Electronic cargo right certificate registration authentication method, system, medium, device and program

Abstract

The invention relates to the technical field of Internet, and provides an electronic cargo right certificate registration authentication method and system, a medium, equipment and a program. The electronic cargo right voucher registration authentication method comprises the steps of obtaining electronic cargo right voucher authentication information, and if the electronic cargo right voucher authentication information is correct, authenticating the electronic cargo right voucher authentication information by adopting a trained large model; wherein the large model training process comprises the following steps: carrying out preprocessing and feature extraction on acquired full-process data information of cargo right management to obtain different types of data feature sets; clustering the different types of data feature sets by adopting a clustering algorithm to obtain a clustering result; performing middle fusion processing on the clustering result to obtain a fusion feature set; and training large models of the plurality of related tasks based on the fused feature set to obtain a trained large model for cargo right authentication of the specified task. According to the invention, through a large model, authentication management of the electronic cargo right certificate is realized, and the authentication accuracy and efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a registration and authentication method, system, medium, equipment and program for an electronic title certificate. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In reality, only when the goods are actually delivered, received and possessed can their property rights be established. However, especially when financial institutions conduct business, it is difficult to set up a warehousing management company to manage the goods. In more cases, the goods are stored in a third-party warehouse, resulting in the separation of goods and rights. At this time, although the goods are kept, the protection of rights becomes a problem. Even if the seal is confirmed, it is more of a possible legal protection of the creditor's rights, and it cannot ensure that the owner of the goods can directly handle the corresponding goods.

[0004] Electronic goods title certificates provide a new and efficient way to confirm the ownership of inventory in the field of inventory trading and financing. Electronic goods title certificates can be used for transfer, pledge and other businesses, realize the efficient circulation and financing of goods, conform to legal logic, and have judicial feasibility.

[0005] The authentication of electronic cargo title certificates is carried out by training a large intelligent model. Since the cargo information recorded in the electronic cargo title certificate includes electronic data, documents, pictures, videos and other information, it is highly complex. The ordinary large model training method has certain limitations and low accuracy. It is easy to lose some information when integrating data from different sources. Summary of the invention

[0006] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a registration and authentication method, system, medium, equipment and program for an electronic certificate of title to goods. The present invention realizes the authentication management of the electronic certificate of title to goods by training a large artificial intelligence model, improves the authentication accuracy and efficiency of the electronic certificate of title to goods, and reduces the interference of human factors in the authentication process.

[0007] In order to achieve the above object, the present invention adopts the following technical solution:

[0008] The first aspect of the present invention provides a method for registering and authenticating an electronic title certificate.

[0009] A registration and authentication method for an electronic title certificate, comprising:

[0010] Obtaining electronic title certificate authentication information, if the electronic title certificate authentication information is correct, using the trained large model to authenticate the electronic title certificate authentication information;

[0011] The process of big model training includes: preprocessing and feature extraction of the acquired data information of the whole process of cargo ownership management to obtain different types of data feature sets; clustering different types of data feature sets using clustering algorithms to obtain clustering results; fusing the clustering results to obtain a fused feature set; training big models of multiple related tasks based on the fused feature set to obtain a trained big model for cargo ownership authentication of specified tasks.

[0012] Furthermore, the full-process data information of the cargo ownership management includes: due diligence information of cargo ownership, contract information, cargo specific information, transportation link information, warehousing link information, publicity information and evidence storage information, and the types of data include: contract type, voucher type, on-site record type and Internet of Things information type.

[0013] Furthermore, the method for training a large model of multiple related tasks based on the fused feature set includes:

[0014] Determine multiple tasks related to electronic title certificate authentication, including: certificate authenticity judgment task, certificate validity verification task and certificate ownership judgment task;

[0015] Create output layers for each task, use fused feature sets, and train large models for multiple related tasks;

[0016] According to the importance of tasks, different weights are assigned to the loss function of each task, and a joint loss function is constructed to optimize the large model;

[0017] According to the output results and true values ​​of the large model, the parameters of the large model are optimized to obtain the trained large model.

[0018] The second aspect of the present invention provides an electronic goods title certificate registration and authentication system.

