137 results about "Associative processing" patented technology

The invention provides a case quality intelligent evaluation method and system based on a large language model, and the method comprises the steps: building an evaluation standard library covering various cases based on a law normative file and judgment practice; designing a complete evaluation reasoning chain based on the evaluation standard library; constructing a multi-agent system based on the evaluation reasoning chain; based on the multi-agent system, realizing distributed task allocation for unplanned online tasks by applying an imprecise alternating direction multiplier method algorithm; based on the distributed task allocation result, combining planning and reinforcement learning technologies to solve a relational multi-agent case association problem; based on the multi-agent case association processing result, applying a forced zero method sparse graph technology to realize effective learning based on a case graph; and constructing a case quality assessment knowledge graph based on the effective learning result of the case graph. By adopting the technical scheme, the accuracy, comprehensiveness and efficiency of case quality evaluation are improved.

The invention provides an interactive question and answer task processing method based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as generative large language models and agents. The method comprises the steps of determining a to-be-solved target task according to natural language input of a user; the target task is decomposed into a plurality of sub-target tasks at least including interactive question and answer tasks, each sub-target task is correspondingly issued to each sub-target agent at least including an interactive question and answer agent, and different sub-agents are used for processing different types of sub-tasks; the interactive question-answering agent is controlled to present an interactive graphical user interface corresponding to the interactive question-answering task to the user, an answer result corresponding to the received feedback answer is presented, and the interactive graphical user interface comprises a question and an interactive answer area; an associated sub-target agent in the multiple sub-target agents is controlled to generate a corresponding associated processing result based on an answer result output by the interactive question and answer agent, and the associated sub-target agent is a sub-target agent which depends on the answer result and serves as part of task input information; and determining a target processing result corresponding to the target task based on the association processing result. Through application of the scheme, a better comprehensive task processing effect can be brought under the condition of lower comprehensive cost, especially for an interactive question and answer task in which a user needs to subjectively answer a proposed question and the effect is checked according to an answer result; the interactive questioning and answering agent provides the interactive graphical interface containing the question and the interactive answering area for the user, so that the task requirement of the user can be met more quickly in an interactive answering mode, and the task solving effect is improved.

The invention provides a network security risk early warning method and system based on multi-source data fusion, and relates to the technical field of network security, and the method comprises the steps: collecting multi-source security data; performing entity identification and association processing on the multi-source security data to obtain entity association information; performing space-time alignment fusion processing on the entity association information, and constructing a threat fusion matrix; performing risk analysis and threat identification on the threat fusion matrix based on rule engine matching, a behavior anomaly detection AI model and a graph neural network; and performing graded early warning based on a risk analysis and threat identification result. According to the network security risk early warning method and system based on multi-source data fusion, the accuracy and the real-time performance of network security risk early warning are remarkably improved through multi-source data fusion and multi-dimensional analysis.

The invention provides an instant message inquiry type task processing method based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as generative large language models and agents. The method comprises the steps of determining a to-be-solved target task according to natural language input of a user; the target task is decomposed into a plurality of sub-target tasks at least including instant information inquiry tasks, each sub-target task is correspondingly issued to each sub-target agent at least including an instant information inquiry agent, and different sub-agents are used for processing different types of sub-tasks; the instant information inquiry agent is controlled to inquire questions from the inquiry object to obtain instant feedback, and the instant information inquiry agent supports question inquiry in a background operation mode; an associated sub-target agent in the multiple sub-target agents is controlled to generate a corresponding associated processing result based on instant feedback output by the instant information inquiry agent, and the associated sub-target agent is a sub-target agent which depends on the instant feedback and serves as part of task input information; and determining a target processing result corresponding to the target task based on the association processing result. By applying the scheme, a better comprehensive task processing effect can be achieved under the condition that the comprehensive cost is lower, and in particular, an instant information inquiry task which needs to be combined with the instant information to verify whether the actual situation meets the task requirement or not and takes the verification result as instant feedback is obtained; in addition, the instant information inquiry agent also supports question inquiry (namely asynchronous task processing) in a background operation mode, so that the user does not need to stay in a session interface all the time, and other operations of the user are not influenced.

