1527 results about "Relevant information" patented technology

A user provides a question to be answered from detailed, dense or otherwise complex documents to a processing system that converts the question to a structured query language query and generates an embedding from the question, augmented by temporal data, synopses, themes, or other relevant information or data. The embedding is compared to embeddings generated from documents of a knowledge base to identify documents that are relevant to the question, and to rank such documents for their relevance. Highly ranking documents are combined with the query and provided to a language model that returns an answer to the question. A source for the answer is identified in at least one of the documents. The answer and the identified documents are presented to the user.

The invention relates to the technical field of power systems and automation thereof, in particular to a distribution network auxiliary decision-making method and system considering source load fluctuation relevance and a medium. The method comprises the following steps: firstly, collecting related information of a distribution network area, quantifying a synchronization and hysteresis association rule of multi-source heterogeneous data fluctuation, and constructing a composite feature vector and a standardized risk perception data set; defining a state space and an action space of a reinforcement learning algorithm based on the composite feature vector, and realizing auxiliary decision-making optimization of the distribution network; constructing a scene feature library, calculating the fluctuation relevance similarity between a new scene and a historical scene, and multiplexing a deep reinforcement learning model architecture and carrying out transfer learning; building a power grid digital twinborn simulation platform, designing evaluation indexes, generating candidate schemes, deducing the candidate schemes, selecting recommendation strategies and storing the recommendation strategies in a strategy knowledge base.

The invention relates to the technical field of digital factory production management, and discloses a digital factory-oriented multi-target production plan optimization method and system, and the method comprises the steps: decomposing an enterprise order into a plurality of subtasks through a production task decomposition module, and extracting related information; the resource dynamic evaluation module collects data in real time to generate a resource state matrix; the multi-objective optimization algorithm module constructs a model and adopts an improved non-dominated sorting genetic algorithm to solve; the dynamic priority distribution module adjusts the priorities of the sub-tasks according to the real-time data; and the conflict resolution unit is used for solving resource allocation conflicts. The method can accurately decompose tasks, evaluate resources in real time, collaboratively optimize multiple targets, flexibly deal with abnormities, efficiently resolve conflicts, comprehensively improve the production efficiency and benefits of the digital factory, and effectively solve the complex problems in the production plan making and optimizing process of the digital factory.

The invention relates to the technical field of network security, in particular to a network security analysis method and system based on big data. Comprising the following steps: collecting related multi-source heterogeneous data of a network, and carrying out standardized processing such as cleaning and de-noising; network analysis is carried out based on the preprocessed data, network traffic is analyzed in real time by using machine learning and deep learning algorithms, and abnormal conditions are detected; constructing a risk prediction model according to a network analysis result and related information, and predicting a future network security risk level; if the risk level exceeds the threshold value, determining a security event source and a responsibility subject through data tracing; and finally, generating a safety response strategy according to risk prediction and data traceability results, and performing disposal. The corresponding system covers the modules of data acquisition, preprocessing, network analysis, risk prediction, data tracing, security response and disposal and the like, and all the modules work cooperatively to form a complete network security analysis and guarantee system, so that the stable operation of the network system is guaranteed.

The invention relates to the technical field of artificial intelligence, and provides a retrieval joint optimization method for a retrieval enhancement generation system, which comprises the following steps: constructing a knowledge base and a vector library of a large language model, and obtaining an input problem of a user; performing keyword matching and similarity comparison on the input question and a knowledge base and a vector base of the large language model, and extracting text blocks from the knowledge base according to a result to obtain an initial retrieval candidate set; extracting related information in the initial retrieval candidate set and the large language model, and generating an initial external related information block set and an internal related information block set; performing progressive information verification on the initial external related information block set to obtain an external related information block set; the internal related information block set and the external related information block set are integrated, conflict information is removed, and a final retrieval result is generated; and sending the input question of the user and the final retrieval result to the large language model, and generating a corresponding answer by the large language model. The accuracy of large language model output can be improved.

