515results about "Product appraisal" patented technology

Systems and methods for controlling rights related to digital knowledge are disclosed. A sample system may include an input system to receive digital knowledge from a user, a tokenization system to tokenize the digital knowledge and a ledger management system to create, manage, and store things on a distributed ledger and provide provable access to the digital knowledge. A smart contract system may create a smart contract including triggering action is and respond with a defined smart contract action on an occurrence of the triggering event. The smart contract system may also process commitments to the smart contract.

Consumer operated kiosks for recycling electronic devices are disclosed herein. In some embodiments, the kiosk includes a rotatable inspection plate configured to receive an electronic device when the inspection plate is in a first position. The kiosk can include a camera having a field of view including at least a portion of the inspection plate. The kiosk can include a wired and / or wireless connectivity device configured to connect to the electronic device and one or more processors configured to: receive characteristic information about the electronic device via the wired and / or wireless connectivity device; cause the inspection plate to rotate to a second position; receive one or more images of the electronic device via the camera when the inspection plate is in the second position; and facilitate determination of an offer price for the electronic device based at least in part on the characteristic information and the one or more images.

Methods, apparatus, and systems for generating a price of a target device. An evaluator device obtains technical properties associated with the target device. The technical properties include a make and a model of the target device. Physical properties associated with the target device are obtained. The physical properties include information related to wear and tear of the target device. Obtaining the physical properties includes indicating to a user that the user should position the target device in multiple predetermined positions and that the evaluator device records an image of the target device in each of the multiple predetermined positions. A video of the target device is recorded while the target device is positioned in the multiple predetermined positions. The obtained physical properties are evaluated to generate a condition metric value of the target device. Based on the generated condition metric value, the price of the target device is determined.

The invention discloses an enterprise data link management and value management method and system, and the method comprises the steps: carrying out the real-time capturing of multi-source heterogeneous data of all business systems in an enterprise through a distributed data collection engine, and recognizing the types of original data in different formats through a preset data source adapter; if structured data is detected, a relational database connector is adopted for extraction, and if the structured data is recognized as unstructured data, a document analysis module is started for content extraction, and an initial data set containing metadata tags is obtained; performing format conversion and field mapping on the initial data set according to a pre-established data standardization rule base, eliminating duplicate records and abnormal values through a data cleaning algorithm, performing automatic evaluation on a data quality grade by adopting a naive Bayes classifier, if a data quality score is lower than a preset threshold value, triggering a data recovery process, and if the data quality score is lower than the preset threshold value, performing data recovery. And standardized data meeting a unified standard is obtained. The normativity and value utilization efficiency of data management are effectively improved.

The invention discloses a digital collection full-life-cycle traceability tracking system based on a block chain, and the system comprises a digital identification module, a verification module, a packaging transfer module, a verification module, an integration module, and a system construction module, and achieves the full-life-cycle traceability tracking of a digital collection through the technologies of multi-dimensional feature extraction, watermark embedding, distributed storage, and zero-knowledge proof. And tracking and verification of the whole process from creation to transaction of the digital collections are realized. According to the system, the transaction authorization model is encapsulated by adopting the intelligent contract, so that safe transfer of ownership is ensured; a tamper-proof verification mechanism is constructed through multi-level integrity verification; different platform data are integrated by using a cross-chain technology to form a comprehensive traceability graph, so that key problems of authenticity verification, copyright protection, value evaluation and the like faced by a digital collection market are effectively solved. In addition, the system also establishes a scientific authenticity evaluation and value dynamic evaluation system, provides an objective basis for market pricing, and significantly improves the credibility and safety of the digital collections.

The invention belongs to the field of automobile evaluation, and provides an automobile live risk evaluation system and method based on a large model, and the method comprises the steps: receiving voice input information of an evaluator in a vehicle on-site inspection process; extracting component state information of the target vehicle based on the structured check item text; acquiring historical maintenance record data of the target vehicle, and performing association fusion on the historical maintenance record data and the component state information; based on a large language model, performing joint reasoning on a currently input inspection label and the historical maintenance record, constructing a causal chain related to an accident risk, and generating at least one subsequent to-be-inspected item; generating voice guide content and feeding back the voice guide content to the evaluator so as to prompt the evaluator to continue to check the target item of the target vehicle; gradually perfecting the risk check path of the target vehicle until the risk chain closed loop is completed; and calling an estimation formula to calculate a residual estimation value of the target vehicle, and outputting a structured risk assessment report.