The invention discloses a multi-modal fusion bank receipt intelligent processing system and method based on vision and NLP, and the method comprises the steps: receiving a bank receipt picture or a PDF document, and completing the text detection, direction correction and character recognition through a visual processing engine; a three-level receipt independent segmentation mechanism is applied, and independent receipt records are divided through spatial clustering analysis, semantic analysis, visual verification and cross-page association processing; jointly extracting text features and layout features of each receipt through a double-flow multi-modal fusion model, and fusing the text features and the layout features; field-level data extraction is executed through a field extraction engine, and financial data verification including account number, amount, date and abnormity quadruple verification is carried out; and generating structured JSON output to obtain a bank receipt processing result. According to the invention, the innovative five-layer processing architecture realizes high-precision analysis of the bank receipts through an independently researched and developed receipt independent segmentation engine, a vision-semantic fusion model and a financial data verification system.

The invention provides a cross-domain collaborative information tracking and positioning auxiliary method and system, and the method comprises the steps: firstly collecting an original data set generated by a target event in a plurality of associated domains, carrying out the cross-domain identifier matching processing to obtain a standardized event data set, and then carrying out the information association processing of the standardized event data set, according to the method, context semantic features and cross-domain time sequence behavior features of a target event are generated, then collaborative analysis is performed on the features based on a preset collaborative analysis model, a cross-domain collaborative tracking index set is generated, and a dynamic tracking path topology is constructed according to the cross-domain collaborative tracking index set. According to the method and the device, the target event is tracked and positioned, the positioning auxiliary strategy matched with the target event is generated, and finally the positioning auxiliary strategy is synchronized to the cross-domain tracking system to activate the cooperative positioning operation, so that the cooperative processing of multi-domain information is realized, and the target event tracking and positioning accuracy and efficiency are improved.

The invention discloses an intelligent conference recording and recording method and system. According to the invention, cloud service equipment receives multi-modal information sent by edge equipment; processing the multi-modal information, and generating conference record information in combination with context sensing error correction, content segmentation, a dynamic segmentation strategy and a preset storage strategy; carrying out encryption processing on the conference record information based on the participant role information, and generating target format conference information; processing the target format conference information to generate initial conference scene mode information including a conference outline, a PPT and a mind map; processing the target format conference information and the initial conference scene mode information to generate conference information data after priority ranking and strategy processing; performing semantic analysis, feature fusion and cross-modal association processing on the conference information data to generate target conference scene mode information; and determining a target application program based on the target conference scene mode information, and sending the target format instruction information to the target application program.

The invention relates to a high-speed target detection and tracking method using infrared event information, which comprises the following steps of: performing information filtering and image noise reduction on a multi-frame accumulated image by using a high-frequency infrared event stream and a low-frequency infrared image to finish preprocessing of event and image information; and a multi-channel input deep neural network comprising a spatio-temporal information association processing module is used for reasoning to realize target detection, finally, construction of a target trajectory is completed, and target tracking is realized through a trajectory association algorithm. According to the method, static information contained in an infrared image is combined with dynamic information in an event stream, high-speed weak and small targets are detected and tracked more accurately and quickly by utilizing the advantages of the two kinds of data, the detection sensitivity and the detection frame rate of the high-speed infrared moving small targets can be improved after the method is deployed in an infrared detection system, and the detection efficiency of the high-speed infrared moving small targets is improved. The method can reduce the energy consumption of the system, and can be widely applied to an infrared detection system with limited processing resources.

The invention provides a factory production quality detection method and system based on the Internet of Things, and the method comprises the steps: carrying out the regional semantic perception association of sensor combinations in different regions, and carrying out the three-dimensional association processing of physical data through a self-adaptive transmission protocol, and obtaining a structured quality data flow; according to the structured quality data flow and the quality inspection parameters, performing differential quality inspection load balanced distribution and multi-stop collaborative reasoning on the logistics stop network to obtain semi-structured quality inspection result data; according to the quality inspection result data, topological path quality decline analysis and quality anomaly spatial-temporal clustering processing are carried out on the goods allocation and the product quality state, and a quality knowledge graph is obtained; and according to the quality knowledge graph, performing multi-dimensional quality control limit self-learning adjustment and quality early warning grading response processing on the quality inspection parameters of different goods locations and paths. According to the method, accurate traceability and rapid improvement of product quality problems are realized, and the efficiency and accuracy of quality detection are improved.