Techniques for logical text passage generation and retrieval for retrieval-augmented generation. The techniques involve processing markup language documents to generate logical text passages and their corresponding embeddings. These embeddings are indexed for efficient retrieval. Upon receiving a user utterance, a user query is formed and transformed into an embedding to query the index. Relevant text passages are identified and used to prompt a large language model (LLM), which generates a completion. This completion is then sent as a response to the user. The process effectively bridges user queries with relevant information through advanced embedding and natural language processing techniques, enabling accurate and contextually appropriate interactions within a user-agent dialogue framework.

The invention discloses a virtual historical character dialogue method and system with role knowledge and context awareness, and relates to the technical field of man-machine interaction, and the method comprises the steps: constructing a multi-level role depth model; when a question of a current user is received, identifying information of a virtual scene where the current user is located, analyzing micro-expressions of the face of the user and voice rhythm characteristics of speech of the user, analyzing an emotional state and an interaction intention of the user based on a multi-modal fusion algorithm, and generating a user state vector; executing a dynamic Prompt construction program, extracting related information from the multi-level role depth model and the user state vector, and generating a structured Prompt; and inputting the structured Prompt into a large language model, generating a reply text conforming to role features based on questions of the current user, and driving a virtual character model. The method solves the problem that in the prior art, virtual historical figures cannot provide real immersion and credible interactive experience with emotional connection.

The invention discloses an intelligent question answering system based on a large language model and a knowledge base, and particularly relates to the technical field of artificial intelligence application, comprising a large language model module, a knowledge base module, a retrieval and matching module, an answer generation module and a user interaction module; according to the method, on the basis of a pre-trained large language model and a structured knowledge base, key entities and semantic intentions in user questions are extracted through a multi-level text analysis technology, and preliminary answers are generated; the system combines domain knowledge in a knowledge base, uses vector retrieval and a graph database to efficiently retrieve related information, dynamically fuses retrieval results and generates answers through an attention mechanism and a gating mechanism, and ensures logic consistency and fact accuracy. The system supports multi-modal input and output, and realizes continuity of multiple rounds of dialogues through a memory network; user feedback data optimizes system performance through strategy gradient, and continuously improves answer quality and field adaptability.

A method of controlling a broadcast receiver and which includes displaying a broadcast program on a screen of the broadcast receiver, determining if a broadcast-related information enlargement mode is selected, and enlarging the broadcast-related information on the screen of the broadcast receiver when the determining step determines the broadcast-related information enlargement mode is selected.

Systems are provided for implementing methods for generating and processing fix suggestions for alerts produced by code analysis tools. The methods involve receiving an alert, parsing the alert to identify relevant information, and assembling a prompt for a Large Language Model (LLM). The prompt includes a general description of the problem, a description of the alert message, a source-code location, and a request for a proposed fix to the alert. The prompt is sent to the LLM, and a response is obtained. The response includes a proposed fix comprising a set of edits to be applied to the source code and / or configuration files. The response is processed and validated, and a fix suggestion is assembled and provided based on the response. The fix suggestion includes a natural language explanation of the proposed fix, suggested source-code changes, and selectable options for accepting, rejecting, and editing the fix suggestion.

The embodiment of the invention relates to a reply text generation method and device, computer equipment and a storage medium. After an input text is preprocessed, a target text is obtained; acquiring context information corresponding to the target text, a first prompt word template and a first keyword; retrieving related information corresponding to the input text from a first database according to the input text, the context information, the first cue word template and the first keyword to obtain a retrieval result; generating cue words of a large language model according to the input text, the context information, the first cue word template, the first keyword and the retrieval result; and inputting the cue word into the large language model to output the reply text through the large language model. Therefore, after the input text is combined with the context information, the cue word template of the industry and the keyword to retrieve the related information, the cue word of the large language model is generated according to the retrieval information, the reply text is accurately generated through the large language model, and the question and answer accuracy and the user satisfaction degree are improved.

