20 results about "Semantic technology" patented technology

The invention relates to the technical field of voice semantics, and discloses an information interaction method and device based on multi-agent collaboration, equipment and a medium, and the method comprises the steps: generating a target workflow through a large language model and a current user demand; determining a target AP I according to the target workflow, and generating initial interaction information; and generating current reply evaluation information based on the initial interaction information and the criticizing agent, and determining the initial interaction information as target interaction information under the condition that the current matching degree is greater than or equal to a matching degree threshold value. Through the above mode, the user demand is split through the routing agent and the built-in large language model, the target workflow is generated, and the method adapts to complex and changeable task scenes. According to the method, the target AP I is determined through the induction agent, and the initial interaction information is generated, so that the efficiency and accuracy of calling the AP I are improved, and the performance of an automatic business process system for processing complex interaction information in the fields of financial science and technology, medical treatment, health, old-age care and the like is improved.

The invention relates to the technical field of voice semantics, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a sign language animation generation method, device, equipment and medium based on semantic parse. The sign language animation generation method comprises the steps that voice input is received and recognized as text content, field semantic parse is conducted on the text content to generate a field semantic template, and the field semantic template is used for generating a sign language animation; and converting the domain semantic template into a sign language intermediate representation sequence, generating a three-dimensional sign language action sequence based on the sign language intermediate representation sequence, rendering the three-dimensional sign language action sequence into a virtual image sign language animation, and displaying the virtual image sign language animation. According to the invention, by fusing speech recognition, semantic analysis and three-dimensional action rendering, direct conversion from spoken language content to sign language animation is realized, and a complete visual expression link from speech to sign language is formed, so that a user can intuitively understand the speech content in a sign language form through a virtual image, and the user experience is improved. Therefore, the barrier-free performance of human-computer interaction and the accuracy of information transmission are improved.

The invention relates to the technical field of voice semantics, and discloses a dialogue intention recognition method and device based on a large model, equipment and a medium, and the method comprises the steps: recognizing a target first-level intention label of a target query text through SFT; determining a target knowledge block according to the knowledge base and the target first-level intention label; and determining a dialogue intention according to the RAG and the target knowledge block. Through the above mode, effective preliminary intention recognition is performed on the target query text through the SFT, the target first-level intention label is determined, the target second-level intention label is accurately determined in combination with the preset knowledge base and the RAG model, the intention recognition accuracy and fineness are improved, and the intention recognition efficiency is improved in the second-level intention recognition process. The method can focus on the knowledge content highly related to the target query text, and reduces the burden of processing irrelevant information by the RAG model. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the user intention recognition accuracy of the intelligent customer service system is improved.

The invention relates to the technical field of voice semantics, and discloses a cue word generation method and device based on large model optimization, equipment and a medium, and the method comprises the steps: carrying out the fitness evaluation of an initial cue word, and generating all comprehensive fitness scores; performing semantic crossover processing and semantic variation processing on the parent cue word to generate a child cue word; and according to the comprehensive fitness score, the offspring cue word and the initial cue word population, generating a target cue word population. By means of the mode, the cue word variant positioning optimal solution is explored through multi-target fitness evaluation and a population evolution mechanism, and it is ensured that cue words are professional. A large language model is introduced to perform semantic crossover and semantic adjustment on understanding of semantic content of parent cue words, so that child cue words inherit effective information and keep smooth. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the accuracy of an intelligent customer service system for understanding complex semantics and generating cue words is improved.

The invention relates to the technical field of speech semantics, and discloses a context-based multi-modal data generation method, device and equipment and a medium, and the method comprises the steps: carrying out the semantic segmentation of context text information through a semantic recognition model, and determining a target semantic tag; multimedia materials are obtained, association is carried out according to the multimedia materials and the context text information, and initial multi-modal data are generated; and generating target multi-modal data according to the initial multi-modal data and the multi-modal data template. According to the mode, the target semantic label of the context text is extracted through the preset semantic recognition model, the text subjected to voice transcription is dynamically associated with the multimedia material according to the semantic label, and the multi-modal data integrating the image-text, the audio and the video is generated, so that a user only needs natural dialogue and does not need typewriting or complex operation, and the user experience is improved. In the business fields of financial science and technology, medical health, old-age care and the like, the interaction efficiency between the intelligent voice interaction system and the user is improved.