The invention relates to the technical field of data resource management, in particular to an online evaluation method for data resource value, which comprises the following steps of: constructing a multi-dimensional evaluation index set, and acquiring metadata and market dynamic information of to-be-evaluated data in real time through a distributed interface; carrying out weight distribution on the index set based on a dynamic weighting algorithm, generating a weight coefficient set and constructing a value calculation model; performing standardized preprocessing on the collected original data, inputting the data into the model, and calculating an initial estimated value; and dynamically correcting the initial value estimation value based on the timeliness attenuation factor and the data scarcity factor, and generating a final value estimation value and an estimation report. Through multi-dimensional index construction, a dynamic weighting algorithm, standardized preprocessing and two-factor correction, automatic evaluation of the data value is realized, the problems of single dimension, static weight and neglect of timeliness scarcity of a traditional method are solved, the real-time performance and scientificity are improved, and a quantitative decision basis is provided for data capitalization.

The invention relates to the field of cross-border trade, in particular to a cross-border trade full-chain risk identification and management model and method. The model comprises a data access module, a score calculation module, an auditing and judging module and a result output module, multi-dimensional data such as enterprise basic information, commodity declaration information, path transportation information and historical trade behaviors are integrated by means of a unified data interface structure, and an expert weight evaluation (AHP) method and a machine learning algorithm are combined to obtain a comprehensive evaluation result. And performing multi-dimensional risk scoring on the enterprises and the declaration receipts, and automatically judging whether the enterprises and the declaration receipts have exceptions or supervision requirements or not. The system introduces a scoring code system, a price list auditing state code and an AHP weight code to construct a standardized evaluation logic, so that the risk control efficiency and the judgment transparency are improved. The model has good expandability and application universality, is suitable for various business scenes such as cross-border supervision, credit assessment, customs affair auditing and the like, can realize pre-warning and process controllability of risks, and remarkably improves the compliance level and management intelligence degree of cross-border trade.

A device may receive first information associated with one or more properties, and second information associated with one or more properties, where the first information is of a different information type than the second information. The device may generate a first graph network based on the first information, and a second graph network based on the second information. The device may combine the first graph network and the second graph network to generate a combined network including a portion of the first information and a portion of the second information. The device may generate an embedding based on the combined graph network. The device may apply the feature embedding as input to a housing model to generate an output.

The present application relates to the technical field of project management, and discloses an integrated management system and method for a large-scale project. The system comprises: a budget subsystem, used for obtaining target project information, and carrying out multi-level classification processing and coding processing on the target project information to obtain budget codes; a contract management subsystem, used for decomposing the target project information, generating a plurality of project contracts and associating the plurality of project contracts with the budget codes; a construction management and control subsystem, used for splitting the project contracts to obtain unit projects, encoding the unit projects to obtain unit codes, and associating quantity data corresponding to the unit projects with a preset construction drawing list; and a joint control subsystem, used for carrying out joint control on the project cost, the project progress and the project quality on the basis of a measurement visa so as to carry out integrated management on a large-scale project. The present application realizes integrated management of large-scale project construction.

A facility for estimating the value of a distinguished home is described. The facility trains a forest of decision trees to estimate valuations for homes within the geographic area where the distinguished home is located using data including both previous home sale transaction prices and synthetic sale transaction prices based on listing prices. The facility accesses information about the distinguished home's attributes and applies each decision tree in the forest to that information, generating a number of estimated valuations. The facility determines an overall valuation for the distinguished home based on the valuations generated by the decision trees.

The invention relates to the technical field of data processing, and discloses a model dimension-based new energy vehicle value retention rate evaluation method and system, and the method comprises the steps: constructing three-table data, and carrying out the preprocessing; and fusing the static features and the time sequence features according to the type identifier to generate a feature sequence. And inputting the static features into a static feature sub-network to obtain a static representation, inputting the time sequence features into a time sequence feature sub-network to obtain a hidden representation of each time step, and obtaining a time sequence representation based on attention weighting. And performing drift detection on the input distribution and the model residual distribution. And splicing the static representation and the time sequence representation, inputting the spliced representation into a quantile prediction sub-network, outputting two value retention rate prediction results of different quantiles, and obtaining a value retention rate quantile set. And obtaining an insurance amount evaluation suggestion value based on the value retention rate quantile set and the new vehicle purchase price. According to the method, fine-grained description of different type feature differences is ensured, and the accuracy and reliability of a prediction result are improved.

Methods and systems for automatically mitigating risks of water damage to a property caused by insurance-related events are provided. A smart home controller and / or insurance provider remote processor may analyze data received from a smart device disposed on, within, or proximate to a property associated with monitoring water flow, as well as data received from an insurance provider. If it is determined that an actual or potential risk of water leakage exists, the smart home controller or remote processor may automatically issue commands to the smart device to take actions that mitigate the risk of water damage. The smart home controller may transmit information about the actual or potential water leakage risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data and perform insurance activities, such as providing a discount or premium, and / or adjusting an insurance policy associated with the property.