The invention belongs to the field of communication, and particularly relates to a historical data-based user appeal association processing method and system, and the method comprises the steps: constructing a hierarchical historical work order library through natural language processing and a classification algorithm, and setting in a sensitive evaluation model and an intelligent matching model; performing classification and sensitivity evaluation on the user demands at the current moment; a double-layer order sending mode is set, the appeals are distributed to corresponding approval nodes according to the appeal classification and sensitivity, and historical associated work orders are searched through an intelligent matching model; distributing the historical associated work order and the basic information of the user to an examination and approval node, and carrying out monitoring and secondary distribution on an abnormal work order; performing examination and approval reply and reply auditing by using the receipt template; according to the invention, the hierarchical historical work order library is constructed and a double-layer order sending mode is adopted, so that the work order processing efficiency and accuracy are improved, and the safety of user demand processing is enhanced at the same time.

The invention discloses a system evaluation-oriented multi-source heterogeneous data association method and device. The method comprises the following steps of: acquiring a system evaluation-oriented multi-source heterogeneous data set; the multi-source heterogeneous data set comprises a multi-source heterogeneous data subset of each technical index obtained by measuring the equipment system; the multi-source heterogeneous data subset comprises a picture data sequence, a text data sequence and a test data sequence; preprocessing the multi-source heterogeneous data set to obtain a preprocessed data set; and performing heterogeneous data association processing on the preprocessed data set to obtain a multi-source heterogeneous data information set of the same equipment system.

The embodiment of the invention provides a multi-modal data processing method and system based on a knowledge graph, and aims to solve the problems of semantic association deficiency and potential association mining difficulty in multi-source information processing. The method comprises the following steps: firstly, acquiring a multi-source information set containing different expression form information units and source identifiers, and performing entity mapping on the multi-source information set and a preset semantic association network to generate an information unit set with semantic association tags; performing cross-source feature association processing to obtain a comprehensive feature set; then, a semantic reasoning rule is called for association extension, and an extension feature set is generated; and finally, based on the extended feature set, generating an information processing result conforming to an application scene and feeding back the information processing result to a corresponding interface, thereby effectively integrating multi-source information and mining potential association.

The invention discloses a project cost analysis method, electronic equipment, a readable storage medium and a program product, and relates to the technical field of project management, and the project cost analysis method comprises the steps: obtaining various types of original data of a target project in a target system to which the target project belongs; each type of original data comprises project type data, system type data and product type data; generating each associated data combination according to the data with the association relationship between every two data in each type of original data; determining the similarity between two pieces of data contained in each associated data combination, and taking each associated data combination with the similarity greater than a preset similarity threshold as each target combination; performing association processing on data contained in all the target combinations to obtain an associated data set of the target project; and analyzing the cost of the target project based on the associated data set. The analysis efficiency and the analysis accuracy of the project cost can be improved.

The invention provides an AI-based financial service product personalized recommendation generation method and system, and relates to the technical field of digital financial services, and the method comprises the steps: firstly obtaining a multi-modal financial data set comprising a user text type financial interaction record, a voice type financial consultation segment and a video type financial product explanation and watching record; carrying out cross-modal association processing on the multi-modal financial data set to obtain an association chain of text semantics, voice emotion and video concern areas, generating a user financial demand reference map containing user demand tendency and association weight based on the association chain, carrying out demand tendency enhancement processing on the user financial demand reference map, adjusting the association weight, and carrying out demand tendency enhancement processing on the user financial demand reference map; and finally, a financial service product personalized recommendation sequence sorted according to the matching degree is generated according to the enhanced user financial demand reference map, so that the user demand can be comprehensively analyzed, and the recommendation accuracy and the user satisfaction are improved.

