72 results about "Question analysis" patented technology

Provided in the present application is an intelligent question answering method based on a collaboration between a large language model and a knowledge graph, relating to the technical fields of artificial intelligence and natural language processing, the method comprising: decomposing a complex question into a plurality of simple questions, and analyzing the degree of association between the simple questions and a basic function so as to form a multi-hop reasoning path; automatically extracting structured information from the simple questions on the basis of a multi-task learning framework of a large model, so as to construct a knowledge graph; and constructing a cumulative reasoning learning framework on the basis of a logic reasoning large model, and performing iterative verification on a process result formed by the knowledge graph on the basis of the multi-hop reasoning path, so as to correct the reasoning path until a correct answer is inferred.

The invention provides a mathematical question and answer process teaching system, which comprises a user interaction module, a question analysis and standardization module, a cognitive diagnosis engine, a generative teaching module, a mathematical knowledge graph database and a user portrait database, teaching content and guiding questions are presented to the user in a multi-mode form; the question analysis and standardization module is used for performing semantic understanding and structured analysis on mathematical questions and generating standardized question description and at least one standard question solving path; according to the method, the structured reasoning of the knowledge graph is combined with the natural language generation ability of the generative AI, so that a closed loop from'problem solving 'to'diagnosis' to'heuristic teaching 'is realized, thinking blockage points of students can be accurately positioned and personalized tutoring can be provided like human teachers, and the learning efficiency and the autonomous thinking ability are remarkably improved.

The invention discloses an RAG and knowledge graph question-answering method and system for security classification and grading of cross-border data, and belongs to the crossing field of big data security management, artificial intelligence and compliance technologies. The method comprises the following steps: step S101, receiving and preprocessing user input; step S102, performing question analysis and semantic intention recognition; step S103, intelligent scheduling control decision making; step S104, reasoning and executing the knowledge graph; step S105, performing RAG generation reasoning execution; step S106, performing intelligent fusion and decision traceability; step S107, carrying out multi-dimensional visual display; step S108, audit record and report generation; and S109, updating the dynamic knowledge. The method has the advantages of intelligent question and answer, multi-source fusion, sustainable evolution, traceability of the whole process and the like, and can be widely applied to compliance management and intelligent decision-making scenes related to data cross-border flow, such as enterprises, governments, finance, medical treatment and the like.

The invention provides a multi-modal large model combined question analysis and explanation generation method and system, and relates to the technical field of multi-modal learning, and the method comprises the steps: carrying out the standardization processing of a multi-modal input question, and obtaining the standardized question data; separating structured question information to perform deep feature extraction, driving three-level knowledge structure linkage matching of the question solving thought library, and generating a plurality of initial question solving paths; performing knowledge blind area coverage screening, and positioning a target problem solving path; recursive knowledge point reinforcement is carried out, and a non-blind area credible problem solving chain is generated; step-by-step analysis logic derivation is carried out, and a target analysis logic framework is output; and performing cross-modal directional rendering according to real-time explanation modal selection, and delivering and outputting a multi-modal analysis explanation stream. The technical problems that in the prior art, deep understanding of personalized requirements and knowledge mastering levels of users is lacked, customized answers cannot be provided for the users, and the learning effect of the users and tool practicability are affected are solved.

The invention discloses a dialogue generation method and device, a customer service system, a storage medium and a program product, and the method comprises the steps: receiving request data inputted by a user, and carrying out the data preprocessing of the request data; performing intention analysis and emotion detection on the preprocessed request data to obtain user intention information and a user emotion state; performing data search on the user intention information to obtain problem analysis data; generating an initial reply text according to the user intention information and the question analysis data; and adjusting the initial reply text based on the emotional state to obtain a dialogue text. By adopting the embodiment of the invention, the intention and the perception emotional state of the user can be accurately analyzed, and multi-modal interaction is realized by fusing multi-element information, so that real-time response and efficient solution of questions of the user are realized.