[0019] An electronic goods title certificate registration and authentication system, characterized by comprising:

[0020] An authentication module is configured to: obtain authentication information of the electronic title certificate, and if the authentication information of the electronic title certificate is correct, use the trained large model to authenticate the authentication information of the electronic title certificate;

[0021] The process of big model training includes: preprocessing and feature extraction of the acquired data information of the whole process of cargo ownership management to obtain different types of data feature sets; clustering different types of data feature sets using clustering algorithms to obtain clustering results; fusing the clustering results to obtain a fused feature set; training big models of multiple related tasks based on the fused feature set to obtain a trained big model for cargo ownership authentication of specified tasks.

[0022] The third aspect of the present invention provides an electronic goods title certificate registration and authentication system.

[0023] An electronic goods title certificate registration and authentication system, comprising:

[0024] A receiving unit, used to receive the registration and electronic title certificate authentication information authentication application submitted by the title confirmation platform;

[0025] A confirmation unit, used to confirm the received electronic title certificate authentication information;

[0026] The authentication unit is used to authenticate the authentication information of the electronic title certificate using the trained big model; wherein the big model training process includes: preprocessing and feature extraction of the acquired full-process data information of the title management to obtain different types of data feature sets; clustering different types of data feature sets using a clustering algorithm to obtain clustering results; performing fusion processing on the clustering results to obtain a fusion feature set; training big models of multiple related tasks based on the fusion feature set to obtain a trained big model for the title authentication of the specified task;

[0027] The sending unit is used to send the authentication structure to the user end.

[0028] Furthermore, the system also includes: a monitoring unit, which is used to monitor the IoT data of the goods in real time through the connected IoT devices, set thresholds for the IoT data of the goods according to the commodity category electronic title certificate confirmation service specifications, and perform intelligent analysis through the artificial intelligence big model. When the threshold is exceeded, an early warning notification will be initiated. At the same time, the image and video information collected by the IoT devices will be intelligently identified. When human intrusion, cargo changes, and warehousing conditions are identified, timely early warnings will be issued for any damage to the goods.

[0029] Furthermore, the confirmation unit is also used to, if the authentication information of the electronic title certificate is incorrect, the user end will feedback the correct information to the title confirmation service platform through the electronic title certificate registration and authentication system, and the title confirmation service platform will correct the information and then initiate the authentication application again; if the information is correct, the information will be confirmed through the electronic title certificate registration and authentication system.

[0030] A fourth aspect of the present invention provides a computer-readable storage medium.

[0031] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the electronic goods title certificate registration and authentication method as described in the first aspect above.

[0032] A fifth aspect of the present invention provides a computer device.

[0033] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the registration and authentication method for electronic title certificates as described in the first aspect above are implemented.

[0034] A sixth aspect of the present invention provides a computer device.

[0035] The present invention provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the electronic goods title certificate registration and authentication method as described in the first aspect above.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention proposes a registration and authentication method for an electronic certificate of title to goods. By registering an electronic certificate of title to goods and adopting the technology of intelligent big model, all information related to the title confirmation of goods recorded under the electronic certificate of title to goods is intelligently authenticated, so that the authenticated electronic certificate of title to goods can comply with the title confirmation links stipulated in the title confirmation service specification of the electronic certificate of title to goods of a specific commodity category, thereby ensuring the effective title confirmation of goods and being able to represent the holder's ownership or security interest in the goods from a legal perspective.

[0038] The present invention applies the big model to the electronic title certificate registration and authentication system to realize automated authentication and review, which can automatically process a large number of electronic title certificates, reduce the time and workload of manual review, quickly respond to authentication needs, and improve the efficiency of the overall business process.

[0039] The big model described in the present invention can more accurately identify key information and potential problems in the certificate by learning a large amount of data, and reduce audit errors and omissions caused by human factors; the application of the big model can significantly improve the automation level of the electronic title certificate registration and authentication system, enhance the efficiency and quality of business operations, and provide enterprises with powerful data analysis and decision support tools.