A decoder of a neural semantic parser receives input data associated with a natural language expression. An action is selected from a queue of actions, the queue of actions storing at least one action, the action being associated with an element from vocabulary of the natural language expression. The selected action is processed to build a tree structure where the processing of the selected action expands the tree structure with a node representing the element, where the tree structure is expanded bottom-up. A set of new actions is generated based on the node associated with the selected action and the vocabulary. The set of new actions is added to the queue of actions. The decoder repeats selecting, processing, generating and adding until a criterion is met. A logical form of the natural language expression is output based on the tree structure.

The invention relates to the technical field of place name data processing, and particularly discloses an automatic association processing method based on open source place name data, which comprises the following steps: firstly, carrying out entity detection on natural language text content containing place names to extract candidate place names, and taking other content in the text as supplement; the semantic coding technology based on deep learning is adopted to carry out semantic coding and compensation type interactive fusion on candidate place names and supplementary content thereof, and the supplementary content is used as a context background to optimize semantic feature expression of the candidate place names. And constructing a place name alternative list by querying associated entity data of the candidate place names in the geographic database, and realizing automatic association of the place name data based on semantic similarity between each alternative place name in the list and the candidate place names. According to the application, the accuracy of place name data association can be effectively improved, meanwhile, the dependence on manual annotation is reduced, and the data processing efficiency is improved.

The invention relates to the technical field of data delivery, and discloses an engineering data digital delivery method and system based on a BIM large model, and the system comprises a data collection unit, a data integration unit, an association processing unit, and a data delivery unit. According to the method, various data are collected from each related system and terminal of the project, rich contents such as a BIM model and a design drawing are covered, a complete data basis is provided for project management, and information loss is avoided; a specific conversion algorithm is adopted for data of different sources, for example, CAD drawings and the like are subjected to accurate format conversion and association, an information base is constructed with a BIM model component as a core, and data availability and management efficiency are improved; by assigning a unique identifier to the component and establishing association between multiple aspects and the component, information of each stage of the component can be conveniently traced, and engineering management is powerfully supported; by means of correlation analysis, the data value is improved, data potential relations are mined, problems are found, the scheme is optimized, and more valuable information is provided for operation and maintenance management.

The invention discloses a financial field knowledge base construction method, device and equipment. The method comprises the following steps: firstly, identifying a text region, a table region and an image region from a target image; then extracting text data of the text region by using an OCR algorithm, and extracting semantic features and visual features of the image region and a second entity set and an entity type corresponding to the table region by using a multi-modal AI model; carrying out illusion detection by utilizing the similarity of the two entity sets, and when judging that the illusion of the AI model does not trigger a fault-tolerant mechanism by utilizing a detection result, carrying out intelligent alignment processing on the two entity sets, and screening out an optimal entity matching pair; carrying out formatting verification on the entity type; and then context knowledge association processing is carried out on text data corresponding to the text region, semantic features and visual features corresponding to the image region and entity matching pairs passing verification, and a more stable and accurate knowledge base is constructed by utilizing the obtained graph structure document to represent corresponding structured knowledge.

A method for concurrently performing multiple computations in an associative processing unit (APU) includes having data in two matrices, representing data in two portions of a memory array of the APU, creating a Tartan matrix by computing an outer product between a first bit vector indicating selected rows and a second bit vector indicating selected columns, the Tartan matrix representing data stored in a third portion of the memory array wherein all cells having a value 1 in the Tartan matrix indicate selected cells, concurrently activating all cells of the matrices and storing a result of Boolean operations therebetween in one of the two matrices, wherein a new value is obtained on cells located at a same row and a same column as the selected cells in the Tartan matrix and an original value remains on other cells.

This invention belongs to the field of intelligent maritime surveillance technology, specifically a smart waterway monitoring and management system based on light beacons. It synchronously acquires multi-source heterogeneous information about vessels through integrated light beacon equipment, performs spatiotemporal registration and target association processing on this information, generates dynamic vessel trajectories, and extracts static attributes, motion behavior characteristics, visual activity characteristics, and environmental interaction characteristics. Utilizing a multi-evidence chain collaborative decision-making mechanism, it accurately identifies four fundamentally different vessel states: normal anchoring, illegal anchoring, active navigation, and uncontrolled dragging of anchor. This achieves a leap from state perception to behavioral cognition, significantly improving the accuracy of vessel anchoring identification and its robustness in complex scenarios. Based on the identification results, it triggers differentiated alarm strategies matching the state, generating handling instructions with reasons for the state determination, thereby greatly optimizing the allocation of surveillance resources and improving emergency response efficiency.

