229 results about "Intellectual property" patented technology

The invention relates to the technical field of deep learning, and discloses an intelligent consultation response system and method based on deep learning, and the system comprises a data acquisition module, a feature extraction module, a feature fusion module, a relevance calculation module, an infringement probability generation module, a clause screening module, and a reply generation module. The intellectual property consulting module is used for obtaining intellectual property consulting questions and legal texts of a user, generating a key clause set of the legal texts according to a multi-scale text convolution kernel and a multi-head attention mechanism, calculating semantic relevance between the intellectual property consulting questions and key clauses, constructing a knowledge graph of the key clauses, and displaying the knowledge graph. Performing multi-hop reasoning on the knowledge graph based on a graph neural network to obtain an infringement probability score, performing clause screening on the key clause set based on the infringement probability score and semantic relevance to obtain screened clauses, and generating a structured standard reply of the question according to the legal potency level of the screened clauses, and the response efficiency of the intellectual property consultation problem is improved.

The present invention introduces a dual-chain property management system that integrates blockchain-based tokens with off-chain government and institutional property records to provide secure, verifiable, and legally recognized asset transactions. Unlike existing blockchain-based property solutions, this system prevents unauthorized tokenization, enforces compliance with jurisdictional property laws, and synchronizes title records dynamically. A concurrency management module eliminates double-minting risks, while a discrepancy resolution engine continuously detects and corrects mismatches between blockchain and legal registries. Smart contracts automate ownership transfers, lease agreements, lien tracking, and compliance enforcement, ensuring fraud-resistant transactions in real estate, vehicles, intellectual property, luxury goods, and financial instruments. This innovation enables legally binding digital property transfers with real-time regulatory oversight, bridging the gap between decentralized asset tokenization and traditional legal frameworks. By automating verification, synchronization, and compliance, the system creates a scalable, transparent, and jurisdictionally compliant property management ecosystem.

The invention provides an intelligence information integration method and device based on a multi-agent task chain strategy large model, and the method comprises the steps: collecting a plurality of pieces of open-source dynamic science and technology intelligence information of a target information source, and employing a literature analysis agent, an abstract induction agent, a content generation agent, a sequencing agent and a report generation agent which are constructed through a large language model; key information extraction, semantic analysis and induction, content evaluation and updating, information sequencing and version change recording and report generation are performed respectively, and automatic aggregation and sequencing of intelligence information are realized. According to the method, the defects of generalization, objectivity, cross-document information processing, flexibility, robustness, illusion rate, extrapolation ability, small sample learning ability and the like in intelligence information integration in the prior art are effectively overcome, the efficiency and effect of intelligence work are improved, and the intellectual property is improved. The method is of great significance in enhancing the service quality benefit of dynamic intelligence information and supporting strategic decision and policy making.

The invention relates to the technical field of artificial intelligence, in particular to a federated learning model property protection method based on quantum coding and lattice passwords. The method comprises the steps that firstly, an initial global model is distributed, and quantum watermark generation and embedding are carried out on the basis of the initial global model in combination with lattice password quantum state coding and an information theory; then, generating corresponding quantum fingerprints based on the initial global model embedded with the watermark, aggregating the quantum fingerprints by adopting a multi-key homomorphic encryption method to obtain global aggregated fingerprints, and recording corresponding identity information in a DAG account book; and finally, receiving verification information, and performing model ownership affiliation verification based on the verification information and the identity information in combination with a zero-knowledge proof protocol based on a lattice difficulty problem. The watermark is encrypted by an LWE instance, and any calculation behavior trying to remove the watermark is equivalent to solving a difficult LWE problem, which is not feasible in calculation. Excellent performance is achieved by adopting an advanced lattice cryptographic algorithm.

A system and method for collaborative creation and management of intellectual property (IP) projects is disclosed. The system includes a server configured to dynamically assign roles and permissions to participants based on predefined criteria. A graphical user interface (GUI) facilitates real-time collaboration, editing, and version control, while a semantic analysis engine ensures compliance with intellectual property standards and assesses content novelty. Predictive analytics generate metrics, such as patentability scores and inventorship overlap, to guide project development. Contributions are electronically tracked and stored in a secure, non-transitory computer-readable medium alongside generated metrics. The system supports role-specific recommendations, automated notifications, and integration with external data sources for enhanced functionality. Participants can visualize contributions, resolve conflicts, and simulate commercialization outcomes, enabling efficient project management and innovation. This invention improves the collaborative development process, ensuring compliance, enhancing productivity, and maximizing the value of intellectual property assets.

