67 results about "Semantic tree" patented technology

A data processing system implements receiving a call requesting a generative model to generate a semantic tree for a source content; constructing a first prompt including the source content and instructions to the model to analyze a semantic structure of the source content and to generate a semantic outline and content chunks of the source content, the semantic outline including one or more topics each connected with one or more of the content chunks, to compute one summary for each of the content chunks, to apply indices to reference each topic node of the semantic tree to one of the topics, and to apply indices to reference each leaf node of the semantic tree to one of the content chunks and the respective summary; providing the first prompt to the model and receiving the semantic tree of the source content; and storing the semantic tree in a database.

The invention discloses a human resource data natural language query and SQL generation method and system, and relates to the technical field of SQL generation, and the method comprises the steps: preprocessing a natural language query text input by a user, and constructing a query semantic tree; traversing the query semantic tree to generate a candidate entity set, determining an unambiguous entity through a three-layer ambiguity resolution mechanism of semantic scoring, service verification and cross validation, identifying a composite intention, disassembling the composite intention into a sub-intention sequence, and generating an SQL operation instruction set in combination with a preset SQL operation mapping rule; based on the SQL operation instruction set and the human resource data association model, determining a data table set and an association path, generating a dynamic calculation logic and structured condition expression, and constructing a structured query skeleton; according to the method, the personalized SQL template is dynamically generated according to the query skeleton, after filling, grammar verification, strategy optimization and logic consistency verification are performed, and the optimized SQL statement is output, so that the query accuracy and performance are remarkably improved.

A data processing system implements receiving a call requesting a generative model to generate a semantic tree for a source content; constructing a first prompt including the source content and instructions to the model to analyze a semantic structure of the source content and to generate a semantic outline and content chunks of the source content, the semantic outline including one or more topics each connected with one or more of the content chunks, to compute one summary for each of the content chunks, to apply indices to reference each topic node of the semantic tree to one of the topics, and to apply indices to reference each leaf node of the semantic tree to one of the content chunks and the respective summary; providing the first prompt to the model and receiving the semantic tree of the source content; and storing the semantic tree in a database.

The invention provides an intelligent customer service query system and method based on natural language understanding, and relates to the technical field of natural language processing. A query intention and a core entity of a natural language query request input by a user side are extracted; performing hierarchical deconstruction on the query intention, and constructing a query semantic tree according to a hierarchical deconstruction result and a semantic association relationship between core entities; generating a decision tensor representing a query path priority according to a node semantic weight of the query semantic tree and an access delay feature of the multi-source database; further adjusting an access sequence and a connection strategy of the multi-source data through a decision tensor and a dynamically updated query cost model to obtain a query execution link adaptive to the current query request; and calling a corresponding data source interface according to the query execution link to execute data retrieval and integration operation to obtain a target result set responding to the query demand of the user. By the adoption of the scheme, multi-source data optimal cost retrieval based on the natural language can be achieved.

The invention discloses a bug repairing method and system based on a grammar semantic tree, and the method comprises the steps: extracting a repairing mode fusing a grammar structure and a semantic intention from a historical bug repairing case, and guaranteeing the accuracy of the mode through program slicing guided by a key entity and iterative verification; on the basis of a double-constraint mechanism of grammar mergibility and semantic consistency, a specific mode is generalized to construct a hierarchical grammar semantic tree knowledge base; a knowledge base is used for generating a plurality of candidate patches for new vulnerabilities, single high-quality patches are generated through structure, grammar and semantic three-dimensional clustering and in-cluster integration and fusion, and the patches are output after heuristic sorting. According to the method, the defects that in the prior art, semantic understanding is shallow, and patch quality is unstable are overcome, and repairing accuracy, generalization ability and engineering practicability are remarkably improved.

