficiency problem caused by the random distribution of signature positions in traditional systems, drives intelligent position recommendations through historical data analysis, and reduces the cost of manual intervention.

[0089] This method, by generating a signature location hotspot map and template library, can provide users with more efficient and accurate signature location recommendations. Users no longer need to manually adjust the signature location; the system automatically recommends the optimal location based on historical data, significantly improving signature efficiency and reducing errors caused by manual operation.

[0090] In a preferred embodiment, the signature-associated text in the user's historical signature behavior information is extracted, and the key contents related to the signature-associated text and the keyword are obtained, and the word frequency and word length of each key content are counted to provide basic data for subsequent semantic analysis. Then, the space segmentation method is used to calculate the number of words contained in each key content, identify the complexity characteristics of long text signatures, and help understand the distribution and importance of keywords in the document. Then, based on the word frequency and word length of each key content and the number of words contained in each key content, a natural language processing model is trained. Finally, the trained natural language processing model is used to predict the alternative signature positions at the intelligent signature node, provide users with multiple alternative signature positions, realize intelligent signature recommendations, and improve the contextual consistency between signatures and document content.

[0091] Step S140: Acquire the contract information in the process form, and sign the process form according to the optimal signature position and the contract information.

[0092] Finally, the contract information (signing form, contracting party information, etc.) in the process form is obtained, and the process form is intelligently and automatically signed according to the optimal signature position and contract information determined in step S130.

[0093] The above steps realize the automation of signature operations, reduce manual intervention, reduce operational risks, improve the accuracy and consistency of signatures, shorten the processing time of business processes, improve overall work efficiency, and help speed up business transactions.

[0094] The intelligent signature method provided by the embodiment of the present application obtains a pre-configured signature process, which includes an intelligent signature node; when the signature process reaches the intelligent signature node, the user's historical signature behavior information is obtained, and the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position; the operation type and seal type of each signature position are scored using a preset weighted algorithm to obtain multiple scoring results, and the signature position with the highest scoring result is used as the best signature position at the intelligent signature node; the contract information in the process form is obtained, and the process form is signed according to the best signature position and the contract information. The present application realizes intelligent selection and positioning of seals based on the user's historical behavior habits and file characteristics, and encapsulates complex signature logic and rules by combining intelligent signatures with workflows. Users can quickly build a signature workflow that meets their needs through simple dragging and configuration, which improves the efficiency of file signing in the workflow and ensures the accuracy and standardization of signature operations.

[0095] Example 2

[0096] like Figure 4 FIG. 4 is a schematic diagram of the structure of an intelligent signature device 400 according to an embodiment of the present application, which includes:

[0097] A first acquisition module 410 is configured to acquire a pre-configured signature process, wherein the signature process includes an intelligent signature node;

[0098] The second acquisition module 420 is configured to acquire the user's historical signature behavior information when the signature process reaches the smart signature node, wherein the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position;

[0099] The scoring module 430 is configured to score the operation type and seal type of each signature position using a preset weighted algorithm to obtain multiple scoring results, and use the signature position with the highest scoring result as the optimal signature position at the smart signature node;

[0100] The signature module 440 is used to obtain the contract information in the process form and sign the process form according to the optimal signature position and the contract information.

[0101] Optionally, the operation type includes manual operation and automatic operation, the seal type includes keyword seal, interleaving seal, page header seal and page footer seal, and the scoring module further includes:

[0102] An acquisition submodule, configured to acquire a first preset weight for each of the operation types and a second preset weight for each of the seal types;

[0103] The calculation submodule is used to couple the first preset weight and the second preset weight of each signature position through a multiplication operator to generate a composite behavior feature value of each signature position, and use the composite behavior feature value of each signature position as the scoring result of each signature position.

[0104] The intelligent signature device provided in the embodiment of the present application can implement each process of the intelligent signature method corresponding to Example 1 and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0105] The intelligent signature device provided in the embodiment of the present application realizes intelligent signature selection and positioning based on the user's historical behavior habits and file characteristics. By combining intelligent signature with workflow, complex signature logic and rules are encapsulated. Users only need to drag and drop and configure to quickly build a signature workflow that meets their needs, thereby improving the efficiency of file signing in the workflow and ensuring the accuracy and standardization of signature operations.

[0106] Example 3

[0107] The present application also provides a computer device. Figure 5 , Figure 5 This is a basic structural block diagram of the computer device in this embodiment.

[0108] The computer device 5 includes a memory 51, a processor 52, and a network interface 53 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 5 with a memory 51, a processor 52, and a network interface 53, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0109] The computer device may be a desktop computer, notebook computer, PDA, cloud server, etc. The computer device may interact with the user via a keyboard, mouse, remote control, touchpad, or voice control device.

[0110] The memory 51 includes at least one type of readable storage medium, including flash memory, hard disk, multimedia card, card-type memory (e.g., SD or D slot compatibility test memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 51 can be an internal storage unit of the computer device 5, such as the hard disk or memory of the computer device 5. In other embodiments, the memory 51 can also be an external storage device of the computer device 5, such as a plug-in hard disk equipped on the computer device 5, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Of course, the memory 51 can also include both the internal storage unit of the computer device 5 and its external storage device. In this embodiment, the memory 51 is generally used to store the operating system and various application software installed on the computer device 5, such as computer-readable instructions for the slot compatibility test method. In addition, the memory 51 can also be used to temporarily store various types of data that have been output or are to be output.