The invention discloses an intelligent question analysis and calibration method based on a multi-modal large model, and relates to the technical field of image processing, and the method mainly comprises the steps: firstly, carrying out the OCR processing of an input multi-modal question picture, and generating structured OCR data containing coordinates, types and subject attributes through a general OCR engine in combination with a subject exclusive recognition plug-in; performing question region identification and segmentation by taking the data as a drive, and establishing a correlation graph among a whole question region, an answering region and an auxiliary region; a reference answer matched with the question type is generated based on the OCR data; further generating deep answer analysis taking the OCR information as a tracing basis in combination with the OCR data and the reference answer; and finally, based on the analysis result, the answer and the OCR data, generating a quantitative scoring standard by taking the analysis integrity, the answer correctness and the data use accuracy as standards. According to the invention, full-automatic processing from multi-modal topic picture input to final quantitative scoring standard generation is realized.

The invention relates to a method and system for relieving large model illusion, and belongs to the technical field of computers. The method comprises the following steps: identifying and analyzing the intention of a question input by a user through a first-level agent, and judging whether an answer is obtained by calling a local knowledge base, a search engine or the capability of a large model; if a search engine is called, pulling the question through a first-level agent, and inputting the content of each webpage, website information, the question input by the user and a prompt cue word into a large model to obtain an answer, wherein the previous set number of webpages are related to the content inquired by the search engine; if a local knowledge base is called, analyzing the question through a secondary agent and generating a query instruction corresponding to the question, performing interactive query with professional databases of industries to which at least two questions with different query modes belong through the query instruction to obtain a query result, and inputting the question input by a user, a prompt prompt word and the query result into a large model to obtain an answer; if the capacity of the large model is called, an answer is obtained through the large model according to the question.

This invention discloses a knowledge graph-based intelligent question-and-answer method for audit guidance, relating to the field of digital auditing. Through knowledge graph framework design and ETL data warehouse technology, this invention extracts, cleans, and transforms audit business data relevant to business environment optimization audits, achieving the fusion of various business data to provide data support for intelligent question-and-answer. By constructing an intelligent question-and-answer system, and designing a multi-task-oriented approach based on real-world audit scenarios, it utilizes word segmentation, matching, and query modules to achieve knowledge graph-based intelligent question-and-answer for business environment optimization audit guidance. This reduces the workload of the audit process, freeing auditors from tedious and repetitive tasks, allowing them to focus more on risk identification, problem analysis, and root cause analysis, effectively improving audit efficiency and quality.

The application discloses a knowledge base question answering method and system under full-process large language model small sample learning, the method comprises the following steps: question analysis, identifying candidate triples and question types of original user questions through a large language model; query template generation, generating a knowledge base query statement template with placeholders for user questions; knowledge base linking, obtaining matched expressions for the placeholders in the query statement template in combination with a large language model and an entity information index that has been constructed; answer generation, generating a knowledge base query language and returning a final result. Through the small sample learning capability of the large model, the retrieval process is redesigned for the knowledge base question answering task, a model does not need to be trained separately, and the question answering process is simplified; through the powerful knowledge reserve of the large model, the question answering effect and generalization capability are improved.

The invention provides a metadata-driven intelligent log analysis system and method, and the system comprises a dialogue interaction module which is used for extracting a technical problem proposed by a user; the keyword extraction and query module is used for carrying out keyword extraction, service attribute labeling and query on the technical problem based on the service metadata pre-identifier; the query statement dynamic construction module dynamically constructs a query statement and performs log data query; the time conversion module performs context conversion on the keyword query result and the log data query result based on a time sequence, and outputs a final log query result; and the hierarchical structured RAG module performs context structured processing on the query result and the technical problem, and outputs a final solution through large model analysis. According to the method, natural language question input is supported, the use threshold is remarkably reduced, accurate retrieval of operation and maintenance data and business context enhancement are achieved through collaborative association of keywords and metadata, and the accuracy of question analysis is improved.