A data processing system implements receiving a call requesting a generative model to generate a semantic tree for a source content; constructing a first prompt including the source content and instructions to the model to analyze a semantic structure of the source content and to generate a semantic outline and content chunks of the source content, the semantic outline including one or more topics each connected with one or more of the content chunks, to compute one summary for each of the content chunks, to apply indices to reference each topic node of the semantic tree to one of the topics, and to apply indices to reference each leaf node of the semantic tree to one of the content chunks and the respective summary; providing the first prompt to the model and receiving the semantic tree of the source content; and storing the semantic tree in a database.

The invention discloses a semantic tree index-based reasoning enhanced RAG retrieval method and system. The method comprises the following steps of: S1, reading and analyzing a document; s2, structuring the semantic knowledge tree by the document; s3, carrying out tree search and retrieval; and S4, enhancing the answer by the RAG system. According to the method, a long document of a specific field task is structured into an indexable semantic knowledge tree, and a large language model is guided to perform multi-step reasoning and path search on the tree in a retrieval process, so that a logic node which is most matched with query is dynamically locked, fundamental transformation from semantic similarity matching to structured logic positioning is realized, and the search efficiency is improved. The method does not need to depend on a vector database and embedded model training.

The invention relates to the technical field of intelligent water transportation information, in particular to an intelligent water transportation standard system construction method based on a four-dimensional level model. The method comprises the following steps: learning decision weights of different development value orientations according to idea features and execution features of a case, and determining a target development value of an actual water transportation service at a value dimension level; a spatial semantic tree is constructed by adopting a semantic layering mode, and traversal of the tree is driven by a target development value, so that matching of key element-scene requirements under a spatial dimension is realized. The method comprises the following steps of: partitioning a whole-cycle flow of a service, and performing time-dimension sequence pattern analysis on standard events at each stage to obtain corresponding time sequence construction requirements; and carrying out analysis and decision-making on operation paths among different elements from a logic dimension level to form a target implementation path and a support strategy. According to the method, a full-factor, full-period and full-scene intelligent water transportation standardization system can be constructed, and reliable multi-dimensional standard guidance is effectively provided for water transportation engineering construction.

The invention provides a content marketing semantic analysis method and system based on natural language processing, and relates to the technical field of natural language processing, and the method comprises the steps: constructing a marketing intention semantic tree through dependency syntax analysis, calculating audience perception vectors to form a conduction path graph, recognizing and demonstrating conflict unit pairs, and evaluating marketing persuasion. A double-layer optimization objective function is constructed for text reconstruction, scientific analysis and accurate optimization of marketing content are realized, the persuasion and the propagation effect of the marketing content are improved, the consumption of marketing resources is reduced, and the accuracy of a marketing strategy is enhanced.

The invention relates to the technical field of computer vision and geographic information, and particularly discloses a cross-view geographic positioning acceleration method based on semantic description, which comprises the following steps of: performing instruction fine tuning on an input query image and a database image by adopting a visual language model to generate natural language description; coding the natural language description into a low-dimensional semantic vector by utilizing a word embedding model; constructing a semantic keyword association graph based on a graph embedding technology, and fusing a general semantic knowledge base and a geographic domain ontology to construct a surface feature special semantic tree; screening candidate subsets according to a preset ground feature priority and a saliency detection result of the query image; extracting global features and local key point descriptors of the images in the candidate subsets by adopting a lightweight model; constructing a visual similarity calculation model based on the state space model, and modeling a feature sequence dependency relationship; and fusing the semantic matching score and the visual similarity, outputting a final matching result by adopting a weighted sorting strategy, and cooperatively accelerating according to the matching result in combination with a lightweight model.

The embodiment of the invention discloses a buried point verification method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of buried points. The method comprises the following steps: acquiring a burying point application form; performing intelligent verification on the burying point application form to obtain a structured parameter table and business metadata; inputting the structured parameters and the business metadata into a semantic analysis engine to obtain a parameter semantic tree of the burying point application form; obtaining a dynamic verification rule generated by a dynamic rule generator; the dynamic rule generator is obtained by training based on a historical burying point log; and verifying the parameter semantic tree of the burying point application form based on the dynamic verification rule to obtain a burying point verification result. According to the scheme, buried point verification can be automatically carried out based on the dynamic verification rule.