[0111] In some embodiments, the processor 52 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or another intelligent signature chip. The processor 52 is typically used to control the overall operation of the computer device 5. In this embodiment, the processor 52 is used to execute computer-readable instructions or process data stored in the memory 51, such as computer-readable instructions for executing the slot compatibility testing method.

[0112] The network interface 53 may include a wireless network interface or a wired network interface. The network interface 53 is generally used to establish a communication connection between the computer device 5 and other electronic devices.

[0113] The computer device provided in this embodiment can execute the above-mentioned intelligent signature method, which can be the intelligent signature method of each of the above-mentioned embodiments.

[0114] Example 4

[0115] This embodiment also 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 intelligent signature method in the embodiment are implemented.

[0116] In this embodiment, the computer-readable storage medium includes flash memory, hard disks, multimedia cards, card-type memories (e.g., SD or DX memories), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic storage, magnetic disks, optical disks, etc. In some embodiments, the computer-readable storage medium may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk equipped with the computer device, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Of course, the computer-readable storage medium may also include both the internal storage unit of the computer device and its external storage device. In this embodiment, the computer-readable storage medium is generally used to store the operating system and various application software installed on the computer device. In addition, the computer-readable storage medium may also be used to temporarily store various types of data that have been output or are about to be output.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or flowchart, and the combination of boxes in the structure diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0118] In addition, the functional modules or units in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0119] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium can be a non-volatile storage medium or a volatile storage medium. For example, the storage medium can be: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and other media that can store program codes.

[0120] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A smart signature method, characterized in that: The method comprises: Obtain a pre-configured signature process, wherein the signature process includes an intelligent signature node; When the signature process reaches the smart signature node, the user's historical signature behavior information is obtained, and the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position; Scoring the operation type and seal type of each signature position using a preset weighted algorithm to obtain multiple scoring results, and taking the signature position with the highest scoring result as the optimal signature position at the intelligent signature node; The contract information in the process form is obtained, and the process form is signed according to the optimal signature position and the contract information.

2. The intelligent signature method according to claim 1, characterized in that: The operation types include manual operation and automatic operation, and the seal types include keyword seal, interleaving seal, page header seal, and page footer seal. The operation type and seal type of each signature position are scored using a preset weighted algorithm to obtain multiple scoring results, including: Obtaining a first preset weight for each of the operation types, and obtaining a second preset weight for each of the seal types; The first preset weight and the second preset weight of each signature position are coupled and calculated by a multiplication operator to generate a composite behavior feature value of each signature position, and the composite behavior feature value of each signature position is used as a scoring result of each signature position.

3. The intelligent signature method according to claim 2, characterized in that: After taking the composite behavior feature value of each signature position as the scoring result of each signature position, the method further includes: Based on the dimensions of the seal types, constructing an operation frequency statistical matrix of the user, wherein the operation frequency statistical matrix records the number of operations performed by the user under each seal type; Constructing a composite behavior characteristic value matrix of the user, wherein the composite behavior characteristic value matrix records the composite behavior characteristic values of the user under each of the seal types; A behavior profile of the user is constructed based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix.

4. The intelligent signature method according to claim 3, characterized in that: After constructing the user's behavior profile based on the operation frequency statistical matrix and the composite behavior eigenvalue matrix, the method further includes: Obtaining a first seal type corresponding to the number of operations exceeding a preset frequency threshold in the operation frequency statistical matrix; Obtaining a second seal type corresponding to a composite behavior feature value exceeding a preset feature value threshold among the composite behavior feature values of the first seal type; According to the second seal type, early warning information is generated.

5. The intelligent signature method according to claim 1, characterized in that: The method further comprises: Counting the occurrence frequencies of the signature positions, sorting the occurrence frequencies of the signature positions in descending order, and obtaining the signature positions corresponding to the first preset number of occurrence frequencies; A signature position template library of the user is generated according to the signature positions corresponding to the first preset number of occurrence frequencies.

6. The intelligent signature method according to claim 2, characterized in that: The method further comprises: Extracting the signature-related text from the user's historical signature behavior information, obtaining key contents related to the keyword seal from the signature-related text, and counting the word frequency and word length of each key content; Calculating the number of words contained in each key content using a space segmentation method, and training a natural language processing model based on the word frequency and word length of each key content and the number of words contained in each key content; The trained natural language processing model is used to predict the candidate signature positions at the intelligent signature node.

7. An intelligent signature device, characterized in that: The device comprises: A first acquisition module is used to acquire a pre-configured signature process, wherein the signature process includes an intelligent signature node; A second acquisition module is configured to acquire the user's historical signature behavior information when the signature process reaches the smart signature node, wherein the historical signature behavior information includes multiple signature positions and the operation type and seal type corresponding to each signature position; A scoring module is used to score the operation type and seal type of each signature position using a preset weighted algorithm to obtain multiple scoring results, and use the signature position with the highest scoring result as the optimal signature position at the smart signature node; The signature module is used to obtain the contract information in the process form and sign the process form according to the optimal signature position and the contract information.

8. The intelligent signature device according to claim 7, characterized in that: The operation types include manual operation and automatic operation, the seal types include keyword seal, interleaving seal, page header seal and page footer seal, and the scoring module also includes: An acquisition submodule, configured to acquire a first preset weight for each of the operation types and a second preset weight for each of the seal types; The calculation submodule is used to couple the first preset weight and the second preset weight of each signature position through a multiplication operator to generate a composite behavior feature value of each signature position, and use the composite behavior feature value of each signature position as the scoring result of each signature position.

9. A computer device, characterized in that: It includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the intelligent signature method according to any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the intelligent signature method according to any one of claims 1 to 6 are implemented.

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