The application provides a large model-based intelligent question analysis method, device and equipment and a storage medium. The application performs step-by-step semantic analysis on a question through a thinking chain reasoning framework, simulates a complete thinking process of a human being from understanding a problem to disassembling a structure, breaks through the limitation of only making sequence translation in the prior art, and significantly improves the accuracy of complex SQL generation. A multi-layer progressive retrieval mechanism is adopted, thinking chain information is used to drive focusing from a business scene to field association layer by layer, the retrieval result is ensured to be highly matched with the query requirement, a dynamically generated personalized SQL sub-template is used, and the adaptation capability for an unseen question is greatly enhanced. A multi-dimensional feature vector integrating semantic similarity, structural complexity and business matching degree is constructed, adaptive selection of a decoding strategy is realized, an optimal generation path can be used in different complexity scenes, and efficiency and quality are taken into account.

The invention relates to the technical field of Internet, and discloses a strategy content co-creation method and system based on artificial intelligence, and the method comprises the steps: displaying a content analysis page used for AI strategy note co-creation and aiming at a target analysis object; in response to a questioning trigger operation on the analysis questioning component, displaying questioning analysis content corresponding to the target analysis object on the content analysis page; displaying a note editing page used for AI strategy note co-creation; and in response to an editing trigger operation on the note title editing component, displaying the policy note title content in the note title area, and / or in response to an insertion note trigger operation for the question analysis content, displaying the question analysis content in the note body area to obtain a target co-created policy note. Therefore, the generation accuracy, the generation reliability, the generation efficiency and the generation convenience of the target co-creation strategy note can be improved, so that the co-creation experience of the user on the strategy note is improved.

An object of the system according to the embodiment is to allow a viewer to ask a question in real time during network broadcasting and obtain an answer on the spot.SOLUTION: A system according to an embodiment includes a dialogue reception unit, a data analysis unit, and an answer generation unit. The dialogue reception unit receives a question from a viewer. The data analysis unit analyzes data on the basis of the question received by the dialogue reception unit. The answer generation unit generates an answer based on the data analyzed by the data analysis unit.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to uncover users' latent needs and contribute to improving the quality of services. [Solution] The system according to the embodiment comprises a collection unit, a generation unit, an analysis unit, and a proposal unit. The collection unit collects user attribute information. The generation unit generates questions based on the information collected by the collection unit. The analysis unit analyzes the answers obtained from the user based on the questions generated by the generation unit. The proposal unit makes specific improvement suggestions based on the analysis results obtained by the analysis unit.

The system according to the embodiment aims to enable users to enjoy conversations with historical figures. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit receives a question from a user. The analysis unit analyzes the question received by the reception unit. The generation unit generates an answer based on the result of the analysis by the analysis unit. The provision unit provides the answer generated by the generation unit.

An object of the system according to the embodiment is to quickly and appropriately answer questions asked by students in a recorded class video.SOLUTION: A system includes a question input unit, an analysis unit, an answer generation unit, and a provision unit. The question input part inputs a question from the student. The analysis unit analyzes the question input by the question input unit. The answer generation unit generates an answer based on the question analyzed by the analysis unit. The providing unit provides the answer generated by the answer generating unit to the student.SELECTED DRAWING: Figure 1

We provide the system. [Solution] A voice acquisition means that captures the user's voice and saves or processes it as digital data, A speech recognition means that converts acquired audio data into text data, A question analysis tool that understands the intent of a question recognized as text data and generates an appropriate answer, A response generation means that creates an appropriate answer based on question analysis, A speech generation means that synthesizes the generated text-formatted response as audio data, A means of providing a response to the user by providing the generated audio data, A system that includes this.