[0040] The present invention adopts a data fusion method through multi-instructional training and midfusion to avoid the loss of some information in the data fusion process, which can more comprehensively understand the content of the title confirmation service specification and improve the accuracy of the electronic title certificate authentication. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0042] Figure 1 It is a framework diagram of the electronic goods title certificate registration and authentication method shown in the present invention. DETAILED DESCRIPTION

[0043] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0044] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0045] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0046] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the methods and systems according to various embodiments of the present disclosure. It should be noted that each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of a code may include one or more executable instructions for implementing the logical functions specified in each embodiment. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the flowchart and / or block diagram, and the combination of boxes in the flowchart and / or block diagram can be implemented using a dedicated hardware-based system that performs a specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0047] Explanation of terms: An electronic title certificate is a written document that expresses the contents in the form of a data message and meets the requirements of laws and regulations. It gives the holder the right to receive, possess and dispose of the document and the goods stated in it. The electronic title certificate records the rights of the issuer and the holder to the goods under the electronic title certificate, including but not limited to the ownership, possession, disposal and pledge of the goods. The electronic title certificate is a digital representation of the title to the goods, and proves the holder's ownership / pledge of the goods through complete title management data.

[0048] Embodiment 1

[0049] This embodiment provides a registration and authentication method for an electronic title certificate, which defines the electronic title certificate, relevant provisions of the electronic title certificate, and usage specifications of the electronic title certificate by establishing a set of management specifications for the electronic title certificate system. Formulate access specifications for each participant in the electronic title certificate system. Formulate service specifications for confirmation of electronic title certificates for different categories of goods. By establishing a set of service specifications for confirmation of electronic title certificates, the present invention enables electronic title certificates that are managed in accordance with the confirmation service specifications to be effectively confirmed and complete the authentication of the electronic title certificate.

[0050] like Figure 1 As shown, the registration and authentication method of the electronic title certificate described in this embodiment is described in detail below:

[0051] Step (1) User account creation: Enterprises applying to join the electronic title certificate system are evaluated in accordance with the requirements of the access specifications for each role of the electronic title certificate. Users who pass the evaluation sign the relevant business agreement, and the system operation and management party establishes account information for each user in the system operation background. After the account information is established, each user will obtain a unique account key. When the user subsequently uses the electronic title certificate management system to perform various businesses, the account key must be used for identity verification.

[0052] Step (2) Access to the title confirmation service platform: After the title confirmation service platform enterprise passes the role access application, it activates the system user and connects with the electronic title certificate registration and authentication system through a standard interface. The electronic title certificate management system provides the following standard service interfaces: electronic title certificate registration interface, electronic title certificate update interface, and electronic title certificate authentication application interface.

[0053] Step (3) Registration / update of electronic goods title certificate: the title confirmation service agency shall manage the goods title of the goods in the whole process according to the requirements specified in the electronic goods title confirmation service specification of the goods in the category, form an electronic record, and transmit it to the title confirmation service platform. The applicant shall initiate the registration or update application of the electronic goods title certificate through the title confirmation service platform, and send the following information to the electronic goods title certificate registration and authentication system through the interface: right holder information, contract information (sales contract, logistics contract, warehousing contract, etc.), goods information (name, type, specification / model, quantity, etc.), warehousing information (warehousing enterprise information, warehouse information, storage location, etc.), logistics / transportation information (logistics information), service agency information and other supplementary information. After receiving the electronic goods title certificate information, the electronic goods title certificate registration and authentication system generates a unique registration code.

[0054] Step (4) Electronic title certificate authentication:

[0055] Step (41): The title confirmation service platform initiates a certification application to the electronic title certificate registration and certification system through the electronic title certificate certification application interface. According to the electronic title certificate title confirmation service specification for the category of goods, the following information needs to be uploaded to the electronic title certificate registration and certification system: electronic title certificate business type (update, transfer, pledge, cancellation), right holder information, contract information (sales contract, logistics contract, warehousing contract, etc.), goods information (name, type, specification / model, quantity, etc.), warehousing information (warehousing enterprise information, warehouse information, storage location, etc.), logistics / transportation information (logistics information), title confirmation management process information (due diligence, specification, delivery, control / possession, publicity), service agency information and other supplementary information.

[0056] Step (42): The warehouse where the goods are stored is connected to the IoT device, and the device is associated with the goods corresponding to the electronic goods certificate applied for authentication, that is, the IoT information of the relevant goods can be obtained through the IoT device. The IoT device includes but is not limited to: monitors, sensors, electronic fences, OCR devices, FRID devices and robot devices.