The invention relates to a method, a system and equipment for generating a large model SQL (Structured Query Language) based on business domain semantic enhancement and multi-round voting. The method comprises the following steps: acquiring a natural language input by a user to recognize and judge a business field related to user query; performing semantic annotation and expansion on the input query; organizing related information into Prompt, inputting the Prompt into a large language model, and generating an SQL statement; generating a plurality of candidate SQL statements, and selecting the candidate SQL statements with the highest occurrence frequency as output; and submitting the finally output SQL statement to an actual database system for execution, and returning and displaying a query result. Through the technologies of business domain division, data structure semantic annotation, multi-round candidate generation, voting screening and the like, SQL generation accuracy and system robustness of natural language query are remarkably improved, query intentions and field constraints in business scenes of enterprises such as banks and the like can be accurately recognized, field matching errors are avoided, and the query efficiency is improved. And through multi-round iterative generation and consistent voting screening, the correctness and stability of the output SQL statement are ensured.

The invention discloses a traffic state monitoring method and system fusing video image recognition and charging data, and the method comprises the steps: obtaining multi-source traffic data, carrying out the preprocessing of the multi-source traffic data, and generating preprocessing data; identifying the pre-processed data to generate vehicle related information; fusing and matching the preprocessed data and the vehicle related information to generate fused traffic data; analyzing the fused traffic data to generate traffic state information; a traffic management and decision support result is generated, and real-time congestion early warning and traffic accident early warning are provided; and mining and analyzing the historical traffic data to generate a traffic flow rule and accident rule analysis result. According to the invention, comprehensive, accurate and real-time monitoring and analysis of the traffic state are realized, powerful support is provided for traffic management and decision making, and the problems of difficult integration of multi-source data, insufficient real-time performance and coverage of state monitoring and imbalance of decision support and cost efficiency are solved.

Methods and systems for retrieving relevant information in response to an input question. The method includes obtaining text content related to the input question and partitioning the content into one or more paragraphs based on predefined rules. The method further involves extracting one or more evidence spans that are relevant to the input question by inputting the text content and the question into a trained language model. A semantic search is then performed on both the paragraphs and the extracted evidence spans, ranking the candidate passages based on their relevance to the input question. Each candidate passage may comprise either a paragraph or an evidence span that addresses the question. The disclosed methods and systems improve the quality and relevance of retrieved information by combining heuristic-based content partitioning with machine learning-based evidence extraction.

The invention relates to the field of artificial intelligence, in particular to a long text segmentation information retrieval result coherence enhancement method, system and equipment based on a knowledge graph, and the method comprises the following steps: receiving a long text input by a user; segmenting the long text into a plurality of segments according to a preset length, and recording the original position and sequence of each segment; performing named entity recognition on each fragment, and extracting a key entity; querying related information in a knowledge graph according to the key entity, and obtaining attributes of the entity and a relationship between the attributes; integrating the related information obtained by query into the corresponding text fragment to form a context enhanced fragment; receiving a user query request; calculating a correlation score based on the context enhanced fragment and the user query, and retrieving a related text fragment by using a hybrid retrieval strategy; and selecting the related text fragment with the highest score to generate a final answer, and outputting the final answer to the user. Therefore, the information integrity and the context continuity in the retrieval process are ensured.

A dynamic experience curation platform utilizing AI and ML techniques, including neural networks and generative models, to enhance user interactions with content on the Internet. The platform employs an Experience Broker (EB) service to disintermediate user devices from the internet (or other content / information sources), improving security and user experience. It processes content requests, extracts relevant information, filters out unwanted content like ads, transforms, combines, and / or mutates existing content, and generates curated content consistent with user preferences and other constraints. The platform's generative AI process renders content into a user interface consistent with user preferences. It allows for personalized content delivery across devices, including virtual and augmented reality environments. The platform supports a spectrum of personalization, allowing users to fine-tune their content consumption experience. Additionally, it manages user sessions across devices and integrates various databases for storing user profiles, preferences, and other relevant information.