The invention discloses a concept erasing method and system based on a T2I autoregressive visual generative model, and belongs to the technical field of intellectual property, personal privacy protection and machine learning. The method comprises the following steps: (1) positioning a causal key layer of a target concept through causal inference, including noise-free operation, noise addition operation and recovery operation, recovering an intermediate activation value of a specific layer under a noise addition condition in the recovery operation as an intermediate activation value under a noise-free condition, and determining the causal key layer according to CLIP score change of a generated image and the target concept; and (2) modifying parameters of the causal key layer based on knowledge editing to erase the generation capability of the target concept while minimizing the influence on other concepts. According to the method, the target concept representation in the model parameters can be accurately positioned, the performance influence on other functions of the model is minimized while the target concept generation capability is completely eliminated, and the requirements of intellectual property and personal privacy protection are met.

The invention belongs to the technical field of project management, and particularly relates to a scientific research project full-process management platform. Comprising a scientific research project management cockpit module, a scientific research project library management module, a scientific research project execution management module, a scientific research project document management module, a scientific research project budget management module, an intellectual property library management module, a scientific and technological achievement library management module, a scientific research project report management module and a scientific research project billboard module. The beneficial effects of the invention are that the system achieves the higher refined management requirements of scientific and technological innovation through an informatization means, and solves the problems of project dispersion, repeated research and development, and project and talent cultivation. And the obvious defects of thin base, late starting and insufficient professional degree in scientific and technological innovation management of production enterprises and research and development institutions for energy power generation are overcome.

The invention discloses a Bayesian-based two-stage deep regression model copyright protection method, which comprises the steps of 1, constructing and training a dropout layer-based watermark model, 2, acquiring a public model and a suspicious model, 3, selecting a key sample, 4, constructing a Bayesian network-based likelihood estimation model, 5, selecting a Bayesian network-based likelihood estimation model, 6, selecting a Bayesian network-based likelihood estimation model, and 7, selecting a Bayesian network-based likelihood estimation model. 5, calculating the infringement probability of the suspicious model by using a likelihood estimation model based on the Bayesian network; and 6, calculating the KL divergence between the suspicious model and the output of the watermark model so as to judge whether the suspicious model infringers or not. When copyright of the regression model is stolen, irrelevant models can be preliminarily excluded in the first stage, and whether the suspicious model is the pirated model or not is further judged in the second stage, so that the pirated model can be quickly identified, and intellectual property of the pirated model is protected from being infringed.

The invention relates to a science and technology project evaluation method and system, and relates to the technical field of multi-index decision and intelligent modeling. Comprising the steps of collecting multi-dimensional data of finance, intellectual property, teams, historical projects and the like of science and technology projects; constructing an evaluation index system; constructing a cognitive map by taking the indexes as nodes and combining statistical correlation and expert rules; a graph attention network (GAT) is utilized to train the graph, and structural causal weights among indexes are extracted; fusing the structure weight and the original fuzzy relation matrix to form a structure enhanced fuzzy relation matrix; and in combination with a weight vector determined by a fuzzy analytic hierarchy process (FAHP), performing fuzzy weighted comprehensive evaluation, and outputting a project grade and an interpretable result. According to the method, the accuracy, self-adaptability and interpretability of science and technology project evaluation are effectively improved, and the method is suitable for complex project evaluation tasks in a multi-source heterogeneous data environment.

The invention relates to the technical field of data processing, and discloses an intellectual property information analysis and matching system based on big data, comprising: an acquisition unit acquiring user demands and a historical demand set, performing semantic analysis on the user demands to extract demand keywords, and determining importance; sequencing the demand keywords according to the importance to form a current keyword group; the judgment unit is used for comparing the keyword group with a historical demand set and judging whether a historical matching catalog is taken or not; when the historical matching catalogue is judged to be used, determining a current matching catalogue according to the historical matching catalogue and the current keyword group; when it is judged that the historical matching catalogue is not used, determining a current matching catalogue according to the current keyword group; the processing unit performs clustering analysis on the matching catalog to determine a matching display result; and the storage unit stores the current keyword group and the matched display result. According to the invention, the matching efficiency and accuracy are improved, and the problems of low efficiency, low accuracy and the like in traditional intellectual property matching are solved.