The invention provides a power equipment-oriented standard semantic knowledge base retrieval method, which comprises the following steps of: acquiring power equipment standard data, analyzing text information of the power equipment standard data, establishing semantic association among standard terms, equipment attributes and key indexes, and forming an equipment-standard-index knowledge graph; standard terms are calculated through a semantic vectorization technology, and matching calculation of the standard and equipment suitability is carried out based on a vector retrieval method; and according to the standard historical data and the deep learning model, carrying out evolution analysis on the standard terms, and providing suitability recommendation of the equipment standard. By establishing the semantic association between the equipment and the standard terms, efficient and accurate standard suitability recommendation and evolution analysis are realized, and efficient and accurate equipment standard suitability recommendation is provided through a semantic technology and a deep learning model.

The invention discloses an industrial technology bottleneck identification method based on science and technology service big data driving, and relates to the technical field of science and technology services, and the method comprises the steps: obtaining to-be-analyzed industrial multi-source heterogeneous data through a data collection interface; respectively extracting a text semantic feature vector, a technical association feature vector and a statistical feature vector; fusing the multi-modal features through an attention fusion mechanism; on the basis of the comprehensive feature representation, probability distribution of the industry on various potential technical bottlenecks is calculated through a bottleneck recognition model; and generating an identification result of the industrial technology bottleneck according to the probability distribution. The method has the advantages that by constructing a multi-modal analysis framework fusing scientific and technical literatures, patent networks and industrial statistical data, comprehensive perception of deep semantics, technical association and macroscopic trends is realized, and the recognition precision and comprehensiveness are remarkably improved; and dynamic, accurate and operable intelligent support is provided for industrial technology layout and research and development decision.

A subject-event method and a workflow engine developed based on it are designed for no-code creation and execution of semantic models of business processes and construction of domain ontologies. The operation of the workflow engine is based on original event semantics using the semantic implementation of a dataflow approach to algorithm execution. The use of a unified event data format made it possible to implement: (1) a specification for describing actions and entities, (2) a semantic workflow engine for executing business processes, (3) a semantic temporal data store. The invention provides a unified platform for enterprise content management, process automation, and knowledge base maintenance, addressing the limitations of traditional workflow engines and semantic technologies.

The application provides a medical search recommendation method, system, product and terminal based on a knowledge graph and a semantic vector. The medical search request input by a user is subjected to medical entity recognition and standardized processing to obtain standard medical entity data. On the one hand, based on the standard medical entity data, a pre-constructed medical knowledge graph is used to perform retrieval reasoning to obtain a first retrieval result set. On the other hand, based on the standard medical entity data, a pre-trained semantic vector model and a vector database are used to obtain a second retrieval result set. According to a preset fusion rule, the first retrieval result set and the second retrieval result set are subjected to fusion processing to obtain a recommendation result. The application effectively breaks the limitations of the existing medical retrieval technology, and through double-path collaborative fusion, the defects of the vector semantic technology in lacking explicit medical logic support and the semantic generalization of the knowledge graph being insufficient are compensated for, so that precise, interpretable and safe medical search recommendation is finally achieved.

It is an object of the present invention to define a single abstract hierarchy data model using semantic techniques to manage different applications and to automate, if necessary, the process of generating interoperability rules. Further, it is desirable to provide an intuitive user interface that develops a natural and intuitive way to explore ontologies for a user, while shielding the user from technical aspects such as performing SPARQL queries. According to the invention, this object is achieved by a method for providing an intuitive user interface in at least one MOM system which controls the manufacturing environment of an autonomous plant, the method comprises the steps of: a) encoding manufacturing domain knowledge for an autonomous plant in an equal weighted co-control network of an extensible and configurable ontology, b) defining the ontology of the MOM domain by semantic conceptualization of the manufacturing domain knowledge; c) providing a web-based framework to create an intuitive user interface for navigating the ontology and associating concepts included in the ontology with logical data structures from existing applications included in the MOM system, wherein: c1) the user interface is capable of enabling a user to select an ontology and search concepts associated with the ontology that the user is interested in using public terms; c2) the user interface can also provide a list of concepts matching the corresponding search; c3) the user interface can also enable the user to select at least one concept from the list of concepts and provide a list of entities relating to the selected concept; c4) the user interface can also enable the user to select at least one entity from the list of entities and provide a visualization of the selected entity; and c5) the user interface can also enable a user to select a plurality of entities in the manufacturing domain that refer to the same concept, thereby generating a transformation rule to process logical data structures across said plant and / or domain with respect to the selected entities in the manufacturing environment of the autonomous plant.

