56 results about "Specialized knowledge" patented technology

A computer-implemented system for automated document generation receives user input and processes it through artificial intelligence models to create professional documents. The system combines user-provided information with specialized knowledge databases containing domain-specific requirements and formatting standards to generate enhanced processing instructions. Trained machine learning models process these instructions to produce contextually appropriate content that addresses specific technical and legal requirements. The generated content is formatted using configurable templates to create completed documents that meet professional standards. The system provides adaptive user interfaces that adjust functionality based on user expertise levels, supports multiple operational modes including guided and automated generation, learns from example documents to improve output quality, and enables comprehensive workflow management through network-accessible services. Applications include patent applications, legal responses, technical documentation, and other specialized professional documents requiring domain expertise and regulatory compliance.

The invention relates to the technical field of semantic understanding, in particular to a special knowledge base fragmented slicing and semantic understanding answer matching method, which comprises the following steps of: obtaining document table images, identifying, segmenting and marking as a fragment set, generating a layered weight sequence by combining question comparison condition obligation and consequence aging reasoning, and obtaining a semantic understanding result; the method comprises the following steps of: identifying and segmenting a text to generate a fragment set, analyzing a connection relationship to form a trajectory link, segmenting candidate answers and performing semantic alignment to supplement missing, calculating a score accumulation result according to a weight sequence, adjusting a parameter sequence and priority, and generating and outputting an optimized answer, and comprises the following steps of: identifying and segmenting the text to generate the fragment set, comparing question contents with conditional obligations and combining consequence aging reasoning; a weighted logic chain is formed, a fragment connection relation dominantly constructs a link, candidate answers are segmented, tracks are aligned, a missing part dependency relation is supplemented, semantic precise alignment is performed on the whole, reasoning is coherent and complete, answer coverage is comprehensive, the integrating degree and precision are improved, and effectiveness and integrity in a complex scene are enhanced.

The invention discloses a preoperative discussion record automatic generation method and system based on a knowledge graph and natural language processing. The system automatically obtains multi-modal data from an electronic medical record, inspection and image system, and carries out standardization processing in combination with doctor input; medical entity recognition and relation extraction are realized through natural language processing, and a patient digital portrait is constructed; reasoning and calling a dynamic template engine based on the specialized knowledge graph, and generating a personalized preoperative discussion record; the generated content has interpretability, a doctor can modify and confirm, and continuous optimization is realized by system record feedback. The system is composed of a data input module, a data processing module, an intelligent generation module, an interactive display module and a learning optimization module. According to the method, intelligent, standardized and personalized generation of the preoperative discussion record is realized, and the writing efficiency and the medical safety are improved.

The invention discloses a retrieval enhancement generation method and device based on an obstetrics and gynecology specialized knowledge base. The server side method comprises the following steps: in response to a retrieval request sent by a client side, preprocessing a current retrieval demand description text carried by the retrieval request and a cached historical retrieval demand description text to obtain a plurality of retrieval keywords; semantic retrieval is conducted according to each retrieval keyword and a preset RAG vector knowledge base, document content meeting the retrieval request is obtained, and the preset RAG vector knowledge base is generated on the basis of a dynamically-updated gynecologic and obstetric specialist knowledge base; inputting the plurality of retrieval keywords and the document content into a generation model which is finely adjusted in advance to generate an answer text corresponding to the retrieval request; and outputting an answer text corresponding to the retrieval request, and sending the answer text to the client. Therefore, by the adoption of the method and device, the model can understand the semantic and logical relation of the context, the model can generate information conforming to the fact, and therefore the accuracy of system retrieval is improved.

An object of a system according to an embodiment is to efficiently and accurately extract data without expert knowledge.SOLUTION: A system includes a data extraction condition input part, an SQL generation part, a mart definition cooperation part, and a customization part. The data extraction condition input unit allows a user to input a data extraction condition in a chat form. The SQL generation unit generates an optimal SQL query based on the extraction condition input by the data extraction condition input unit. The mart definition association unit associates the SQL query generated by the SQL generation unit with the mart definition to reflect the latest definition. The customization unit performs customization for each company.SELECTED DRAWING: Figure 1

The invention discloses a knowledge base dynamic construction and intelligent retrieval method based on a large model, and relates to the technical field of computer retrieval, a DeepSeek large model is taken as a teacher model, a lightweight student model is trained through a specialized knowledge distillation strategy, and local deployment is realized in combination with a containerization technology; the specialized knowledge distillation strategy comprises dynamic modal perception distillation, knowledge graph structure guide distillation and online incremental distillation; according to the method, the overall process efficiency is remarkably improved compared with a traditional scheme through multi-modal data automatic processing and lightweight model local deployment; cross-modal semantic alignment and joint reasoning are realized, and the accuracy of retrieval and answer generation is improved; a real-time updating mechanism and version management enable knowledge to always meet actual requirements, and the logic contradiction occurrence rate is remarkably reduced; the fact reliability of the generated content is greatly improved by a fact anchoring and double-stage verification mechanism; local deployment and containerization isolation design avoid leakage of sensitive information, and meet the requirements of data security compliance.