The invention discloses a model anti-attack robustness evaluation method and system in a black box scene, and belongs to the field of anti-attack and artificial intelligence intellectual property protection analysis. Comprising the steps of obtaining an access permission of a target model in a black box scene, and defining a substitution model having the same function as the target model; obtaining a label-free original image sample consistent with target model data distribution, and taking the label-free original image sample as an initialized confrontation sample; optimizing the adversarial sample by using the substitution model; and inputting the original image sample and the final adversarial sample after iteration into the target model, and calculating a robustness evaluation score and a security level of the target model. According to the method for generating the adversarial sample, the intermediate feature of the substitution model is used as an optimization target, the adversarial sample is optimized to generate a more robust adversarial feature so as to enhance the adversarial mobility of the adversarial sample, and the method does not need to obtain a model label of the sample. Quantitative evaluation of the model anti-attack robustness is realized on the basis of taking the anti-attack feature robustness as a model security evaluation index.

The invention relates to the technical field of block chains, in particular to an intellectual property transaction traceability information storage method and system based on a block chain, and the method comprises the following steps: S10, collecting information recorded in an intellectual property full life cycle, and integrating the information into intellectual property full life cycle traceability information through a PROV model; s20, packaging the traceability information into an intelligent contract; and S30, verifying the packaged traceability information based on the threshold signature added with the timestamp. According to the method, the PROV model and the threshold signature are deeply fused, so that the integrity and verifiability of each operation step are ensured, sensitive operation must be authorized by a legal program, and the risk of centralized storage of key data is avoided through distributed key management. The technology coupling not only strengthens the non-repudiation of the traceability data, but also realizes hierarchical authorization control through a dynamic threshold strategy, and obtains balance between safety and efficiency.

A brand protection tool for managing risk to a brand is disclosed. The brand protection tool may provide a survey to a user. The survey may include a plurality of questions related to intellectual property. Based at least in part on the survey responses, the brand protection tool may determine a risk score, a protection score, and a net protection score. The brand protection tool may automatically generate a report including the net protection score and a visualization including a representation of the risk score and protection score. The brand protection tool may provide the report to a user or downstream system.

The present invention discloses a method for software bidding settlement review, including a function review module, a function point code decomposition module, a compliance module, a security module, an economic review module, and an open source code management module. The method for software bidding settlement review of the present invention compliantly references open source code, utilizes standard development function points, saves the development cycle and development costs, greatly saves social resources, makes the cost formula of code development, and at the same time avoids security and intellectual property infringement disputes brought by open source code.

The invention discloses a project and intellectual property achievement association evaluation method and system, and relates to the technical field of evaluation methods, and the method comprises the following steps: S1, data acquisition: obtaining project data, intellectual property achievement data and product data; s2, association model construction: constructing a project-intellectual property achievement-product association model based on the project data, the intellectual property achievement data and the product data; s3, matching degree calculation: calculating a multi-dimensional matching degree between the project and the intellectual property achievement based on the association model; s4, performing dynamic correction; and S5, value evaluation. According to the method, through quantitative analysis of a claim modification track in the review opinion reply process, especially the core index of the calculation technology abandon-retention ratio, patents which are subjected to large limitation shrinkage and of which the core protection range is seriously shrunk can be effectively discriminated, and association degree overestimation caused by neglecting the review game process is avoided.

This invention introduces the Dynamic Equity Distribution Method, a groundbreaking system designed to enable fair, transparent, and adaptable equity allocation in startups and collaborative ventures. By integrating blockchain technology, tokenization, and dynamic adjustment mechanisms, this method overcomes the limitations of static equity models, ensuring that ownership shares continuously align with each member's real-time contributions. Key features include: Comprehensive Contribution Valuation: A structured approach to evaluate both financial and non-financial contributions, such as intellectual property, network resources, physical assets, skills, and time, using Fair Market Value (FMV) assessments. Dynamic Adjustment Mechanism: Automated equity realignments powered by smart contracts, conducting periodic reviews to reflect ongoing contributions and performance milestones. Tokenization and Blockchain Integration: Equity shares represented as digital tokens stored on a blockchain, ensuring transparency, security, and ease of ownership transfer. Structured Exit Protocols: Predefined procedures for member exits, including buy-back options, share dilution mechanisms, reserve funds to manage ownership transitions seamlessly.

The invention discloses a global user and manufacturer oriented end-to-end online customization manufacturing platform system and a method thereof, which realize the whole process from creative input to finished product delivery based on ai-driven design generation and global manufacturing resource intelligent scheduling. The platform comprises an AI design generation module, a CAD modeling and optimization module, a manufacturing rule verification module, a material intelligent recommendation module, a global factory matching and pricing module, a tax and logistics estimation module, a one-key ordering and delivery module, an intellectual property protection module and a user and factory authentication mechanism module. And a multi-part structure decomposition and remote part division type cost optimization scheduling module. A user can generate a product drawing through language or image input, a platform automatically outputs a CAD model and performs structure optimization and manufacturability verification, and materials are recommended in combination with a purpose scene. The system intelligently matches global manufacturers based on factors such as features, manufacturing difficulty, regions, tax and productivity, estimates the tax and logistics cost, and provides a one-key ordering path.

