11 results about "Knowledge object" patented technology

The invention discloses a data consanguinity link determination method and device based on a large model, relates to the technical field of big data processing, and mainly aims to solve the problems of poor accuracy and low efficiency of existing data consanguinity link generation. Comprising the steps that a knowledge base is called, and the knowledge base comprises technical knowledge information and business knowledge information; a knowledge object is obtained from the knowledge base according to a preset verification strategy, the knowledge object is analyzed based on a large model, a blood relationship link analysis result is obtained, and the knowledge object is at least one piece of knowledge key information formed based on the technical knowledge and / or the business knowledge information; and performing service verification on the blood relationship link analysis result, and generating a data blood relationship link based on a verification result.

This application provides a generative knowledge object extraction method and system based on context learning, relating to the field of generative artificial intelligence technology. The method includes: preprocessing the target text by encoding it using a first Transformer encoder in a dual-tower structure to obtain a target vector; traversing and matching the target vector in a pre-stored vector library to obtain a target matching vector, where the target matching vector corresponds to a target example; combining the target text and the target example to form a target structured input prompt; and under the constraint of the target structured input prompt, a generative knowledge object extraction model extracts and analyzes the target text to obtain the target extraction result. This application can solve the technical problem of poor accuracy in entity recognition results of existing generative entity recognition models, achieving the technical effect of improving the accuracy of generative named entity recognition models.

This disclosure provides a method, computing device, computer program product, and computer-readable storage medium for constructing a knowledge graph of medical literature. The method includes: extracting multiple granularity knowledge objects from the medical literature using a medical domain-specific cue word template-driven large language model, wherein the multiple granularity knowledge objects include entities, relationships between entities, and declarations of each entity and / or relationship; determining key excerpts from the medical literature for each knowledge object using a progressively narrowing matching algorithm based on preceding and following anchor points; and classifying the knowledge objects according to the key excerpts of each knowledge object and the context of the corresponding medical literature using a predefined evidence-based medicine hierarchy to generate a knowledge graph of the medical literature.

The application provides a kind of spent fuel reprocessing process knowledge object processing method, device and equipment, wherein the method comprises: obtaining at least two knowledge objects in spent fuel reprocessing process;The knowledge object includes: at least one spent fuel reprocessing process, at least one equipment corresponding to the spent fuel reprocessing process, at least one process parameter corresponding to at least one equipment of the spent fuel reprocessing process;According to at least two knowledge objects, obtain the knowledge graph chromosome population of spent fuel reprocessing process;According to the preset algorithm, obtain the target chromosome individual vector of the knowledge graph chromosome population;According to the target chromosome individual vector, adjust the preset knowledge base of spent fuel reprocessing process, and obtain the target knowledge base.The application scheme improves the optimization ability of reasoning and problem solving of knowledge object in spent fuel reprocessing process, and improves the efficiency of spent fuel reprocessing process.

The invention discloses a cultivated land quality data standardization packaging method and system based on Internet of Things and metadata, and relates to the technical field of agricultural informatization and data management, and the method comprises the following steps: S1, a data acquisition and primary packaging step: acquiring original monitoring data from at least one Internet of Things monitoring device deployed in cultivated land; and in response to the obtained original monitoring data, calling a metadata template pre-associated with the type of the Internet of Things monitoring equipment. According to the cultivated land quality data standardization packaging method and system based on the Internet of Things and the metadata, it is ensured that complete identity, time-space and context information is bound at the beginning of the generation of the data, the unification of the data format and the source of description is achieved, and a data machine is endowed with understandable clear semantics and rich dimensions; the data is evolved into a knowledge object which can be correlated and reasoned from a pure numerical value, and the problem in farmland quality multi-source heterogeneous data integration is effectively solved.