This invention discloses a hierarchical perception-based method and system for analyzing complex English sentences, relating to the interdisciplinary fields of natural language processing and intelligent education. By defining structural delimiters, sentences are divided into syntactic levels according to the number of effective delimiters, first eliminating invalid parallel structural delimiters; then, a syntactic encoding module completes text segmentation, hierarchical tagging, word embedding, and feature fusion; a hierarchical perception module calculates feature weights and generates target syntactic features; finally, a syntactic decoding module outputs the sentence's main body and modifier decomposition results. The hierarchical framework constructed by this invention fully covers the core modifiers of English, is suitable for the scenario of complex sentences in the College Entrance Examination (Gaokao), and can achieve accurate and lightweight decomposition of all types of complex sentences. It effectively solves the problems of irregular decomposition, poor generalization, and poor adaptability of traditional methods, and the analysis process is clear and teachable.

An object of a system according to an embodiment is to provide an appropriate and human-like answer to a user's trouble or question.SOLUTION: A system includes a reception unit, an analysis unit, a generation unit, and an interaction unit. The reception unit receives a question from a user. The analysis unit analyzes the question received by the reception unit. The generation unit generates an answer based on the question analyzed by the analysis unit. The interaction unit proceeds with an interaction based on the answer generated by the generation unit.SELECTED DRAWING: Figure 1

Embodiments of the present disclosure relate to a five-question summary for problem analysis in observability systems. Systems, methods, apparatuses, and computer program products for generating a five-question analysis method to perform root cause analysis in a computer environment. A method can include receiving a set of related entities associated by a topology, receiving at least one parameter associated with the set of related entities, determining a correlation of the related parameters, generating a correlation score for each event, and constructing a prompt configured for a large language model.

An object of the system according to the embodiment is to provide highly reliable information and solve user's questions and troubles.SOLUTION: A system includes a question analysis part, an information provision part, and a reliability evaluation part. The question analysis unit analyzes a question of a user. The information providing unit provides information based on the question analyzed by the question analysis unit. The reliability evaluation unit evaluates reliability of the information provided by the information providing unit.SELECTED DRAWING: Figure 1

The application belongs to the technical field of artificial intelligence and food safety information, and discloses a question and answer system of a meat product whole-chain safety knowledge graph based on deep learning, which is composed of a knowledge graph construction module and a system question and answer module; wherein the knowledge graph construction module comprises a data acquisition unit, a data processing unit, an entity recognition unit, a relationship extraction unit, a critical control point selection unit and a knowledge graph construction unit; the system question and answer module comprises a user question analysis unit, a query statement generation unit, a standard answer generation unit and an intelligent question and answer Web system construction unit. The question and answer system of the meat product whole-chain safety knowledge graph based on deep learning is adopted, a more easy-to-use and more intelligent natural language question and answer system is developed by constructing the meat product whole-chain safety knowledge graph, and finally the professional, scattered and complex meat product safety knowledge is efficiently, accurately and friendly provided to the end users.

The present specification provides a knowledge graph-based target reporting data processing method, device and server, which can be used in the field of artificial intelligence. When a user encounters a target problem related to target reporting while processing target reporting business, the user can initiate a target query request to the server. The server receives and responds to the target query request, first distinguishes different problem types, and according to the problem type, adopts a matching mode to process the target problem text carried by the target query request to obtain a corresponding target problem analysis result; then according to the target problem analysis result, a corresponding target query sentence matched with the target knowledge graph is constructed through semantic slot extraction; and then according to the target query sentence, the target knowledge graph is queried to timely feed back the corresponding target answer text to the user. Thus, the processing difficulty of the user in processing the target reporting business can be effectively reduced, and the user can be assisted to efficiently and accurately complete the related target reporting business.