A method for calculating the N-bit square root B of a 2N-bit number X comprises: performing a multiplication of the bits b of the square root B. i Iterate starting from the most significant bit of the square root B and working your way down to the least significant bit. For each iteration, the method includes: positioning a 1 at bit b in the CHECK variable. i The bit b is determined based on the comparison of the number X with all previously found bits and a function of the previous comparison results. i shift all previously found bits in the CHECK variable right by 1 position; and i The determined value is added to its square position in the CHECK variable.

The present disclosure provides an image processing and classification method and apparatus, an electronic device, and a storage medium, wherein the method comprises: obtaining a first image selected from an image set, and a feature set stored in a storage buffer; performing a first enhancement process and a second enhancement process on the first image to obtain corresponding first enhanced images and second enhanced images; inputting the first enhanced image and the second enhanced image into a trained neural network for feature extraction to obtain first features and second features; performing association process on the first features and the second features with features in the feature set, and adjusting the neural network based on the similarity or difference between the first associated features and the second associated features obtained by the process. The loss function value in the present disclosure comprehensively considers the associated features of enhanced images with different enhancement strengths. This limitation can improve the training performance of the neural network, thereby improving the accuracy in subsequent classification applications.

The invention provides a Promise-based AI platform resource monitoring method and system, and relates to the technical field of resource monitoring, and the Promise-based AI platform resource monitoring method comprises the following steps: creating resource objects of a container management platform, and configuring a resource label for each resource object; a pre-configured label index set is used for screening resource labels meeting the monitoring requirement, list connection association processing is carried out on the screened resource labels and resource monitoring indexes provided by the open source container monitoring tool, and a wide list is generated; aggregation processing is carried out on the resource monitoring indexes in the wide table, and the total resource use amount under the preset query dimension is calculated; and a global index mapping rule base is constructed, and standardized access of different monitoring devices is adapted by configuring an adaptation layer. According to the method, the complexity caused by different equipment monitoring plug-ins is shielded through the unified query adaptation layer, the code quantity and complexity of a query interface are reduced, and the maintainability and readability of codes are improved.

A calculator for calculating a plurality of square roots includes a memory array, at least two registers, a bit subtractor, and a controller. The memory array is organized into columns and rows. The registers store a fixed value. The controller, operatively coupled to the other components, allocates a first set of rows to test variables and a second set to result variables, and initially stores each of a plurality of radicands in a separate column. For multiple iterations, the controller concurrently activates selections of rows to form current operands and current guesses for each column. The controller then instructs the bit subtractor to perform subtraction operations. For each column with a positive subtraction result, the controller selectively writes a new bit of the square root and selectively overwrites values with a new remainder derived from the subtraction result, without performing an explicit data-shifting operation.

The application discloses a multi-modal cooperative instruction analysis and execution method and system for a screen-equipped sound box, relates to the technical field of intelligent sound box interaction control, and comprises the following steps: merging interactive response inputs generated by a local end of the screen-equipped sound box into interactive acceptance events according to the entering order of the local interactive processing procedure, generating acceptance time sequence positions for the interactive acceptance events, and forming an acceptance time sequence chain; forming a display bearing relationship according to the corresponding relationship between display objects and action entrances, associating the display bearing relationship with the corresponding acceptance time sequence positions, writing the acceptance time sequence positions into the acceptance time sequence chain, and forming a display bearing state record. According to the application, the interactive acceptance events and the acceptance time sequence chain are established at the local end, so that the screen trigger input, the voice input and the display bearing state can be associated and processed on the basis of the same acceptance time sequence, and the instruction acceptance accuracy of the screen-equipped sound box in continuous multi-round interaction is improved.