The application discloses a traditional Chinese medicine meridian and acupoint immersive teaching method and system based on three-dimensional modeling, relates to the technical field of three-dimensional modeling, and comprises the following steps: in response to a teaching display instruction, setting a lightweight neural network model on a teaching terminal, analyzing a 3D human body point cloud to be rendered, and constructing a meridian topology network; identifying meridian and acupoint knowledge objects based on the meridian topology network, combining a preset parameterized human body model, monitoring changes in bone joint poses and muscle envelope shapes, performing grid offset, generating a target skin area, and triggering a teaching interaction instruction; in response to the teaching interaction instruction, acquiring virtual interaction data, introducing a preset teaching rule engine, acquiring the positioning accuracy level of the meridian and acupoint and acupuncture actions, performing correction determination in combination with an abnormal operation event, and acquiring corrected three-dimensional modeling information; and the application improves the accuracy of acupoint positioning and the satisfaction of immersive teaching.

The application relates to the technical field of computer data processing, and discloses a code and non-code resource bidirectional mapping and consistency maintenance method and system, which can effectively decouple tasks and codes, and can maintain a strong semantic association and an automatic synchronization mechanism between the tasks and the codes. The method stores source codes and task descriptions in first and second storage spaces which are physically independent and logically associated by configuration, generates a globally unique association identifier, and realizes cross-space entity mapping through metadata marking. An automatic collaborative engine is configured to monitor changes in real time, and trigger an intelligent semantic processing module to perform cross analysis. Task constraint conditions are analyzed to dynamically generate verification logic in the first storage space, or code change characteristics are analyzed to automatically generate structured knowledge objects in the second storage space.

A computerized system for generating digital response documents includes a knowledge repository database of digital knowledge objects, an ingestion subsystem configured to process source materials into structured digital request objects, an object management subsystem configured to generate digital strategy objects based on those inputs, and a response generation subsystem configured to construct annotated outlines and populate response documents using outputs from a large language model (LLM) in response to non-user generated prompts.

A system receives a plurality of knowledge objects (KOs). The system receives repository structure definition information, the repository structure definition information specifying one or more repository structure definitions that define respective structures for the one or more data repositories. The system groups the plurality of KOs based on the name, type, and tag attributes of the KOs, and storage paths of the underlying unit of structured, semi-structured, and unstructured data at the one or more data repositories corresponding to the KOs to generate a number of groups of KOs. For each group in the groups of KOs, the system determines a count of KOs in the group. The system generates multiple mapping structures with M to N relationships between the groups of KOs to the one or more repository structure definitions, the mapping relationship including the count of associated KOs.

The embodiment of the invention discloses an environment early warning collaborative response method, device and equipment based on a traffic agent. A specific embodiment of the method comprises the following steps: acquiring a persistent multi-source environment data set from multi-source environment monitoring equipment; preprocessing the persistent multi-source environment data set to obtain a standard multi-source environment data set; performing single-point feature extraction and spatial association on the standard multi-source environment data set to obtain a multi-source environment data feature set; determining an environment event knowledge object based on a preset judgment rule base, the standard multi-source environment data set and the multi-source environment data feature set, and executing cascade early warning measures based on the environment event knowledge object; and based on the multi-source environment data feature set, determining a derivative high-risk scene, and based on the derivative high-risk scene, executing a traffic cooperative response measure. According to the embodiment, the effects of avoiding excessive reduction of passing efficiency or resource waste, reducing secondary accident risks and reducing casualties are achieved.

The application provides a petrochemical industry large model retrieval enhancement processing method and system. The method comprises the following steps: performing semantic unit segmentation, graphic element analysis, working condition slicing and object identification alignment on various data to generate a standardized industrial knowledge object set; constructing an industry knowledge base associated with process topology domain, control logic domain, risk event domain and system version domain based on the standardized industrial knowledge object set; receiving a retrieval enhancement request, analyzing to obtain object entities, behavior intentions, time constraints and safety levels, and generating a query semantic skeleton; performing error correction re-retrieval according to the retrieval quality evaluation result to generate a candidate evidence cluster; determining a target evidence cluster, generating a candidate response based on the target evidence cluster and a preset constraint, and performing interlocking conflict verification, process boundary verification and system applicability verification on the candidate response, and outputting a retrieval enhancement processing result. The application can improve retrieval accuracy, enhance working condition version adaptability and improve output safety.