The invention relates to the technical field of financial science and technology and artificial intelligence crossing, and particularly discloses a personal loan unfavorable asset intelligent evaluation and pricing method based on a graph neural network, and the method comprises the steps: obtaining original data in real time, extracting multi-modal feature data based on the original data, and fusing the multi-modal feature data; establishing a debtor associated network atlas based on the debtor information, and performing risk assessment based on the debtor associated network atlas and the fused multi-modal feature data; the asset recovery rate is predicted, and the uncertainty is quantified; the asset package combination is optimized based on a Markov decision process model; pricing is carried out based on a risk assessment result, an asset recovery rate prediction result and an optimization strategy, by means of the deep fusion technology of multi-modal data and the strong nonlinear fitting capability of a deep learning model, the system can more fully mine value information contained in the data, and by constructing and analyzing a debtor association map, a debtor evaluation result is obtained. And investors are helped to avoid potential major investment risks.

An approach is provided for trading card platform. The approach involves, for example, initiating a reading of a machine readable code from a trading card to determine a card identifier. The approach also involves querying for one or more attribute data records associated with the trading card based on the card identifier. The approach further involves computing a value metric based on the one or more attribute data records and presenting a user interface displaying a digital representation of the trading card, the one or more sponsorship data records, the value metric, or a combination thereof.

A method and system for new property acquisition process for utilities. The process uses preprogrammed virtual reality headsets to provide property owners with a virtual reality (VR) social platform, such as a metaverse-enabled presentation, showing projects, answering questions, and delivering individualized property rights acquisition proposals. The invention enhances the property owner's presentation and enables significant scaling without significant headcount growth.

The invention relates to the technical field of bulk commodities, in particular to a bulk commodity transaction price prediction method, which comprises the following steps: acquiring multi-modal data of bulk commodities in the current period; the multi-modal data comprises meteorological data, macroeconomic index quantized values and news event analysis parameters processed by natural languages; the news event analysis parameters comprise market emotion indexes and policy change influence factors; performing data preprocessing on the multi-modal data of the bulk commodities in the current period to obtain preprocessed multi-modal data; inputting the preprocessed multi-modal data into a trained price prediction model to obtain a final prediction price; the price prediction model is a hybrid neural network model fused with an LSTM-Transformer (LSTM-Transformer). According to the method, the accuracy of bulk commodity price prediction is improved, and the calculation efficiency is high.

The invention provides an intelligent evaluation method and system for rental asset recovery and a medium. The method comprises the steps of obtaining equipment basic information data of target mobile equipment, performing evaluation processing, obtaining equipment preliminary recovery value evaluation data, collecting appearance image information of the target mobile equipment, extracting appearance condition feature data, performing processing according to the appearance condition feature data, obtaining an equipment appearance value evaluation index, and obtaining a recovery value evaluation result of the target mobile equipment. Obtaining hardware performance characteristic data of the target mobile equipment, processing to obtain an equipment hardware performance depreciation index, obtaining use behavior characteristic data of the target mobile equipment, processing to obtain an equipment depreciation index, and evaluating the data according to the initial recovery value of the equipment; processing is carried out in combination with an equipment appearance value evaluation index, an equipment hardware performance loss index and an equipment depreciation degree index, and final recovery value evaluation data of the equipment is obtained, so that the lease asset recovery intelligent evaluation technology is realized.

A device may receive first information associated with one or more properties, and second information associated with one or more properties, where the first information is of a different information type than the second information. The device may generate a first graph network based on the first information, and a second graph network based on the second information. The device may combine the first graph network and the second graph network to generate a combined network including a portion of the first information and a portion of the second information. The device may generate an embedding based on the combined graph network. The device may apply the feature embedding as input to a housing model to generate an output.

The invention discloses a second-hand car transaction information management method, and relates to the field of data: obtaining second-hand car historical transaction data, and performing hierarchical processing on the obtained data to obtain a hierarchical data set; the hierarchical data set adopts a brand-vehicle series-vehicle type three-level data structure; establishing a hierarchical graph neural network model through transfer learning according to the hierarchical data set; according to the second-hand car historical transaction data, establishing an evaluation model based on a residual value rate; mapping to-be-evaluated vehicle data to corresponding nodes in the hierarchical data set, and calculating a data sufficiency coefficient of the to-be-evaluated vehicle; according to the data sufficiency coefficient, selecting a hierarchical graph neural network model or an evaluation model to carry out second-hand car price prediction; and performing second-hand car transaction information management according to the predicted second-hand car price. As the sparse data vehicle type price prediction precision is low, the second-hand vehicle price prediction precision is improved.