The invention relates to a large-model-based future quantitative back-testing method and system, and the method comprises the steps: constructing a future quantitative knowledge base for the field of future based on the construction logic of a FinDKG dynamic knowledge graph; performing enhanced training on the open source large language model through a GRPO enhanced training algorithm by taking improvement of the generation capability of the futures quantification code of the large language model as a target; and under a context retrieval enhancement generation framework combined with ACE and RAG, according to the obtained user natural language and the futures quantification knowledge base, generating a futures quantification code through the trained open source large language. According to the method and the device, a complete and executable quantitative backtest code, a specialized knowledge base of futures, algorithm fine tuning and an ACE + RAG framework can be automatically generated by relying on a large language model and enabling a user with a non-professional programming background to describe strategy requirements through a natural language, so that the intelligence and the accuracy of model code generation are greatly improved.

The system according to the embodiment aims to enable experts to promptly and appropriately consult on specialized knowledge. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, and a provision unit. The reception unit receives consultation content from an expert. The analysis unit analyzes the consultation content received by the reception unit. The provision unit provides related expertise based on the information analyzed by the analysis unit.

We provide the system. [Solution] A means for a person with specialized knowledge to input that knowledge and speaking style as information, A method for training an AI model using natural language processing technology based on that input information, A means of storing and making available trained AI models on the platform, A means for users to search for AI models through the platform and begin interacting with them, A means by which an AI model generates a response to that AC input and sends it back to the user, A means of providing responses as an interactive learning experience and enhancing immersion through visual and auditory means, A system that includes this.

Personalizing the services offered enables the delivery of services that are tailored to the user's needs. [Solution] When a user is engaging in a conversation with a dialogue model for general conversation (S235-S246, NO in S247, NO in S249), the system switches to the task processing model to engage in conversation depending on the content of the conversation (NO in S247, S248), enabling the use of the task processing model's specialized knowledge in a particular field. Furthermore, through conversations with individual users by the dialogue model, the dialogue model is personalized to suit the individual user (YES in S245, S246).

The system according to the embodiment aims to generate database queries efficiently and accurately and extract data without requiring specialized knowledge. [Solution] A system according to an embodiment includes a reception unit, a generation unit, an execution unit, a linking unit, and a customization unit. The reception unit receives data extraction conditions from a user. The generation unit analyzes the conditions received by the reception unit and generates an efficient SQL query. The execution unit executes the SQL query generated by the generation unit and extracts data. The linking unit updates the data extracted by the execution unit based on the latest data definition. The customization unit supports customization for each company.

The invention discloses a simulation behavior rule automatic generation system based on knowledge graph and data fusion, a processor and a storage medium, and relates to the technical field of building energy consumption simulation and artificial intelligence. A behavior pattern mining module mines and constructs a Meta Event database from original time sequence data; the knowledge extraction module generates general knowledge through multi-stage intelligent filtering, screening and extraction; the field specialization module compiles the general knowledge into a modeling blueprint and generates specialized knowledge; the hierarchical knowledge graph construction module constructs a knowledge graph, and processes and stores general knowledge and specialized knowledge based on the hierarchical knowledge graph; and the knowledge-data offline fusion module carries out matching, calibration and entity interpretation on the behavior rules in the knowledge graph and a database to generate a fusion behavior rule base. According to the method, the literature theory, the measured data and the physical entity are systematically fused, so that the automation degree, the interpretability and the data fidelity of simulation model configuration are remarkably improved.

The invention relates to the technical field of intelligent nursing, and discloses a disease intelligent nursing auxiliary system based on evidence-based data, comprising: an evidence-based knowledge base module integrating multi-source evidence-based data to form a specialized knowledge graph; the model training optimization module carries out base model field fine tuning and multi-algorithm fusion according to the multi-source evidence-based data so as to carry out intelligent decision-making assistance and generate a personalized nursing scheme; the multi-scene intelligent interaction module carries out knowledge pushing, consultation and question answering through multi-terminal interaction; the full-period nursing management module performs staged nursing execution and dynamically adjusts a nursing plan; the quality control early warning module carries out risk early warning, medication verification and flow quality control; and the multi-dimensional effect evaluation module generates a multi-level evaluation report, and drives update of the evidence-based knowledge base and algorithm iteration. According to the invention, an accurate and adaptive whole-cycle nursing scheme and standardized guidance are provided, the nursing risk is reduced by means of real-time quality control early warning, and the treatment compliance and medical experience of a patient are improved.