[0057] Step (43): The actual controller of the goods obtains the electronic goods certificate authentication information through the electronic goods certificate authentication and registration system, and confirms the authenticity of the above information. If the information is incorrect, the actual controller of the goods can feedback the correct information to the title confirmation service platform through the electronic goods certificate registration and authentication system, and the title confirmation service platform will correct the information and initiate the authentication application again; if the information is correct, the information can be confirmed through the electronic goods certificate registration and authentication system.

[0058] Step (44): After completing the information confirmation, the electronic title certificate registration and authentication system authenticates the electronic title certificate through the intelligent big model.

[0059] Step (45): After the authentication is completed, the authenticated electronic title certificate is returned to the title confirmation service platform.

[0060] Step (46): Synchronously update the public information of the electronic title certificate and display the certification pass mark on the public page.

[0061] Step (5) Update the authenticated electronic title certificate information:

[0062] Step (51): According to the commodity category electronic title certificate confirmation service specification, the authenticated electronic title certificate needs to be updated regularly.

[0063] Step (52): The electronic cargo ownership certificate registration and authentication system periodically obtains data generated by the full process of cargo ownership management recorded by the title confirmation service platform;

[0064] Step (53): The IoT data of the goods is monitored in real time through the connected IoT devices. According to the commodity category electronic goods ownership certificate confirmation service specification, corresponding thresholds are set for the information obtained by the IoT devices, such as temperature, humidity, and gas concentration. Intelligent analysis is performed through the artificial intelligence big model. When the threshold is exceeded, an early warning notification is initiated. At the same time, the images, videos and other information collected by the IoT devices are intelligently identified. When the intrusion of people, the change of goods, the entry and exit of the warehouse, etc. are identified, timely early warnings are issued for the infringement of the goods.

[0065] Step (54): The actual controller of the goods obtains the electronic goods certificate authentication information through the electronic goods certificate authentication and registration system, and confirms the authenticity of the above information. If the information is incorrect, the actual controller of the goods can feedback the correct information to the title confirmation service platform through the electronic goods certificate registration and authentication system, and the title confirmation service platform will correct the information and initiate the authentication application again; if the information is correct, the information can be confirmed through the electronic goods certificate registration and authentication system.

[0066] Step (55): After completing the information confirmation, the electronic title certificate registration and authentication system authenticates the electronic title certificate through the intelligent big model.

[0067] Step (56): After the authentication is completed, the authenticated electronic title certificate is returned to the title confirmation service platform.

[0068] Step (57): Synchronously update the public information of the electronic title certificate.

[0069] Step (6) Registration and Publicity of Electronic Title Certificate:

[0070] Step (61): After the electronic title certificate is registered, it will be automatically registered and publicized in the registration and publicity module of the electronic title certificate registration and authentication system.

[0071] Step (62): Each time the certification review is passed, the public information and status of the electronic title certificate are synchronized in a timely manner.

[0072] The present invention reduces the risk of sensitive information being exposed during manual processing through automated auditing, can integrate security mechanisms such as anomaly detection to prevent fraud and illegal behavior, and can reduce labor costs and additional correction costs caused by manual errors. It ensures the consistency of audit standards and processes, improves the predictability of audit results, and avoids inconsistencies caused by subjective judgments through standardized audit processes.

[0073] Step (63): The publicly displayed electronic goods title certificate information is as follows: right holder information, contract information (sales contract, logistics contract, warehousing contract, etc.), goods information (name, type, specification / model, quantity, etc.), warehousing information (warehousing enterprise information, warehouse information, storage location, etc.), logistics / transportation information (logistics information), service agency information, other information and electronic goods title certificate status.

[0074] Step (64): An authorized viewing mechanism is used for commercially sensitive information in the public announcement. The inquirer can initiate an authorized viewing application to the current holder of the electronic title certificate. After the application is approved, the inquirer can see the content that needs to be authorized to view.

[0075] Step (7) Large model for electronic goods title certificate authentication: The present invention uses artificial intelligence large model technology to authenticate electronic goods title certificates to improve the audit efficiency and avoid the problem of erroneous authentication caused by subjective factors and erroneous operations in manual audits.