The present invention provides a method and system for automatically associating classroom recording videos with knowledge graphs, and relates to the field of data processing technology. The present invention utilizes the rule that under normal circumstances, there must be continuous segments in a teaching video that belong to the same knowledge point or continuous knowledge points, adopts a derivation calculation starting from a point to perform forward and backward knowledge point matching, and realizes calculation from point to surface, thereby realizing the association between the entire video and the knowledge points, and the sequential relationship of the teaching knowledge conforms to the objective distribution law. In the derivation process, the knowledge point continuity rule is combined with a large model. When it is not necessary, the rule is used for association processing, and the large model is used for auxiliary judgment only when it is necessary. The setting of fixed rules reduces the amount of calculation, can achieve a great improvement in efficiency, and maintains the objectivity of the matching results and avoids the influence of hallucinations to the greatest extent.

The invention provides a maintenance fund data management method and device, equipment, a medium and a product. Relates to the technical field of data processing. The method comprises the following steps: acquiring index design demand data and maintenance fund data of a plurality of cells; determining at least three index dimensions according to the index design demand data, and determining a main body and a to-be-combined attribute of each index dimension; storing the maintenance fund data of each cell as an independent attribute table in an attribute value manner according to the main body of each index dimension and the to-be-combined attribute; obtaining user query request data, and determining a plurality of to-be-combined attributes of the at least three index dimensions according to the user query request data; generating corresponding index query conditions according to the to-be-combined attributes of the at least three index dimensions; and carrying out association processing on the attribute table of the index dimension corresponding to each to-be-combined attribute and the business process data to obtain an index result meeting the index query condition. The method has the technical effect of improving the flexibility and real-time performance of maintenance fund data processing.

The invention relates to the technical field of large language models, and discloses an intelligent geographical name and address data matching method based on a large language model, which comprises the following steps: collecting geographical name and address related data and corresponding spatial graphic data, and carrying out fusion association processing on the geographical name and address related data and the corresponding spatial graphic data to obtain processed information; carrying out textualization and vectorization conversion on the processed information to form a place name address knowledge base adaptive to a large language model; based on a place name and address knowledge base and a big language model enhanced retrieval and cue word fine tuning technology, obtaining a place name and address matching model with address hierarchy matching result evaluation; receiving a to-be-matched place name address text, performing retrieval based on the place name address knowledge base after preprocessing, and obtaining a candidate matching result set; and calling a place name and address matching model to perform hierarchical evaluation on the candidate matching result set, and outputting an optimal matching result and a matching hierarchy thereof.

The invention discloses an artificial intelligence security operation central system, and particularly relates to the technical field of network security operation management. The system comprises a data fusion layer, an intelligent analysis layer, a decision response layer and a digital twinborn layer. The data fusion layer is responsible for performing real-time receiving, standardization and association processing on the multi-source heterogeneous security data to generate a security event sequence in a unified format; the intelligent analysis layer is used for identifying security threats and detecting abnormal behaviors through a multi-mode neural network and a behavior mode analysis module; the decision response layer automatically matches a response strategy according to a dynamic risk assessment result; the digital twinborn layer constructs a system virtual mirror image and supports attack and defense deduction and strategy pre-verification. According to the system, intelligence and automation of the whole safety operation process are realized, and the threat detection precision, the response speed and the overall safety defense capability are effectively improved.

This invention relates to the technical field of robot training. Specifically, it relates to a robot adaptive training method, apparatus, and medium based on reinforcement learning. The method includes generating task sub-objective information using a high-level policy network, inputting the task sub-objective information into a low-level execution network, generating action control commands based on the task sub-objective information, collecting interaction feedback information during execution, calculating a reward value based on the interaction feedback information, associating the reward value with scene complexity parameters, performing dynamic reward shaping operations to generate an adjusted reward signal, generating a policy model optimized by meta-learning based on the adjusted reward signal, loading the policy model into a simulation environment to generate a target policy model optimized by simulation training, loading the target policy model into the robot, and controlling the robot to perform task operations in an actual interactive scenario. This invention achieves the effect of adaptive task learning for robots in multi-interaction scenarios.