The invention relates to the technical field of intellectual property value evaluation, in particular to an intellectual property value evaluation method, which comprises the following steps of: establishing a composite feature representation system containing technical semantics, keywords and claims, establishing a dynamically updated industry hotspot vector library, and performing vector space alignment to obtain an intellectual property value evaluation result. And generating a comprehensive score of a 0-1 interval based on a distance weighting model of a Gaussian kernel function, and displaying a result through an interactive system. The system comprises a composite feature extraction module, an industry hotspot modeling module, a vector space alignment module, a distance weighted evaluation module and a result display module. The method solves the problems that a traditional evaluation method is high in subjectivity and single in feature, objective quantification of patent value is achieved, and the method is suitable for scenes such as intellectual property management and technology transfer and transformation.

A method includes generating a media object; associating the media object with a trigger action; monitoring user activity of a user to detect an occurrence of the trigger action by the user; in response to detection of the occurrence of the trigger action by the user, modifying the media object to generate a modified media object; minting the modified media object as a non-fungible token (NFT) on a blockchain network; associating a dynamic value with the NFT, the dynamic value configured to change as a function of at least time according to an algorithm; providing the NFT to the user; in response to the user initiating redemption of the NFT in connection with an electronic payment transaction having a transaction amount, determining the dynamic value of the NFT based on the algorithm; and processing the electronic payment transaction by applying the dynamic value to the transaction amount.

The invention provides a vehicle evaluation management method and system for vehicle condition loss assessment, and the method comprises the steps: obtaining the vehicle basic information and vehicle damage information of a target vehicle, constructing a plurality of vehicle loss assessment dimensions of the target vehicle, and generating a part composition structure of the target vehicle, inputting the vehicle basic information and the vehicle damage information into the part composition structure for function test to obtain part performance characteristics corresponding to each vehicle part in the target vehicle, constructing actual vehicle condition information of the target vehicle based on the part performance characteristics, deducing a plurality of vehicle performance characteristics of the target vehicle by using the actual vehicle condition information, and determining the vehicle damage information of the target vehicle according to the vehicle performance characteristics. The target vehicle is evaluated step by step based on the vehicle performance characteristics, the market balance selling price range of the target vehicle is determined and displayed, the second-hand vehicle can be priced according to the vehicle condition and the market floating price of the vehicle, the stability of the market can be maintained, and consumers can buy the second-hand vehicle at ease.

The description relates to a system and method for predicting accident damage estimates for cars. More particularly, the description relates to a system and method for predicting accident damage estimates for new cars that utilizes accident data pertaining to previous insurance claims and car assembly modeling to predict accident damages. These accident damage predictions are used as input to calculate appropriate insurance premiums.

The invention relates to the technical field of real estate, and discloses an ant colony algorithm and neural network combined house price data prediction method, which comprises the following steps: S1, multi-source data acquisition, S2, data preprocessing, S3, ant colony algorithm parameter optimization, S4, neural network dual-stage training and S5, adaptive optimization feedback. According to the house price data prediction technology combining the ant colony algorithm and the neural network, neural network model parameters are optimized by adopting the ant colony algorithm; in the house price prediction model, the parameters are combined to form a path, and ants traverse different parameter combination paths; along with iteration, pheromones on a better parameter combination path are continuously accumulated and enhanced, and ants are guided to explore more; in this way, the parameter space can be fully traversed, local optimum caused by parameter random initialization of a traditional neural network is avoided, and therefore the model can obtain a better parameter combination, and the prediction precision is remarkably improved.

A system may include a non-transitory computer-readable storage medium storing instructions for execution and one or more processors that execute the instructions. The instructions may cause the one or more processors to configure at least one parameter of a crowdsourcing request related to obtaining information relating to a collateral for a loan, publish the crowdsourcing request related to obtaining the information relating to the collateral for the loan to a group of information suppliers, collect and process a response from an information supplier of the group of information suppliers, where the response includes information on a condition of the collateral for the loan, process the response provided by the information supplier to determine whether an information supply event relating to the response is successful, and respond to a determination of a successful information supply event.

The invention provides a business processing system for data assets. According to the method, the right of the data assets can be confirmed, for example, the data asset holding right, the data asset processing and using right, the data asset operating right and the like are clearly judged. The implementation path of the financial value of the data assets is considered, financing and transaction of the data assets are supported, and enterprises are helped to use the data assets for financial innovation. According to the method, the data assets can be capalized, the difficulty of cost collection is reduced, and the cost collection is a process of identifying, classifying, metering and summarizing various costs involved in the whole life cycle of the data assets from generation, processing to application.

The present disclosure provides systems and methods for facilitating completion of asset transactions by collaborating with users. User credentials from a plurality of users for a digital platform are received. The plurality of users are authenticated based on their user credentials. A set of selling parameters corresponding to an asset are received from a seller. A price of the asset is dynamically estimated based at least on the set of selling parameters and similar and / or geographically closely located assets. An offer price for the asset is received from one or more buyers. A communication connection, for example, a chat is established between the plurality of users including the buyer, the seller, and optionally, an agent, a landlord, an attorney, and a service provider to facilitate the completion of the transaction of the asset via the digital platform.