[0076] Step (71): Obtain data information on the entire process of cargo ownership management, including due diligence information on cargo ownership, contract information, cargo specific information, transportation link information, warehousing link information, public information, and evidence storage information.

[0077] The specific process includes: collecting data on goods ownership management from warehouse management companies, inventory management companies, financial institutions and law firms that rank high in the field of warehouse financing. The data is representative of the industry, has operational specifications, complies with legal provisions, and has legal characteristics. The data includes the following categories:

[0078] Contracts: warehousing contracts, loan contracts, pledge contracts, mortgage contracts, etc.;

[0079] Vouchers: orders, bills of lading, health certificates, invoices, payment vouchers, warehouse entry and exit lists, inventory lists, transportation documents, etc.

[0080] On-site records: including business due diligence process, transportation process, warehousing business process, etc.;

[0081] Internet of Things information: including monitoring images, cargo counting, cargo identification and other information.

[0082] Step (72): pre-process the data, including document processing, image processing, video processing and IoT data.

[0083] The specific process includes: preprocessing the data and processing the data into standardized data.

[0084] For contract and voucher data, their file formats are uniformly processed into PDF format, which supports the recognition of specific content and extracts key content in contracts and vouchers, such as the signatories of the contract, the terms in the contract that specify the goods, the terms on the delivery of goods, and the contract period, etc. The voucher class identifies the goods information, related company information, storage address information, transportation company information, entry and exit time, goods quantity information, etc., and uses NLTK technology to segment the extracted text, filter out stop words, and convert the text into a numerical vector.

[0085] For field records and IoT information, the data is in image format. The image size is standardized to meet the input requirements of the model. The image is rotated, scaled, flipped, and brightness adjusted to increase data diversity and reduce overfitting. The image pixel value is scaled from [0,255] to [0,1] or [-1,1] to facilitate model processing.

[0086] Step (73): Extract features from the pre-processed data based on the link of goods title confirmation, data type, evidence description, on-site record description, document description and other information in goods title management, and then cluster all features to obtain features that are helpful for electronic goods title certificate authentication.

[0087] The specific process includes: firstly, constructing a feature library of electronic goods certificate authentication information, whose feature library rules come from the electronic goods certificate confirmation service specification, processing the rules and converting them into machine-understandable rules. And then, training a feature extraction model to automatically extract features from the above pre-processed data.

[0088] Step (731): The feature extraction model adopts the existing deep learning model and the clustering algorithm K-means++, as follows:

[0089] Step (7311): Initialization: When performing unsupervised model training, select K initial centroids, which can be points in the data set or randomly selected points. K-means++ is an improved initialization method that selects initial centroids through probability distribution to speed up convergence.

[0090] Step (7312): Assign data points; for each point in the data set, calculate its distance from all K centroids and assign it to the nearest centroid, thereby forming K clusters.

[0091] Step (7313): Update the centroid; once all data points are assigned to clusters, recalculate the centroid of each cluster, that is, calculate the mean of all points in each cluster and use it as the new centroid.

[0092] Step (7314): Repeat the iteration; repeat step (7312) and step (7313) until the position of the center of mass no longer changes, or the predetermined number of iterations is reached.

[0093] Step (7315): Evaluate the results: Use methods such as silhouette coefficient and elbow rule to evaluate the clustering effect. The silhouette coefficient measures the quality of clustering, while the elbow rule determines the optimal K value by observing how the total inner square sum (SSE) changes with the K value.

[0094] Step (7316): Explain and visualize the clustering results to understand the structure and pattern of the data. Through training and learning a large amount of text and image data, the characteristic information of the contract, document voucher, on-site record and IoT data in the electronic goods title certificate authentication information is obtained.

[0095] Step (732): feature information optimization processing, feature processing is performed on the pre-processed data through a feature extraction model, and the extracted feature information is corrected by professionals, for example, marking key contract terms, important cargo data in documents and vouchers, and using bounding boxes in images to mark key features such as staff, cargo, warehouses, operating equipment, etc.