Embodiments of the present disclosure disclose a method and device for querying building data and synthetic data. The specific implementation of the method comprises: extracting a graph embedding vector from input building-related graph data, and storing the graph embedding vector into a vector database and storing the graph data into a graph database; converting a question related to the graph data into a question embedding vector, and searching for a target vector similar to the question embedding vector in the vector database; generating a query instruction in a predetermined language based on the target vector through a first large language model; executing the query instruction in the graph database to determine a query result; and outputting a natural language answer to the question based on the query result through a second large language model. The implementation realizes efficient querying of complex building data and reduces the user's dependence on professional knowledge of semantic technology.

Systems and methods for search execution, which can involve generating labels and keywords from a search query with a Named Entity Recognition (NER) model; executing classification logic on the labels and keywords from the search query to determine a corresponding search logic; executing the corresponding search logic to generate search results associated with scores; combining the scores of the search results for each of the labels to generate a ranking of the search results; and providing the ranked search results in response to the search query.

In order to cope with the challenges of data explosive growth and heterogeneous data integration and utilization in the scientific research field, an innovative device integrating intelligent deep analysis, verification and automatic claiming of heterogeneous data of scientific research achievements is invented. According to the method, knowledge graph, artificial intelligence and semantic technologies are fused, standardization, integration and deep analysis of heterogeneous scientific research data are achieved, the data governance level is improved, and data interoperability is promoted. According to the device, knowledge structured representation is constructed by utilizing a knowledge graph, and achievements of different sources are associated; data is deeply analyzed by means of artificial intelligence, key information is extracted, and accuracy is verified; and a semantic technology is introduced to eliminate semantic differences, and data docking is realized. Through technical collaboration, scientific research achievements can be automatically attributed, and the management efficiency and accuracy are improved. The research and development of the system improve the scientific research data management efficiency, provide a convenient tool for researchers, promote interdisciplinary communication and cooperation, promote scientific research data opening and sharing, follow the FAIR principle, accelerate scientific discovery, and provide new power for scientific research and innovation.

The invention relates to the technical field of speech semantics, and discloses a speech synthesis method, device and equipment for hierarchical emotion condition control and a medium, and the method comprises the steps: extracting three layers of acoustic feature vectors through a feature extraction model, and determining three layers of emotion distribution; generating to-be-synthesized text information through the original text information; and synthesizing the three-layer emotion distribution and the to-be-synthesized text information to generate target synthesized voice information. By means of the mode, the hierarchical emotion distribution is constructed by generating the three-level timestamps and extracting the acoustic feature vectors. The quality problem caused by alignment error accumulation is eliminated through a speech synthesis model, three-layer emotion distribution and to-be-synthesized text information are fused through a cross attention mechanism, and intensity values of phonemes, words and sentences are adjusted. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the voice synthesis accuracy of a voice synthesis system in combination with user emotion is improved.

It is therefore an object of the present invention to define a method of managing a single abstraction layer data model of different applications using semantic techniques and to automate the process of generating interoperability rules among different manufacturing sites. According to the invention, this object is achieved by a method for enabling an MOM system for an autonomous plant by encoding manufacturing domain knowledge in an equal-weighted co-control network of extensible and configurable ontologies, said method comprising the following steps: a) defining an ontology of the MOM domain by semantic conceptualization of manufacturing domain knowledge; b) representing the ontology by at least one mapping knowledge domain; c) implementing the ontology in an owl format; d) providing a web-based framework to provide a set of intuitive user-friendly user interfaces for navigating the ontology and associating concepts included in the ontology with logical data structures from existing applications included in the MOM system; e) mapping the logical data structures by semantic conceptualization semantic matching, f) generating interoperability codes between the data structures of the different applications, thereby mapping the data structures of the different applications within the same MOM system and / or over a plurality of distributed MOM systems of the autonomous plant.

The invention relates to the technical field of voice semantics, and discloses an emotion perception and cross-language dialogue information generation method and device, and the method comprises the steps: extracting a current discrete voice unit sequence and a current emotion feature vector; multi-modal emotion joint representation is generated through an extended vocabulary library and an attention fusion mechanism; and according to the multi-modal emotion joint representation, generating a target voice signal, and based on the context cache pool and the target voice signal, generating interactive dialogue information. By means of the mode, the multi-mode emotion joint representation is generated by extracting the discrete unit sequence and the emotion feature vector, and the emotion state of the user is captured while the semantic content is understood. And multiple rounds of dialogues fusing semantics and emotions are generated by means of an attention mechanism. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the accuracy of dialogue information generation by an intelligent interaction system in combination with user emotion and cross-language cross-mode is improved.