The invention discloses a network interface dynamic configuration method, electronic equipment, a storage medium and a program product, and relates to the technical field of computers, and the method comprises the following steps: obtaining a user interface configuration model and target terminal equipment characteristics, analyzing a model unit to construct a semantic tree and a response type configuration object, interface conversion is completed in combination with equipment features and a preset layout strategy to obtain an adaptive component instance, and incremental rendering is achieved through a virtual interface node tree. According to the method, interface configuration logic is abstracted and unified through a standardized model, accurate terminal matching is achieved through a multi-terminal adaptation rule, redundant operation is reduced through an incremental updating mechanism, traditional development limitation is broken through, the problems that network interface multi-terminal adaptation consistency is poor, development and maintenance cost is high, and updating response efficiency is low are solved, and the network interface multi-terminal adaptation consistency is improved. And the technical effects of improving the interface adaptation precision and the development efficiency, reducing the resource consumption and optimizing the user interaction experience are achieved.

The invention provides a method and a device for automatically detecting the injection-writing consistency of automobile drawings through computing power by an intelligent computing cloud platform, and relates to the technical field of intelligent computing cloud platforms and computing power infrastructure, the method comprises the following steps: constructing a sample data set based on a preset consistency semantic tree, and dividing the sample data set into a training set and a verification set; the intelligent computing cloud platform performs N times of iterative training on the initial model based on the training set by using computing power, and determines the initial model after the Mth time of iterative training as a final model; and deploying the final model on the intelligent computing cloud platform so as to carry out injection-writing consistency detection on the received automobile drawings in batches. Therefore, the model can accurately position the injection and writing position and identify the abnormal injection and writing in the automobile drawing based on the characteristics fully trained in the early stage, thereby reducing the understanding difference in the process of manually reviewing the injection and writing consistency of the automobile drawing, and improving the detection efficiency and accuracy.

The invention relates to a software function point identification method fusing a large model and multiple clustering analysis, and solves the problems of subjective deviation, inconsistent naming and low auditing efficiency caused by function disassembly depending on artificial experience in traditional function point measurement and calculation. The method comprises the following steps: inputting a design scheme, and constructing a document level semantic tree; obtaining feature information described by corresponding function points in the semantic tree, and analyzing the feature information to determine candidate function points; fusing the candidate function points according to semantic tree hierarchy alignment; and carrying out differentiation processing on the candidate function points, and carrying out duplicate removal on the similarity frequency according to the candidate function points to obtain the function points. According to the method, based on construction and analysis of a document hierarchy semantic tree, feature positions and large model reasoning ability are combined, and accurate extraction and auditing of function points are achieved. And differentiation is formed by adopting multiple clustering, and a co-cooperation relation matrix is constructed through clustering cross validation, so that the function point de-duplication accuracy is greatly improved.

The invention provides a method and system for querying a multi-source DPU flow table, a DPU cluster and computing equipment, and the method comprises the steps: receiving and analyzing a flow table operation statement which comprises a query target field and a filtering condition; converting the flow table operation statement into a structured semantic tree, and extracting the query target field and the filtering condition; according to the query target field, the filtering condition and DPU information obtained from a DPU information base, generating a flow table operation command of the corresponding DPU; respectively issuing the flow table operation commands of the corresponding DPUs to the corresponding DPUs to execute corresponding operations and obtain return values; and unifying the different return values as a final operation result of the logic flow table model field. According to the technical scheme, the problems that heterogeneous DPU flow table query modes are diversified, management is complex, and unified standard interfaces are lacked can be solved, the operation and maintenance efficiency is improved, the use threshold is lowered, and the consistency and intelligence of cross-manufacturer equipment flow table data management are enhanced.