[0096] Step (74): Mid Fusion of Feature Information: Mid fusion of feature information is performed based on the clustering results, and data of different modalities are fused at the feature level to obtain richer information.

[0097] The specific process includes: combining the feature vectors of different modalities after clustering through the mid-fusion data fusion strategy. Mid-fusion aims to balance the information retention and fusion efficiency by fusing at the feature layer rather than the original data layer. This method allows the most informative features extracted from each modality to be integrated together, while avoiding the problem of information loss that may occur in early fusion. The weighted average strategy is adopted in the example of the present invention. According to the impact of each link on the title confirmation service in the electronic title certificate title confirmation service specification, different weighted values ​​are assigned to the feature vectors of different links, thereby constructing a feature library to associate text information and image files with corresponding feature information.

[0098] Step (75): Define tasks related to certification for multi-instructional training. Train the model through multiple related tasks to improve the generalization ability of the model.

[0099] The specific process includes: implementing multi-instructional training, designing a model that can handle multiple related tasks at the same time, so as to enhance the model's generalization and adaptability to different certification tasks. The following are the specific implementation steps of multi-instructional training:

[0100] Step (751) defines related tasks: determines multiple tasks related to the authentication of the electronic title certificate. These tasks include:

[0101] Task 1: Verification of the authenticity of the certificate (authenticity classification).

[0102] Task 2: Credential validity verification (valid / invalid classification).

[0103] Task 3: Determine the ownership of the certificate (identify the owner).

[0104] Step (752) Dataset preparation: Classify the feature information obtained in step 4 for each task. For example:

[0105] For the authenticity judgment task, contracts, vouchers and their authenticity labels are collected.

[0106] For validation tasks, collect credential status information.

[0107] For the attribution judgment task, collect the attribution information of the voucher.

[0108] Step (753): Create a dedicated output layer or a series of output layers for each different task, which are responsible for making the final prediction or decision from the extracted feature representations.

[0109] Step (754): Model training, using data from all tasks to train the model simultaneously. This can be achieved by:

[0110] Joint training: In each training iteration, a batch of data is randomly extracted from each task and input into the model together, and the output of the model is calculated according to the loss function of each task.

[0111] Loss function weighting: Depending on the different importance of tasks, they can be balanced by assigning different weights to the loss function of each task. The model evaluates the difference between the predicted results and the actual labels by calculating the loss function (e.g., cross entropy loss) and backpropagates these losses to update the network weights.

[0112] Step (755) Optimization strategy: Select an appropriate optimization algorithm (such as Adam or SGD) to update the weights of the model. Use techniques such as learning rate decay and early stopping to prevent overfitting.

[0113] Step (756) Model evaluation: Use the validation set to evaluate the performance of the model on each task. Monitor the performance of different tasks to ensure that the model is not biased towards a specific task.

[0114] Step (757): Adjust and optimize: Adjust the model architecture or training strategy based on the evaluation results. Possible adjustments include: adjusting the network structure of task-specific layers, balancing the loss weights of different tasks, adjusting the learning rate and other hyperparameters.

[0115] Step (758): Iterative improvement: Iteratively improve the model until the performance of all tasks reaches a satisfactory level.

[0116] Step (759): Deployment and monitoring: Deploy the trained model to the actual authentication system and continuously monitor its performance.

[0117] Through this multi-instruction training method, the model can learn richer feature representations and improve the accuracy and robustness of electronic title certificate authentication tasks.

[0118] Step (76): Train a large model based on the above data and tasks to obtain an electronic title certificate authentication large model for use in the authentication of electronic title certificates.

[0119] Step (77): The commodity category electronic title certificate confirmation service specification stipulates the title management links that the title management data should include and the relevant elements of each link.

[0120] The large model described in the present invention can be continuously optimized through continuous learning to adapt to new voucher formats and audit requirements, and the model can be easily updated to cope with regulatory changes or adjustments to business needs.

[0121] Embodiment 2

[0122] This embodiment provides a registration and authentication system for an electronic title certificate.