To provide a system for enabling anyone to easily execute digital marketing without expert knowledge.SOLUTION: Means for receiving a merchandise concept from a user, means for automatically generating a delivery scenario in a AI based on the received merchandise concept, means for automatically generating advertisement content in the AI based on the automatically generated delivery scenario, means for adjusting the generated content and delivery scenario by a designer, means for detecting legal risks and conformity to brand guidelines of the advertisement content using the AI and presenting the detected legal risks and conformity to the brand guidelines to a legal department, means for delivering the generated advertisement content to influential target users and performing an AB test, means for evaluating delivery results with a BI tool and measuring CTR, CVR, and ROI, and means for analyzing evaluation results with the AI and improving the delivery scenario and the content.SELECTED DRAWING: Figure 1

This system provides support to help users without specialized knowledge of nurse call system paging devices recover from malfunctions. [Solution] When the maintenance terminal 2 receives an abnormality detection notification for any of the call devices 91 from the main unit 8 of the nurse call system 7, it displays the device ID of the call device 91 and the details of the abnormality (no response, delayed response, error message, etc.) included in the abnormality detection notification, and prompts the maintenance manager to select a recovery procedure for the call device in which the abnormality was detected from among several recovery procedures that are stored in advance. The maintenance terminal 2 then transmits the selected recovery procedure, along with the abnormality detection notification, to the support terminal 3 installed in the waiting area (nurse center, etc.) of the users (doctors, nurses, caregivers, etc.) who use the nurse call system 7. In response, the support terminal 3 displays the device ID of the call device 91 and the details of the abnormality included in the abnormality detection notification, along with the recovery procedure.

An object of the system according to the embodiment is to effectively appeal the approach to the SDGs without expertise.SOLUTION: A system includes a collection unit, an analysis unit, and a generation unit. The collection part collects business contents and basic information. The analysis part analyzes the information collected by the collection part and analyzes the activity contents of the enterprise. The generation part selects an activity target and generates a template on the basis of a result analyzed by the analysis part.SELECTED DRAWING: Figure 1

To allow for appropriate data analysis without expert knowledge or experience.SOLUTION: A data analysis system according to an embodiment comprises: a reception unit which receives input of a request related to execution of analysis of data stored in a prescribed storage unit, in a natural language, from a terminal device used by a user; a processing unit which converts the natural language related to the request received by the reception unit into a machine-readable wording and performs processing according to the request on the basis of the converted machine-readable wording to obtain a response to the request; and a responding unit which converts the response into the natural language and returns the response to the terminal device.SELECTED DRAWING: Figure 6

To provide a professional 3D asset generation support system for producing a 3D asset only by text input even without advanced expertise such as a 3D engineer.SOLUTION: The automatic 3D asset generation support system 10 selects a 3D asset template from the database 30 based on the text information input to the user prompt 20, generates a 3D asset from the selected template and the generated parameters by the AI, and modifies the generated 3D asset by adding text information to the user prompt 20 so that the AI modifies the parameters of the selected 3D asset template or the AI selects a 3D asset template different from the selected 3D asset template and generates the parameters of the template to modify the 3D asset.SELECTED DRAWING: Figure 1

An object of the system according to the embodiment is to propose a personal computer configuration optimal for the needs of a user without expert knowledge.SOLUTION: A system according to an embodiment includes a needs collection unit, an analysis unit, a proposal unit, a customization unit, and an estimation unit. The needs collection unit collects needs of a user. The analysis unit analyzes the needs collected by the need collection unit. The proposal unit proposes an optimum PC configuration based on the need analyzed by the analysis unit. The customizing section provides customization options based on the personal computer configuration proposed by the proposing section. The estimating unit calculates an estimated amount based on the customization option provided by the customizing unit.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to enable agents with specialized knowledge of the business to respond quickly and appropriately to employees' questions and inquiries. [Solution] The system according to this embodiment comprises a learning unit, a reception unit, and a provision unit. The learning unit learns knowledge specific to the business. The reception unit receives questions and consultations based on the knowledge learned by the learning unit. The provision unit provides appropriate advice based on the questions and consultations received by the reception unit.