The application discloses a large language model-based visual large-screen intelligent generation method and system, relates to the field of visual processing, and comprises the following steps: receiving a visual large-screen generation demand instruction, calling a large language model to generate an initial large-screen item containing multiple visual graph elements; receiving a modification instruction, determining the physical coordinates, layer depth and logical association relationship of all visual graph elements on the current canvas, and converting the same into a spatial semantic tree; inputting the combination of the modification instruction and the spatial semantic tree into the large language model to obtain a differential operation instruction set; analyzing the differential operation instruction set and applying the same to the current visual large screen; receiving a graph element redrawing instruction, determining whether there is a spatial conflict between the visual graph elements in the current visual large screen, and adaptively adjusting the positions of the visual graph elements that have the spatial conflict to eliminate the spatial conflict. The application can effectively guarantee the stability of the layout structure, graph element position and hierarchical relationship during the generation of the visual large screen.

The application provides a kind of text and video generation method and system based on cross-modal semantic mapping, it is related to data processing technical field, the method includes: step 1, input product description text, execute hierarchical semantic decoupling, extract core object noun, attribute adjective and scene adverb, and construct hierarchical structured semantic tree;Step 2, based on hierarchical structured semantic tree, execute the area exploration of fine-grained modifier semantics, identify the associated area of attribute adjective or scene adverb, generate semantic adaptation correction factor for each associated area.The application realizes the automatic generation of product description text to semantic precision, time sequence coherent dynamic video by hierarchical semantic decoupling, area semantic mapping, cross-modal feature fusion and dynamic space-time calibration, ensures that visual effect is consistent with text semantics.

The application relates to the technical field of security risk standardization management, and discloses a project intelligent management and analysis device based on security risk standardization, which comprises the following modules: a hierarchical semantic space representation model construction module, which constructs a multilevel semantic representation and outputs a hierarchical semantic tree; a meta-learning driven cross-domain mapping function construction module, which receives the hierarchical semantic tree and constructs a cross-domain mapping function to realize cross-domain knowledge transfer; a semantic hierarchical prototype network construction module, which receives the output of the cross-domain mapping function and maps a complex risk structure; a sample rapid adaptation implementation module, which realizes efficient knowledge transfer of the output of the construction module; a standardized risk knowledge base construction and application module, which receives the output of the sample rapid adaptation implementation module and realizes risk standardization and application; the application reduces the sample quantity and sample demand required for new field adaptation by combining meta-learning and a semantic hierarchical prototype network, and shortens the construction period of new field risk standardization.

The application discloses a kind of repair manual and assembly body multimodal semantic alignment method and system, it is related to artificial intelligence and computer aided design cross technical field, including respectively analyzing standard repair manual and CAD model, extract hierarchical structure, construct text semantic tree and CAD topological graph;Definition hyperbolic space model and its Riemann geometry operation rule;Text semantic tree and CAD topological graph are mapped into hyperbolic embedding vector using hyperbolic neural network respectively;According to the hyperbolic space model and hyperbolic embedding vector established, by minimizing hyperbolic contrast loss function and hyperbolic implication cone loss function, jointly optimize text encoder and CAD encoder;Geodesic distance and implication relationship are calculated in hyperbolic space, for realizing accurate positioning from text to CAD entity.The application uses the above method and system, realizes the full-process automation processing from original repair manual and CAD model to accurate semantic alignment.

The application provides a kind of intelligent computing cloud platform through computing power and carries out automobile drawing annotation consistency automatic detection method and device, it is related to the technical field of wisdom calculation cloud platform and computing power infrastructure, this method includes: based on the consistency semantic tree of pre-set sample data set is constructed, and the sample data set is divided into training set and verification set;Intelligent computing cloud platform utilizes computing power, based on the training set, the initial model is iteratively trained N times, and the initial model after the Mth iteration training is determined as the final model;The final model is deployed on the intelligent computing cloud platform to perform annotation consistency detection on the received batch of automobile drawings.This way, the model based on the characteristics of the early training can accurately locate the annotation position and identify abnormal annotation in the automobile drawing, reducing the understanding differences in the process of manual annotation consistency review of automobile drawings, improving the detection efficiency and accuracy.