[0123] An electronic goods title certificate registration and authentication system, comprising:

[0124] An authentication module is configured to: obtain authentication information of the electronic title certificate, and if the authentication information of the electronic title certificate is correct, use the trained large model to authenticate the authentication information of the electronic title certificate;

[0125] The process of big model training includes: preprocessing and feature extraction of the acquired data information of the whole process of cargo ownership management to obtain different types of data feature sets; clustering different types of data feature sets using clustering algorithms to obtain clustering results; fusing the clustering results to obtain a fused feature set; training big models of multiple related tasks based on the fused feature set to obtain a trained big model for cargo ownership authentication of specified tasks.

[0126] Among them, the full-process data information of the cargo ownership management includes: due diligence information of cargo ownership, contract information, cargo specific information, transportation link information, warehousing link information, public information and evidence information. The types of data include: contract type, voucher type, on-site record type and Internet of Things information type.

[0127] In some embodiments, the method of training a large model for multiple related tasks based on a fused feature set includes:

[0128] Determine multiple tasks related to electronic title certificate authentication, including: certificate authenticity judgment task, certificate validity verification task and certificate ownership judgment task;

[0129] Create output layers for each task, use fused feature sets, and train large models for multiple related tasks;

[0130] According to the importance of tasks, different weights are assigned to the loss function of each task, and a joint loss function is constructed to optimize the large model;

[0131] According to the output results and true values ​​of the large model, the parameters of the large model are optimized to obtain the trained large model.

[0132] The invention provides a fast audit process to improve customer satisfaction. Customers can track the audit status in real time and improve transparency. It provides real-time data analysis and reporting to help management make more informed business decisions. It provides data support for business strategies through the prediction and analysis functions of the model. It ensures that the audit process complies with industry standards and regulatory requirements, and reduces compliance risks through automated processes.

[0133] Embodiment 3

[0134] This embodiment provides an electronic goods title certificate registration and authentication system, including:

[0135] An electronic goods title certificate registration and authentication system, characterized by comprising:

[0136] A receiving unit, used to receive the registration and electronic title certificate authentication information authentication application submitted by the title confirmation platform;

[0137] A confirmation unit, used to confirm the received electronic title certificate authentication information;

[0138] The authentication unit is used to authenticate the authentication information of the electronic title certificate using the trained big model; wherein the big model training process includes: preprocessing and feature extraction of the acquired full-process data information of the title management to obtain different types of data feature sets; clustering different types of data feature sets using a clustering algorithm to obtain clustering results; performing fusion processing on the clustering results to obtain a fusion feature set; training big models of multiple related tasks based on the fusion feature set to obtain a trained big model for the title authentication of the specified task;

[0139] The sending unit is used to send the authentication structure to the user end.

[0140] In some embodiments, the system also includes: a monitoring unit, which is used to monitor the IoT data of the goods in real time through the connected IoT devices, set a threshold for the IoT data of the goods according to the commodity category electronic title certificate confirmation service specification, and perform intelligent analysis through an artificial intelligence big model. When the threshold is exceeded, an early warning notification will be initiated. At the same time, the image and video information collected by the IoT devices will be intelligently identified. When human intrusion, cargo changes, and warehousing situations are identified, timely early warnings will be issued if there is any damage to the goods.

[0141] In some embodiments, the confirmation unit is also used to, if the authentication information of the electronic title certificate is incorrect, then the user terminal will feedback the correct information to the title confirmation service platform through the electronic title certificate registration and authentication system, and the title confirmation service platform will correct the information and then initiate the authentication application again; if the information is correct, the information will be confirmed through the electronic title certificate registration and authentication system.

[0142] After receiving the authentication, the electronic cargo title certificate will receive various business operations (transfer, pledge, update, cancellation, etc.) and full-process cargo title management data during its validity period; the information of the registered and authenticated electronic cargo title certificate will be publicized.

[0143] The system can be easily expanded to adapt to business growth or changes without significantly increasing human resources, and can be integrated into the existing IT architecture and work in conjunction with other systems.

[0144] Embodiment 4

[0145] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in the electronic goods title certificate registration and authentication method as described in the above-mentioned embodiment 1 are implemented.

[0146] Embodiment 5

[0147] This embodiment 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 program, the steps in the registration and authentication method for electronic title certificates as described in the first embodiment above are implemented.

[0148] Embodiment 6

[0149] This embodiment provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the above-mentioned electronic title certificate registration and authentication method.