The invention belongs to the technical field of data storage management, and discloses an intellectual property data-based storage management system, which comprises the following steps of: firstly, acquiring comprehensive data, preprocessing, and constructing a comprehensive feature set; secondly, according to the comprehensive feature set, repeated data are detected, and repeated data items are identified; then, the influence of the repeated data items is evaluated and processed; and finally, in the data item processing process, data among multiple nodes are kept consistent, and abnormal states are monitored in real time, so that quick response and problem solving are facilitated, the intellectual property data management efficiency and quality are improved, the robustness and reliability of the system are enhanced, and more reliable and convenient services are provided for users.

The invention provides an intellectual property service intelligent recommendation method and system and electronic equipment, and the method comprises the steps: carrying out the feature extraction of an invention technology material submitted by a user, obtaining a technical feature vector, carrying out the data preprocessing, constructing a technical feature matrix based on the technical feature vector, and constructing a human body immune model. Inputting the technical characteristic matrix as an antigen into a human immune model, generating an initial technical antibody, obtaining an initial technical antibody candidate set based on the initial technical antibody, performing clone mutation operation on the initial technical antibody candidate set based on two-channel evaluation, obtaining a mutation technical antibody candidate set, and obtaining a mutation technical antibody candidate set; carrying out three-property optimization screening on the variation technology antibody candidate set to obtain an immune technology antibody set; carrying out simulation examination verification on the immune technology antibody set based on GAN to obtain a technology optimization strategy; optimizing the immune technology antibody set based on the technology optimization strategy to generate a corresponding intellectual property service strategy; and a more refined service recommendation strategy is provided for intellectual property service recommendation.

Approaches are disclosed for providing optimized AI models for use in performing various inferencing tasks. In at least one embodiment, a user may request a model to be used to perform an inferencing task, and may be presented with one or more optimization options. The user can select one or more of these optimization options, and in response a model and parameter set can be provided to the user, where the model and / or parameter set may be optimized and / or proprietary, and thus have their use restricted. Such an approach allows a user to effectively obtain a customized AI model that can be used for a specific type of inferencing task without the need to fine-tune or customize the model. In order to protect any intellectual property (IP), such as an optimized parameter set offered by a provider, the set may be encrypted and able to be decrypted and used only in authorized environments and associated with users having a valid key or cryptographic token associated with the set of optimized parameters.

The invention provides an intelligent customer service dialogue method and system for intellectual property legal consultation, and the method comprises the steps: firstly receiving an intellectual property legal consultation request of a user, and obtaining a consultation text sequence which comprises a plurality of legal question expressions and logic association information; performing intention analysis on the consultation text sequence, and extracting surface and deep appeal elements to form an appeal element set; calling an AI legal reasoning model to perform scene element matching based on the appeal element set, and generating a legal reasoning scene anchoring result; constructing a multi-round legal reasoning chain with the appeal element set as a starting node and the legal conclusion derivation as a termination node, and generating a multi-round reasoning process record; and the content of the reasoning node is dynamically associated with the provisions of the preset intellectual property legal basis library to generate a consultation response sequence containing the reasoning logic and the legal basis, and the consultation response sequence is fed back to the user, so that the efficiency, the accuracy and the comprehensiveness of intellectual property legal consultation are improved.

Solutions for efficiently scalable assurance assessments for hard third party intellectual property (3PIP) are disclosed. Examples parse a data file (e.g., a netlist, GDSII, or OASIS) identifying components and connections for a functional component of an integrated circuit (e.g., ASIC, FPGA) and generate a graph having nodes and edges corresponding to the components and connections. Subgraph matching identifies portions of the graph that match subgraphs in a library of known secure functionality. Unmatched portions are then further analyzed for security, such as by extracting a schematic, performing a Boolean analysis, or performing a circuit simulation. When all portions of the data file are found to be secure, the data file is flagged and the integrated circuit may be fabricated or programmed.

The present invention provides an information processing device affording excellent convenience, usefulness, and reliability. The information processing device includes a reception unit, a documentation data extraction unit, a prompt data generation unit, an information extraction unit, and a display data generation unit. The reception unit has a function for receiving intellectual property data. The intellectual property data includes a specification, claims, a written notice of reasons for refusal, and cited documents. The documentation data extraction unit has a function for extracting at least one of the above pieces of documentation. The prompt data generation unit has a function for generating prompt data that includes instruction data and the extracted piece of documentation, and for outputting the prompt data to a language model. The information extraction unit has a function for extracting information from response data generated by the language model. The display data generation unit has a function for generating display data on the basis of the information and outputting the display data to an information terminal.