Embodiments of present disclosure relate a method for providing maintenance information for a robot at a maintenance system. The maintenance system includes a coordinator agent and a plurality of tooling agents. In the method, a coordinator agent receives a query from a user as a prompt. The query relates to maintenance information about the robot and / or applications of the robot. The coordinator agent selects at least one of the plurality of tooling agents based on the maintenance information. The coordinator agent interacts with the at least one tooling agent to answer information in response to the query. The coordinator agent provides the answer information to the user. In this way, the user can interact with the maintenance system using plain language without specialized knowledge.

The system according to the embodiment aims to generate musical scores based on music data without requiring specialized knowledge, and to apply for permission from the copyright holder. [Solution] The system according to the embodiment comprises a reception unit, an analysis unit, a generation unit, and an application unit. The reception unit uploads music data. The analysis unit analyzes the music data uploaded by the reception unit. The generation unit generates a musical score based on the data analyzed by the analysis unit. The application unit submits a permission request to the author based on the musical score generated by the generation unit.

An object of the system according to the embodiment is to efficiently make a patent application without expertise.SOLUTION: A system includes a patent information learning part, an interaction part, an image determination part, a format generation part, and a cooperation part. The patent information learning unit learns patent information. The interaction unit performs interaction with a user. The image determination unit determines an image related to a design. A format generation part generates a format for patent application. The cooperation unit cooperates with the patent office.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to effectively share data and know-how from each project within a corporate group and to provide optimal advice and solutions. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, and a provision unit. The collection unit collects data and know-how from each project within the corporate group. The analysis unit analyzes the data collected by the collection unit to understand specialized knowledge and the history of the project. The provision unit provides optimal advice and solutions based on the analysis results obtained by the analysis unit.

An object of a system according to an embodiment is to collect information from a plurality of data sources without expert knowledge and visualize data in response to a request from a user.SOLUTION: A system according to an embodiment includes a data collection unit, a prompt analysis unit, and a data visualization unit. The data collection unit collects market data, public information, and in-house closed data. The prompt analyzer analyzes a user's prompt based on the market data, the public information, and the in-house closed data collected by the data collector. The data visualization unit visualizes the data based on the prompt analyzed by the prompt analysis unit.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to enable users to find reliable options even without specialized knowledge. [Solution] The system according to the embodiment comprises a reception unit, a review unit, a comparison unit, and a proposal unit. The reception unit receives information about options from the user. The review unit reviews the information received by the reception unit and presents highly reliable options. The comparison unit compares the options presented by the review unit and displays their advantages and disadvantages. The proposal unit proposes the option best suited to the user's situation and needs based on the information displayed by the comparison unit.

An object of the system according to the embodiment is to generate an answer that is easy for anyone to understand regardless of the age and living environment of the user and the presence or absence of expert knowledge.SOLUTION: A system includes an age optimization part, a living environment optimization part, a technical term optimization part, a dialect optimization part, and an easy-to-understand answer generation part. The age appropriateness section uses the generated AI to select an appropriate language or word in accordance with the age of the user. The living environment optimizing section selects an appropriate language or word in accordance with the living environment of the user. The technical term adjustment unit generates an answer in easy-to-understand words while avoiding technical terms and difficult expressions. A dialect optimization part generates an answer by adopting the dialect of an area where the user lives. The easy-to-understand answer generation unit generates an answer that is easy for anyone to understand regardless of the age and living environment of the user and the presence or absence of expert knowledge.SELECTED DRAWING: Figure 1

Disclosed herein are systems and methods for aggregating knowledge from a plurality specialized knowledge models (KMs). In one aspect, an exemplary method includes: receiving a query; analyzing the query to determine that the query is directed to different subject matter areas; selecting a plurality of specialized KMs each having respective expertise in one of the different subject matter areas of the query; generating a first sub-query directed to the first subject matter of the query and a second sub-query directed to the second subject matter of the query; transmitting the first sub-query for processing by the selected first specialized KM; obtaining a first response from the first specialized KM based on the first sub-query; transmitting the second sub-query and the first response from the first specialized KM for processing by the selected second specialized KM; and generating an aggregated response from the second specialized KM.

To create an environment where computing resources can be utilized without requiring specialized knowledge. [Solution] The system includes means for authenticating a user based on input information from a terminal, means for receiving and storing a program for providing computing resources uploaded by the user, means for analyzing the stored program and optimizing it to improve computing efficiency, means for executing the optimized program in a high-performance computing environment, and means for making the execution results available to the user.

The system according to the embodiment aims to enable data analysis, graph visualization, and policy planning without requiring specialized knowledge. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, a graph generation unit, and a policy proposal unit. The reception unit receives input of data. The analysis unit analyzes the data received by the reception unit. The graph generation unit generates a graph based on the data analyzed by the analysis unit. The policy proposal unit proposes a policy based on the graph generated by the graph generation unit.