1331results about "Market data gathering" patented technology

A value chain network control tower system comprises a processor and memory configured to execute a know your model system that manages the complete lifecycle of Al models in enterprise environments. The know your model system performs model intake and registration actions including model documentation collection, registration procedures, metadata collection, input / output interface standardization, legal and licensing validation checks, and security validation. The system conducts comprehensive model evaluation and risk assessment actions by analyzing foundational properties, task performance, safety and risk management, alignment and compliance characteristics, operational metrics, and tooling transparency capabilities. The know your model system executes model deployment actions through automated environment validation, predeployment approval processes, and controlled production deployment with continuous monitoring.

In some embodiments, a configured artificial intelligence system includes a plurality of intelligence models; a scoring system configured to generate know-your-model scores that quantify suitability for specific tasks of each model; a model execution system configured to provide standardized execution environment for the plurality of intelligence models; a training and reinforcement system configured to monitor outcomes relating to decisions or predictions made by the plurality of intelligence models and use outcome data as feedback to reinforce model performance; and a governance and analysis system configured to ensure model operations comply with governance standards. The intelligence controller may be configured to receive task requests, analyze task complexity, decompose tasks into manageable subtasks, and dynamically select appropriate models from the plurality of intelligence models to execute each subtask based on model suitability and performance characteristics.

The present disclosure is directed to enabling asynchronous analytics via an intercept device. The intercept device may intercept a request transmitted by a user device to a host server, the request indicating data of interest to be provided by the host server in a response; transmit the request to the host server; asynchronously extract analytic data from the request; transmit the analytic data to an analytics server for performance of analytics on the analytic data; receive, from the analytics server, a result of performance of the analytics on the analytic data; determine, based at least in part on analyzing the result, whether the response from the host server is to be modified; selectively effect modification of the response based at least in part on determining whether the response from the host server is to be modified; and transmit the response to the user device. Various other aspects are contemplated.

A social media platform provides a map-based graphical user interface (GUI) for accessing social media content submitted for public accessibility via the social media platform supported by the map-based GUI. The GUI includes a map providing interactive location-based searching functionality in that selection of a target location by the user in the GUI, such as by tapping or clicking at the target location, triggers a search for social media content having geo-tag data indicating geographic locations within a geographical search area centered on the target location. A search period for which content is returned is dynamically variable based on the duration for which the tap or click is held.

An autonomous futures contract orchestration platform includes a set of processors programmed with a set of non-transitory computer-readable instructions. The instructions include receiving, from a data source, an indication associated with a product that relates to an entity that purchases or sells the product. The instructions include predicting a baseline cost of purchasing or selling the product at a future point in time based on the indication. The instructions include retrieving a futures cost, at a current point in time, of a futures contract for an obligation to the purchasing or selling the product for delivery or performance of the product at the future point in time. The instructions include executing a smart contract for the futures contract based on the baseline cost and the futures cost. The instructions include orchestrating the delivery or performance of the product at the future point in time.

A method for prioritizing predictive model data streams includes receiving, by a first device, a plurality of predictive model data streams. Each predictive model data stream includes a set of model parameters for a corresponding predictive model. Each predictive model is trained to predict future data values of a data source. The method includes prioritizing, by the first device, priorities to each of the plurality of predictive model data streams. The method includes selecting at least one of the predictive model data streams based on a corresponding priority. The method includes parameterizing, by the first device, a predictive model using the set of model parameters included in the selected predictive model data stream. The method includes predicting, by the first device, future data values of the data source using the parameterized predictive model.

The invention discloses a campus intelligent consumption analysis system and method based on multi-dimensional data fusion, and relates to the technical field of electric digital data processing. The system comprises a terminal feature fusion module, an anomaly identification analysis processing module and a classification verification and synchronization module. The terminal feature fusion module fuses terminal feature data and time feature data in the original multi-dimensional data to generate behavior association features, and data dispersion is reduced; the anomaly identification analysis processing module performs anomaly identification and processing on the behavior association features to form a feature data set and verify the validity, so that the detection accuracy is improved; and the classification verification and synchronization module uploads the verified classification result as a core data set to a specified service platform and synchronizes the core data set to a database of the specified service platform, so that the platform processing efficiency is improved. Through cooperation of multiple modules, efficient fusion, accurate anomaly detection and data synchronization of campus consumption data are realized, and comprehensiveness of campus consumption analysis and processing efficiency of a service platform are improved.

A computer-implemented method for computational textual search to find and display search identified information in documents. Search queries are processed over one or more documents either at a server or user device using match schemes that produce both binary (match or no match) and non-binary (i.e. multiple matching values) results and have relative fuzziness relationships. A fuzzier match scheme implies more results and fewer false negatives and a less fuzzy match scheme implies fewer results and fewer false positives. This fuzziness relationship allows, without changing a search string, for users to quickly change from a match scheme to a fuzzier or less fuzzy match scheme depending on user evaluation of results as containing too many false negatives or too many false positives—without becoming a programmer of complex search string metadata or an expert user of advanced search capabilities.