The invention relates to the technical field of speech semantics, and discloses a speech generation method and device based on a self-guiding diffusion model, equipment and a medium, and the method comprises the steps: generating a semantic mark sequence; generating a Mel spectrogram according to the coarse-grained diffusion model, the fine-grained diffusion model and the semantic marking sequence; and generating target voice information through a feature conversion technology and the Mel spectrogram. By means of the mode, the weakening semantic guiding model and the main semantic prediction model work cooperatively, self-guiding enhancement is carried out in the semantic mark generation process, and the generation probability of wrong semantic marks is reduced. Through self-guiding optimization of coarse-grained and fine-grained two-stage diffusion models, hierarchical refined generation of speech features is realized, fine noise easily generated by a traditional single diffusion model is avoided, and the method can be applied to the business fields of financial science and technology, medical treatment, health, old-age care and the like, and has a wide application prospect. And the reliability of converting the text information into the voice information by the intelligent customer service system is improved.

The invention discloses an artificial intelligence visual system based on semantic archiving and an application method thereof, the system breaks through the calculation limitation of a traditional end-to-end generation model, and efficient content generation and recognition are achieved through modular visual fragment recombination. The system comprises a data acquisition unit which acquires multimedia data from various heterogeneous data sources, wherein the multimedia data comprises a static data set, a real-time video stream and 3D rendering data; the semantic segmentation unit adopts edge detection and a clustering algorithm to decompose multimedia data into visual fragments with semantic meaning, and the visual fragments comprise spatial metadata, confidence information and edge compatibility descriptors; the vector quantization unit converts the visual fragments into compact numerical vector representation by extracting a color histogram, LBP texture features and geometric moments; the hierarchical labeling unit adds multi-level semantic metadata and technical metadata for the visual fragments, the semantic metadata is organized according to a hierarchical classification method structure, and the technical metadata defines contact edges and assembly rules to support intelligent recombination; the semantic technology archiving unit adopts a double index mechanism to store and retrieve visual fragments with metadata, and supports hash retrieval based on semantic tags and similarity search based on technical descriptors; the multi-modal retrieval unit uses a semantic-technology score fusion algorithm to sort the candidate segments; the intelligent assembly unit recombines the selected fragments based on predefined topology rules and consistency constraints; the selective refinement unit applies GPU-assisted local optimization processing only at the fragment connection points. According to the system, a new visual processing normal form based on semantic memory and fragment modularization recombination is achieved, the calculation load is remarkably reduced, the large-scale retraining requirement is eliminated, and efficient visual generation and recognition in a real-time application environment are supported.

The application discloses a method and device for identifying multilayer semantic advanced threat knowledge, namely, the application proposes a multilayer semantic advanced threat knowledge description framework, the method combines STIX threat data element standards and ATT&CK technique and tactics knowledge framework, utilizes semantic technology to construct a perfect advanced threat knowledge framework, establishes a set of relatively universal network threat ontology knowledge model which has practicability and expansibility, provides a unified behavior model architecture for complex and changeable attack behaviors such as APT attacks, and thus can comprehensively describe the knowledge model of threat intelligence field knowledge information in a multiregion knowledge sharing and standardized scene to cope with changeable network threat scenes.

The application discloses a kind of multimodal depth semantic fusion integrated machine system and method, system uses integrated design, including hardware base, fusion engine, enable platform and scene application relevant module, hardware base provides heterogeneous computing, high-speed storage and interconnection resources, fusion engine realizes multi-channel semantic understanding, depth fusion decision and resource elasticity scheduling, enable platform provides visual configuration and model management tool, scene application module provides industry application template;Method generates intermediate semantic result by parallel processing multiple source heterogeneous input, generates structured instruction by multidimensional confidence evaluation and tree fusion decision, realizes system closed-loop optimization in combination with interactive feedback;The application realizes depth collaboration of software and hardware and private deployment, solves the problems of complex deployment, insufficient adaptation, multi-source information fusion difficulty and data security risk etc. of traditional semantic technology.