The invention belongs to the technical field of power system automation, and particularly relates to a power grid dispatching instruction safety prevention and control method and system based on semantic analysis and multi-dimensional dynamic verification, and the method achieves the automatic semantic analysis and dynamic safety verification of a dispatching instruction through the technology of constructing a power grid knowledge graph and analyzing an instruction text to generate a structured semantic tree. The method supports the multi-dimensional conflict detection of the equipment state, the topological relation and the sequential logic, reduces the manual intervention proportion, and improves the verification accuracy and real-time performance.

The embodiment of the invention provides a text data extension method and device, and relates to the technical field of data processing. The method comprises the steps of obtaining an extension constraint condition corresponding to original text data; constructing an original semantic tree corresponding to the original text data; transforming the original semantic tree to obtain a transformed semantic tree; and expanding the text data corresponding to the transformed semantic tree based on the expansion constraint condition to generate expanded text data corresponding to the original text data. The embodiment of the invention is used for improving the quality of the expanded text data.

The application discloses a document query method and device, equipment, storage medium and computer program product, relates to the technical field of natural language processing, and the method comprises the following steps: generating a target user query based on a current user query input by a user and a historical question and answer pair sequence of the user; determining a target compressed text paragraph in a preset document semantic tree according to a target paragraph index matched by the target user query, the preset document semantic tree storing a mapping relationship between compressed text paragraphs in a target document and paragraph indexes; and generating a document query result corresponding to the current user query based on the target compressed text paragraph. According to the application, the compressed text paragraph can be matched in the document semantic tree according to the user query, and the document query result is generated based on the compressed text paragraph, so that the technical problem that the accuracy of the query result is not high due to the fact that the retrieved document paragraph exceeds the context processing capability of the model in the existing document query method is solved.

The embodiment of the invention discloses a historical dialogue management method and device based on a semantic tree and related equipment. The method comprises the following steps: acquiring a historical dialogue text, and performing entity extraction on the historical dialogue text to obtain an entity set comprising a plurality of entities; the entities in the entity set are clustered through a clustering algorithm, and a plurality of topic clusters are obtained; performing semantic recognition based on the historical dialogue text corresponding to each entity, determining an entity relationship among the entities in the topic clusters, and constructing a semantic tree corresponding to each topic cluster according to the entity relationship to obtain a semantic tree corresponding to each topic cluster; and receiving a question intention corresponding to the current question, performing matching with the theme cluster of the last historical dialogue based on the question intention, and performing reply content generation according to a matching result. According to the method, the intention of the user is understood, related entities are quickly positioned based on the semantic tree, wrong replies caused by information understanding deviation are avoided, and the user experience is effectively improved.

The invention relates to the technical field of electronic component fault diagnosis, and discloses an avionics equipment fault auxiliary diagnosis method and related equipment. Potential semantic association between hierarchical structures and chapters of technical documents is fully mined, fragmentation of retrieval contexts is avoided, meanwhile, multi-modal data such as texts and schematic circuit diagrams are effectively analyzed, cross reference and reasoning among different forms of data are established, and the interpretation requirements of avionics component fault diagnosis on the multi-modal documents are met. And the context is enhanced through retrieval result fusion and correlation score screening, so that the inconsistency of diagnosis hypothesis and original technical document facts is reduced, the illusion risk is reduced, and field experts are assisted to efficiently complete knowledge-intensive fault diagnosis tasks.