[0150] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0151] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0152] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0154] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0155] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A registration and authentication method for an electronic title certificate, characterized in that: include: Obtaining electronic title certificate authentication information, if the electronic title certificate authentication information is correct, using the trained large model to authenticate the electronic title certificate authentication information; The process of big model training includes: preprocessing and feature extraction of the acquired data information of the whole process of cargo ownership management to obtain different types of data feature sets; clustering different types of data feature sets using clustering algorithms to obtain clustering results; fusing the clustering results to obtain a fused feature set; training big models of multiple related tasks based on the fused feature set to obtain a trained big model for cargo ownership authentication of specified tasks.

2. The electronic goods title certificate registration and authentication method according to claim 1, characterized in that: The full-process data information of the cargo ownership management includes: due diligence information of cargo ownership, contract information, cargo specific information, transportation link information, warehousing link information, public information and evidence information. The types of data include: contract type, voucher type, on-site record type and Internet of Things information type.

3. The electronic goods title certificate registration and authentication method according to claim 1, characterized in that: The method for training a large model of multiple related tasks based on a fused feature set includes: Determine multiple tasks related to electronic title certificate authentication, including: certificate authenticity judgment task, certificate validity verification task and certificate ownership judgment task; Create output layers for each task, use fused feature sets, and train large models for multiple related tasks; According to the importance of tasks, different weights are assigned to the loss function of each task, and a joint loss function is constructed to optimize the large model; According to the output results and true values ​​of the large model, the parameters of the large model are optimized to obtain the trained large model.

4. The electronic title certificate registration and authentication system is characterized by: include: An authentication module is configured to: obtain authentication information of the electronic title certificate, and if the authentication information of the electronic title certificate is correct, use the trained large model to authenticate the authentication information of the electronic title certificate; The process of big model training includes: preprocessing and feature extraction of the acquired data information of the whole process of cargo ownership management to obtain different types of data feature sets; clustering different types of data feature sets using clustering algorithms to obtain clustering results; fusing the clustering results to obtain a fused feature set; training big models of multiple related tasks based on the fused feature set to obtain a trained big model for cargo ownership authentication of specified tasks.

5. The electronic title certificate registration and authentication system is characterized by: include: A receiving unit, used to receive the registration and electronic title certificate authentication information authentication application submitted by the title confirmation platform; A confirmation unit, used to confirm the received electronic title certificate authentication information; The authentication unit is used to authenticate the authentication information of the electronic title certificate using the trained big model; wherein the big model training process includes: preprocessing and feature extraction of the acquired full-process data information of the title management to obtain different types of data feature sets; clustering different types of data feature sets using a clustering algorithm to obtain clustering results; performing fusion processing on the clustering results to obtain a fusion feature set; training big models of multiple related tasks based on the fusion feature set to obtain a trained big model for the title authentication of the specified task; The sending unit is used to send the authentication structure to the user end.

6. The electronic goods title certificate registration and authentication system according to claim 5 is characterized in that: The system also includes: a monitoring unit, which is used to monitor the IoT data of goods in real time through connected IoT devices, set thresholds for the IoT data of goods according to the commodity category electronic title certificate confirmation service specifications, and perform intelligent analysis through an artificial intelligence big model. When the threshold is exceeded, an early warning notification will be initiated. At the same time, the image and video information collected by the IoT devices will be intelligently identified. When human intrusion, cargo changes, and warehousing situations are identified, timely early warnings will be issued if there is any damage to the goods.

7. The electronic goods title certificate registration and authentication system according to claim 5 is characterized in that: The confirmation unit is also used for, if the authentication information of the electronic title certificate is incorrect, the user terminal feeds back the correct information to the title confirmation service platform through the electronic title certificate registration and authentication system, and the title confirmation service platform corrects the information and initiates the authentication application again; If the information is correct, it will be confirmed through the electronic title certificate registration and authentication system.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the electronic goods title certificate registration and authentication method as described in any one of claims 1-3 are implemented.

9. 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 program, the steps in the electronic goods title certificate registration and authentication method as described in any one of claims 1-3 are implemented.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps in the electronic title certificate registration and authentication method as described in any one of claims 1-3.

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