An AI-based energy edge platform is provided herein with a wide range of features, components and capabilities for management and improvement of legacy infrastructure and coordination with distributed systems to support important use cases for a range of enterprises. The platform may incorporate emerging technologies to enable ecosystem and individual energy edge node efficiencies, agility, engagement, and profitability. Embodiments may forecast, plan for, and manage the demand and utilization of energy in greater distributed environments. Embodiments may use AI, IoT, and technologies that filter, process, and move data more effectively across communication networks. Embodiments of the platform may leverage energy market connection, communication, and transaction enablement platforms. Embodiments may employ intelligent provisioning, data aggregation, and analytics.

The invention relates to the technical field of agricultural facility management, and discloses an AI-based agricultural scene omnibearing perception system and an implementation method, and the system comprises an order analysis module which is used for receiving order data and generating decision variables based on the order data; the collaborative optimization module is used for obtaining an optimization scheme based on a multi-objective function; the resource arrangement module is used for calculating a resource configuration scheme based on multi-target scheduling optimization; the sensing correction module is used for updating model parameters of the prediction model; the settlement loop module is used for performing delivery settlement based on the actual execution data; according to the invention, through adoption of a collaborative architecture, full-chain intelligent decision-making from market order analysis to agricultural product delivery is realized, through full-chain optimization and accurate decision-making, the net income of agricultural production is improved, and the production cost is reduced; through multi-objective function construction and a robust optimization algorithm, an optimal decision scheme can be found under complex constraint conditions, and the overall benefit of agricultural production is significantly improved.

An autonomous customer support Chatbot Agent utilizes a large language model to aid in implementing a workflow to solve a customer issue. A natural language workflow policy may be selected by an admin, along with tools such as API calls. The large language model determines the implementation details for the workflow based on the workflow policy and the selected tools.

An emerging service in the private and non-profit sectors is to electronically facilitate engagement of employees and volunteers for various causes. The instant systems and methods provide a software as a service platform that provides user engagement via machine learning and artificial intelligence.

The invention provides an intelligent marketing decision analysis method and system for a real-time competitive product strategy, and the method comprises the steps: collecting the marketing content of a competitive product published on a social media platform, extracting an account number, an arriving person portrait feature, a content structure label, a platform identifier and publishing time, and constructing a standardized strategy behavior vector; performing time sequence alignment on the strategy behavior vectors and our marketing indexes, and identifying competing product strategy behavior subsets which have significant influence on the our indexes; based on the subset, generating a structured response strategy containing a recommended person type, a content structure label, a delivery platform and a time period; and performing multi-dimensional matching on the marketing resource library and the content template library, and outputting an executable marketing resource combination and scheduling instruction. According to the method, a closed loop from competitive product behavior perception and causal influence identification to response strategy automatic generation and landing execution is realized, and the real-time performance, the accuracy and the automation level of marketing response are improved.

A method and system for profiling user behavior using personas, ground by context and based on survey and other data. Data associated with a segment is identified. The data comprises one or more characteristics of the segment. An interactive digital persona representing the segment is generated based on the data. The interactive digital persona representing the segment is caused to be provided to a user device.

A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may configure a robotic process automation system to execute the task to facilitate an improvement in the value chain network.

A new generation 3D modeling system is described for the management of the 3D characteristics of man-made structures in a shared geographic information system (GIS) platform. The system accommodates the conversion of 2D GIS topology to 3D real-world topology, originate and perpetually maintain 3D models and non-graphical attribute data through time managed by a community of users based on a series of permissions and user roles. The system integrates 3D model data with attribute data and may be supplemented with published map or attribute data and / or data made available by users of the system.

The invention discloses a smart marketing system and device and a medium, and belongs to the field of big data analysis. The system comprises a data support layer used for collecting multi-source heterogeneous data including equipment data, user behavior data and third-party data, and forming data assets by preprocessing the multi-source heterogeneous data; the intelligent decision-making layer is used for identifying the life cycle stage of the current user based on an intelligent model matrix and the data assets, predicting the transition stage of the life cycle of the user and generating a precision marketing strategy and a channel selection scheme of each stage; and the business application layer is used for converting the precision marketing strategy and the channel selection scheme into a specific marketing task, monitoring marketing effect data and feeding back the marketing effect data to the data support layer and the intelligent decision-making layer. According to the system, the intelligent marketing process of full-link data fusion, dynamic life cycle management and automatic marketing closed loop can be realized.