The invention provides a content auditing method and system based on multi-modal retrieval enhancement generation. The method comprises the following steps: collecting and preprocessing multi-modal data; mapping the preprocessed data to a security classification system constructed by a multi-level security semantic tree, and dynamically skipping to a corresponding level; marking, checking a marking result, generating a joint vectorization result, and constructing a multi-modal vector data set; clustering analysis is carried out, and an anti-fact comparison sample is generated according to each cluster to construct a comparison enhancement retrieval library; finely adjusting the first multi-modal model, encoding, inputting an encoding result into a comparison enhancement retrieval library for retrieval, and returning an anti-fact comparison sample; and constructing an enhanced prompt containing a context example, and generating a final auditing conclusion. According to the method, the text and the image are unified into the same semantic space to realize cross-modal retrieval of the most similar safe and unsafe samples. In the reasoning stage, similar samples are used as contexts to be embedded into prompts, a retrieval enhancement generation mechanism is formed, the illusion probability is remarkably reduced, and the auditing accuracy is improved.

A method for making predictions includes identifying, for each node in the heterogeneous graph structure, a set of node-target paths that connect the node to a target node; assigning, to each of the node-target paths, a path type identifier indicative of a number of edges and corresponding edge types in the associated node-target path; and extracting a semantic tree from the heterogeneous graph structure. The semantic tree includes the target node as a root node and defines a hierarchy of metapaths that each correspond to a subset of the node-target paths in the heterogeneous graph structure assigned to a same path type identifier. The semantic tree is encoded by generating a metapath embedding corresponding to each metapath in the semantic tree. A label is predicted for the target node in the heterogeneous graph structure based on the set of metapath embeddings.

The invention discloses a report generation system and method for intelligent analysis of multi-source data, and relates to the technical field of intelligent reports, and the system at least comprises a semantic analysis module which is used for carrying out intention recognition and semantic decomposition, generating a semantic tree and obtaining a semantic enhancement data source; the data modeling module generates a virtual data set; the visualization generation module generates a chart instance; the difference configuration management module carries out versioning management on the whole report configuration process and generates a version configuration difference package based on the editing state of the icon instance; the authority management module is used for generating an authority strategy so as to perform authority control on response data of the chart instance; the user-defined component module is used for responding to a chart component file of a user to generate a component instance and dynamically expanding a report; unified modeling and full-process automatic updating of multi-source data are achieved through cooperation of all the modules, the report generation efficiency is improved, meanwhile, full-amount refreshing is avoided, data safety and data conflicts are ensured, and the concurrent processing capacity and the overall throughput of the system are improved.

This application discloses a method for dynamic configuration of a network interface, an electronic device, a storage medium, and a program product, relating to the field of computer technology. The method includes acquiring a user interface configuration model and target terminal device characteristics, parsing model units to construct a semantic tree and responsive configuration objects, combining device characteristics and preset layout strategies to complete interface transformation and obtain adaptive component instances, and achieving incremental rendering through a virtual interface node tree. By standardizing the model to abstract and unify the interface configuration logic, achieving accurate terminal matching through multi-terminal adaptation rules, and reducing redundant operations through an incremental update mechanism, this method breaks through the limitations of traditional development and solves the problems of poor consistency in multi-terminal adaptation of network interfaces, high development and maintenance costs, and low update response efficiency. It achieves the technical effects of improving interface adaptation accuracy and development efficiency, reducing resource consumption, and optimizing user interaction experience.

The application relates to the technical field of three-dimensional modeling, in particular to a modeling method and system based on dynamic 3D targets, an electronic device and a storage medium, the method comprising: generating a three-dimensional modeling operation instruction, wherein the operation instruction at least contains an operation type, a target object identifier and a space scope parameter; constructing an operation semantic tree based on the operation instruction; detecting a space scope overlapping area by comparing a local operation semantic tree with a received remote operation semantic tree; applying a space-time dimension priority merging rule when the overlapping area is detected; executing the merged operation instruction and generating a binary log containing an operation semantic tree hash value; and performing a local rollback based on a differential CRC check value when an operation conflict is detected, wherein the differential CRC value is only calculated for the overlapping area data block. The application effectively solves the problems of semantic understanding loss, logical inconsistency and low recovery efficiency during three-dimensional space operation.