The invention belongs to the technical field of intelligence, and discloses an intellectual property operation management system based on big data, comprising: acquiring behavior data and basic data of intellectual property; carrying out missing value and abnormal value processing on the behavior data of the intellectual property to obtain a preprocessed data set; predicting value index data of the intellectual property by using an SVR model based on the preprocessed data set; an ETL tool is used for extraction, conversion and loading, a TF-IDF technology is used for processing the application name, a keyword group B is extracted, and the keyword group B serves as a new field to be stored in a target database; based on a text input by a user, obtaining a keyword A by using a TF-IDF technology; matching with the keyword group B to obtain comprehensive matching degree data; based on the comprehensive matching degree data, a threshold value is set, and whether recommendation is carried out or not is judged; and the intellectual property operation management efficiency and accuracy are improved.

The invention discloses an intellectual property value management method based on artificial intelligence, and the method comprises the steps: obtaining exogenous data, and constructing a basic database according to the exogenous data; constructing an interpretation model and obtaining intellectual property information, performing semantic interpretation on the intellectual property information through the interpretation model, retrieving instance contents of similar fields and knowledge in the basic database according to an interpretation result, and integrating the instance contents and the interpretation result; performing intellectual property value evaluation on the integrated content by combining the cue word through the large model to obtain an intellectual property value evaluation result; and storing the evaluation result and the instance content, and performing visualization processing on the evaluation result and the instance content to obtain a visualization result.

A system for zero-knowledge proof of regulatory compliance for artificial intelligence model deployment encodes regulatory requirements into compliance predicates, generates and verifies zero-knowledge proofs without disclosure of protected information, updates a trust state, and enforces execution across jurisdictions and vendors while preserving privacy and intellectual property.

The application discloses a system construction method for realizing CAD model security and data property right identification management, and realizes automatic identification management of UG / NX model security and data property right classification based on a PLM system.The technical scheme comprises the following steps: step 1: security classification label, that is, determining the security label of the model through a security review process node; step 2: intellectual property right classification label, that is, determining the intellectual property right label of the model through an intellectual property right review process node; step 3: specifying the corresponding label based on an improved document review process of product life cycle management of an enterprise; step 4: remotely transmitting the label information embedding program to a task queue server, that is, triggering the embedding program to remotely transmit the label information and related model information to the task queue server after the review is completed; and step 5: automatically writing the label into the server based on UG / NX secondary development technology, so as to write the label information into the UG / NX model.

The application discloses a kind of project-oriented full life cycle intellectual property risk collaborative management method and system, it is related to project full life cycle management data processing technical field, the present application obtains the multi-source relevant data of each stage of target project full life cycle, constructs project intellectual property risk management and control benchmark database, completes data standardization processing and risk characteristic mapping, establishes the intellectual property risk grading management and control system covering project full stage, completes project full cycle risk identification, grade division and early warning by intellectual property risk intelligent identification model, issues risk disposal task to corresponding responsibility subject to realize multi-subject collaborative management, iteratively optimizes risk management and control strategy and outputs adapted management and control optimization scheme.The present application realizes project full life cycle intellectual property risk full coverage management and control, improves risk identification accuracy and multi-subject collaborative disposal efficiency, provides stable support for project intellectual property risk management and control.

This application is directed to managing and visually displaying intellectual property portfolio data to a user. A server is communicatively coupled to a database and a client device via an application programming interface, and hosts an intellectual property-data web application including one or more intellectual property-specific user interfaces. The server receives a request from a client device. In response to the request, the server provides an intellectual property information user interface displaying selectable intellectual property data affordances and an interactive data visualization, which further includes independently selectable jurisdictions. In response to a user selection of a particular independently selectable jurisdiction on the interactive data visualization, particular intellectual property data are retrieved from the database and provided to the client device. In response to a selection of a particular selectable intellectual property data affordance, particular intellectual property data are retrieved from the database and provided to the client device.

The system according to this embodiment aims to efficiently uncover and appropriately utilize intellectual property hidden within a company. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a judgment unit, a proposal unit, and a utilization proposal unit. The collection unit collects internal company data. The analysis unit analyzes the data collected by the collection unit. The judgment unit determines the potential of the intellectual property based on the results of the analysis by the analysis unit. The proposal unit proposes an application to the Japan Patent Office based on the results determined by the judgment unit. The utilization proposal unit proposes a method for utilizing the intellectual property based on the results proposed by the proposal unit.