The invention provides an intelligent customer interaction method and system based on cloud computing and Al, and the method comprises the steps: carrying out the elastic shunting of user request data in a high-concurrency scene in a cloud computing architecture, and obtaining a classified request data set; performing AI model-driven semantic analysis and emotion feature extraction on a user input text in the request data set to obtain a user core intention tag and an emotion tendency coefficient; performing fusion analysis on the user core intention label, the emotional tendency coefficient and the user historical interaction behavior data to obtain a user personalized demand portrait; and based on the personalized demand portrait of the user, performing adaptive optimization on the preset UI interaction scheme and the service response template to obtain a scenarized optimal interaction scheme. According to the method and the device, the service stability is improved, the core demand in the text input by the user can be deeply understood, and the defect that the personalized interaction demand of different users is difficult to meet at present is overcome.

The invention relates to the technical field of metro key station identification and vulnerability evaluation methods, in particular to a metro key station identification and vulnerability evaluation method, which specifically comprises the following steps: step 1, metro network construction: establishing a weighted metro network model by adopting a Space-L space method according to a topological relation between metro stations and intervals, taking stations as nodes, intervals as edges and passenger flow as edge weights to form a weighted graph structure reflecting passenger travel rules, constructing an OD passenger flow matrix based on subway passenger flow card swiping data, and quantifying passenger flow connection strength between different stations; according to the method, the time-varying importance evaluation of the dynamic Domiank is combined with the feature learning ability of the graph convolutional network, and meanwhile, the structural complexity and passenger flow dynamic features of the subway network are described, so that the high-precision identification of the key stations and the comprehensive evaluation of the network vulnerability are realized.

The embodiment of the specification provides a gas operation method and an Internet of Things system based on a smart gas call center. The method comprises the following steps: acquiring gas user call data of the call center; predicting demand information of different types of users based on the gas user call data, wherein the demand information at least comprises gas product demand and gas service demand; determining and pushing gas operation push features based on the demand information of different types of users, wherein the gas operation push features comprise push type features and push content features.

The invention relates to the technical field of system dynamics, and discloses an electricity certificate carbon market price analysis method and system based on system dynamics, and the method comprises the steps: S1, determining the main body of a green certificate transaction market and the main body of a carbon emission permit transaction market, and determining a renewable energy power generation mode; s2, constructing a TCC cost control mechanism; s3, TCC cost is calculated according to a TCC cost control mechanism; s4, establishing stock flow dynamic model frames of the green certificate market and the electricity market and the carbon emission permit trading market and the electricity market, and combining the two dynamic model frames to generate an electricity certificate carbon market stock flow dynamic model frame; and S5, analyzing the electricity evidence carbon market price. The system comprises an information input unit, a mechanism construction unit, a calculation and analysis unit and a system dynamics model framework construction unit. According to the method, the system dynamics and the method for controlling and optimizing the TCC cost are combined, and the analysis accuracy and reliability are improved.

The invention discloses a tobacco marketing abnormal address management and control method, system and device based on GIS and multi-dimensional data fusion and a medium, and belongs to the technical field of tobacco industry informatization and internet marketing. The technical problems that in the prior art, address risk control dimensionality is single, query precision is insufficient, data linkage is lacked and visual analysis capacity is weak are solved. According to the technical scheme, the method comprises the steps that abnormal address data is constructed and queried based on a multi-dimensional label; gIS visualization and correlation analysis based on a mixed similarity model: GIS positioning and range loading, spatial candidate set filtering, text similarity fine screening, mixed weighted scoring and visualization rendering and statistics are realized through the mixed similarity model of spatial index coarse screening and text algorithm fine screening, and correlation order detail form display based on GIS range triggering is carried out.

Methods, apparatuses, system, devices, and computer program products for AI-driven data aggregation and analysis for entity scoring and assessment are disclosed. In a particular embodiment, a controller generates an entity profile for an entity by iteratively retrieving data related to an entity, the data including structured data and unstructured data, determining a structure for the unstructured data by applying the retrieved data to the AI model, the structure including a plurality of fields, and populating one or more fields of the entity profile with a respective value that is extracted from the retrieved data using the AI model. The controller stores the entity profile in a database comprising a plurality of entity profiles corresponding to different entities. The controller generates, using the AI model, a score for the entity in relation to an attribute based on an AI-driven analysis of the plurality of entity profiles.