An object of a system according to an embodiment is to enable a student to quickly obtain an answer to a question.SOLUTION: A system includes a question analysis part, an answer generation part, a lesson generation part, a progress tracking part, and a feedback provision part. The question analysis unit analyzes a question of a student. The answer generation unit generates an answer to the question analyzed by the question analysis unit. The lesson generation unit generates the individual lesson based on the answer generated by the answer generation unit. The progress tracking unit tracks the progress of the lesson generated by the lesson generation unit. The feedback providing unit may provide feedback based on the progress tracked by the progress tracking unit.SELECTED DRAWING: Figure 1

The system according to the embodiment aims to provide a prompt and appropriate answer to a user's question. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, a generation unit, and a provision unit. The reception unit receives a user's question. The analysis unit analyzes the question received by the reception unit. The generation unit generates an answer based on information analyzed by the analysis unit. The provision unit provides the answer generated by the generation unit.

The invention discloses an atropine myopia prevention and control evidence-based dialogue method and system, and belongs to the technical field of prevention and control data intelligence. The method comprises the steps of question analysis: performing semantic analysis on a received user question; retrieval of evidence-based evidences: performing retrieval enhancement according to a semantic analysis result, and obtaining the evidence-based evidences and sources and levels of the evidence-based evidences from the atropine myopia prevention and control knowledge graph; inference chain generation: combining evidence-based evidences with cues, and guiding the model to generate inference chain content according to the steps of individual core feature analysis, atropine prevention and control scheme matching, safety evaluation and scheme optimization through a thinking chain CoT; and answer generation: according to the evidence-based evidence and the reasoning chain content, generating different types of atropine myopia prevention and control answers. According to the method and the device, the matching between each core entity in the output atropine myopia prevention and control scheme and individual requirements is improved, and the accuracy of the atropine myopia prevention and control scheme is improved.

The system according to this embodiment aims to conduct fair and objective recruitment based on the skills and aptitudes of candidates. [Solution] The system according to the embodiment comprises a document analysis unit, an interview support unit, an answer analysis unit, and a job offer decision unit. The document analysis unit analyzes the candidate's documents. The interview support unit generates interview questions based on the results analyzed by the document analysis unit. The answer analysis unit analyzes the candidate's answers based on the questions generated by the interview support unit. The job offer decision unit makes a job offer decision based on the results analyzed by the answer analysis unit.

The invention relates to the technical field of artificial intelligence and data processing, and provides a structured display method and system for a reasoning process in interface generation, computer equipment and a storage medium. The method comprises the following steps: obtaining an interface design cue word input by a user and carrying out demand disassembly to generate a structured analysis result containing a demand type, style constraint and functional requirements; obtaining an original reasoning data stream of the large model, identifying a stage conversion flag bit, and automatically mapping reasoning content to a preset problem analysis stage, a creative direction thinking stage or a design scheme arrangement stage; feature items are extracted based on the domain feature library and extracted as core key points by using a semantic concentration algorithm; and synchronously presenting the key points and the progress animation according to a logic sequence, and constructing an increment cue word based on an adjustment instruction to trigger local reasoning update. Structured reconstruction and visualization of large language model reasoning logic are achieved, and the problem that the interaction response performance and the resource utilization rate are limited is solved.

To provide a system capable of realizing effective presentation.SOLUTION: The system includes an information inputting means, a material generating means for automatically generating a presentation material based on inputted information using a AI model, an evaluating means for checking the generated material and guaranteeing an appropriate design and expression, a displaying means for displaying the checked material, an avatar generating means for performing a pre-practice of the presentation and simulating an actual presentation partner, a feedback generating means for analyzing a result of the pre-practice and generating a feedback, a progress managing means for monitoring a progress of the presentation in real time during the presentation and providing an alert and a notification, and a question analyzing means for analyzing a question during the presentation and generating an appropriate answer.SELECTED DRAWING: Figure 1

An object of a system according to an embodiment is to accurately estimate the age of a pet and obtain information for providing appropriate care.SOLUTION: A system includes a photograph analysis unit, a question analysis unit, and an age estimation unit. The photograph analysis unit analyzes the photograph of the pet. The question analysis unit analyzes an answer to a simple question. The age estimation part integrates the analysis results of the photograph analysis part and the question analysis part to estimate the age of the pet.SELECTED DRAWING: Figure 1