The invention relates to the technical field of computer software, provides a visual flow arrangement method for e-commerce marketing, and aims to solve the problem of insufficient system processing performance and expansibility when an existing flow arrangement technology is applied to an e-commerce marketing scene. Generating and storing a state transition rule set; obtaining a user behavior event, obtaining a historical state transition event sequence according to the user behavior event, and then dynamically calculating a current user journey state; acquiring a corresponding state transition rule set, and performing matching query by taking the current user journey state and the user behavior event as input; if matching succeeds, a corresponding marketing action command is executed, and a new state transition event is generated and persisted to an event log so as to update a user journey state, so that efficient and accurate state-driven rule matching and automatic execution are realized, and the processing efficiency, expandability and state traceability of a system in a high-concurrency scene are improved.

The invention provides a multi-modal interaction method and device of an intelligent customer service system, equipment and a storage medium, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining multi-modal vehicle consultation data input by a target user; performing feature extraction on the vehicle consultation data of the multiple modes to obtain multiple feature vectors corresponding to the vehicle consultation data of the multiple modes; according to the types of the multiple modes and the current interaction scene of the target user, obtaining weights of the multiple modes in the current interaction scene; performing feature fusion on the multiple feature vectors according to the weights of the multiple modes to obtain a fused feature vector; and generating a service scheme for the target user according to the fused feature vector. According to the embodiment of the invention, standard processing and deep fusion of multi-modal data are realized, the problems of low response efficiency and inaccurate recommendation of traditional customer service are solved, and finally, the purposes of accurately insight into car purchase demands of users and efficiently outputting personalized marketing services are achieved.

Techniques described herein are directed to intelligently identifying buyers for resale items based on digital records. A computing system of a payment processing service can analyze digital records of a plurality of user associated with the service. A target buyer of an item can be identified. The computing system can cause an actuation mechanism to present on a user interface of the target buyer. The computing system can identify one or more users that have previously purchased an instance of the item and cause a notification that identifies the item as a candidate for resale to present via computing devices associated with the users. The computing system can receive an indication that a user desires to sell an instance of the item. The computing system can process a transaction on behalf of the user to enable the target buyer to purchase the instance of the item.

The invention discloses a multi-objective optimization method based on a Black-Litterman model for an ore grinding grading process, a multi-objective optimization device based on the Black-Litterman model for the ore grinding grading process, multi-objective optimization equipment and a computer readable storage medium. According to the method, the experience viewpoint of a process expert and historical data are organically fused by adopting the Black-Litterman model; the limitation that a traditional optimization method only depends on data driving or only depends on expert experience is overcome, and collaborative complementation of subjective knowledge and objective data is achieved. The deep learning technology is introduced to extract time series data features, and the convolutional neural network is combined to fuse expert viewpoints, so that the optimization model can fully excavate complex dynamic characteristics and inherent rules in the ore grinding classification process. Practical experience is fused into a prediction framework, so that the result is more suitable for practical operation, and the accuracy of ore grinding classification multi-objective optimization is improved.

The invention discloses a regional consumption demand calculation method based on e-commerce platform data, and belongs to the technical field of regional consumption demand calculation. The problem that a regional consumption demand calculation method is inaccurate in calculation is solved. The method comprises the steps of collecting basic data, obtaining preprocessed regional transaction data through an abnormal value self-adaptive suppression and neighborhood spatial interpolation method, carrying out spatial association, and calculating a regional commodity consumption characteristic entropy value; decomposing a time trend and a space trend in the consumption data through a periodic function and a space overflow model, and calculating a decomposed consumption trend and a decomposed daily average consumption trend; considering the influence of price elasticity and logistics timeliness, and calculating a consumption demand coupling factor; performing spatial heterogeneity correction through a geographical weighted kernel function to obtain a corrected consumption demand coupling factor; the regional commodity demand index is calculated through nonlinear normalization and supply constraint. Compared with a traditional theoretical demand calculation method, the method has the advantage that the landing conversion rate is improved.

Methods and apparatus for associating energy use with a data-stream passing through a device, or system or service center are provided, enabling reporting and control of energy from data centers or content delivery networks. In one embodiment, information is transmitted from a data center, comprising a number of customers associated with the data center, corresponding data rates for each of the number of customers and an energy for each of the number of customers. A total energy can be determined for all customers and for individual users. In another embodiment, an energy corresponding to an individual user within a set time interval can be determined and transmitted using the determined energy corresponding to the data center.

Methods, systems, and apparatus, including medium-encoded computer program products for secure workflows that enhance data security using sandboxes hosted by trusted execution environments. A digital component (DC) request can be received, and in response, multi-stage workflows can be identified. Each multi-stage workflow (i) being configured to select DCs of multiple content platforms and (ii) including customizable stages. A trusted execution environment of the server can initiate a sandbox environment for executing stages of the workflow, which can be executed within the sandbox environment, preventing the code of the workflow from transmitting user data from the server. Output data can be received from the workflow by the server and from the trusted execution environment. A DC can be selected by the server based on at least a portion of the output data from the workflows. The DC can be provided to the client device for presentation to a user.