The invention discloses an intelligent-based abnormal carbon emission data automatic identification early warning system, which belongs to the technical field of intellectualization and comprises a data acquisition preprocessing module, a high-precision space-time analysis module, an intelligent analysis module, an automatic abnormal identification module, a carbon footprint tracing module, a self-adaptive adjustment module and an intelligent emission prediction module. A carbon emission source and time-space distribution characteristics are accurately positioned through spatial positioning and time sequence analysis of the high-precision time-space analysis module, a spatial distribution diagram is more detailed and accurate through the optimized sensor position and an interpolation algorithm, and time sequence analysis is more accurate through timestamp correction and power spectrum density analysis. The method effectively evaluates the periodic intensity of the signal, analyzes a hidden mode and an association rule in the data through the intelligent analysis module integrating the spatial-temporal characteristics and the related information of the data acquisition and preprocessing module, analyzes the spatial-temporal association between variables through the calculation of a clustering center and the association intensity, and facilitates the discovery of a potential abnormal mode.

The invention relates to a full-process order life cycle management method, system and device and a medium, and the method comprises the following steps: obtaining user information and user demands, and building a work order; according to a preset rule, work order distribution is carried out, related information is supplemented, and a pre-sales scheme is generated; technical feasibility, resource requirements and risks of the pre-sales scheme are automatically assessed, and an assessment report is generated; project research and development are carried out based on the pre-sales scheme and the evaluation report, the research and development progress is updated in real time in the research and development process, and research and development results are uploaded after research and development are completed; the research and development results are tested based on the automatic test script, and a test report is automatically generated; generating a delivery list based on research and development results and test reports, and automatically sending the delivery list to the user; and obtaining questions fed back by the user, performing automatic classification according to the questions, and performing adjustment according to a classification result until the order is completed. Compared with the prior art, the device has the advantages of high automation degree and the like.

The invention discloses a business filling scene data acquisition method and system, a storage medium and electronic equipment, and the method comprises the steps: firstly storing filling historical data and domain knowledge into a vector database, and according to the current input of a user, searching related information, and combining the current input to generate a filling suggestion through a generation type large model; multi-modal information of the multi-end filling system is obtained, semantic understanding and information extraction are completed through a large model, and the multi-modal information is converted into structured data; mapping the structured data to a specified field by means of a field mapping rule; a data verification rule is designed, data verification is corrected through a rule engine or large model dynamic logic verification, and a verification result and a prompt suggestion are output; and finally, storing the processed and verified data, and providing data support for the user. According to the invention, the data acquisition efficiency is improved; the intention of the user can be predicted, corresponding suggestions can be provided, and the legality and accuracy of data are ensured.

The invention relates to the technical field of electronic medical record generation, and discloses an electronic medical record automatic generation method based on voice recognition, which comprises the following steps: S1, initializing voice input, distributing a unique voice acquisition identifier for a medical session, and completing identifier generation, input, storage, association and identity verification; s2, voice information intelligent recognition: converting voice into a text by using a voice recognition engine, and ensuring semantic consistency through a context verification unit and a semantic analysis unit; and S3, performing multi-speaker processing based on intelligent interference detection and resolution, positioning an interference time period and an interference source through an interference detection unit, and realizing time period distribution and priority ranking of multi-speaker voices by using a voice segmentation protocol and a linear weighting model. And finally, extracting related information from the text generated by voice conversion, and filling the related information into a medical record template of a hospital. The method improves the efficiency and accuracy of electronic medical record generation, solves the problems of multi-speaker interference and semantic logic, and is suitable for medical informatization scenes.

The invention provides a self-adaptive information retrieval and optimization system based on retrieval enhancement generation, which comprises a prospective answer module used for receiving a query statement and context information and inputting the query statement and the context information into a large language model so as to generate a prospective preliminary answer; the confidence coefficient detection module is used for setting a confidence coefficient score threshold value to carry out keyword-level confidence coefficient evaluation on the content in the prospective preliminary answer, correcting a low-confidence-coefficient part in the answer according to an evaluation result, and outputting a complete answer content as a confidence coefficient answer; the knowledge graph extension query module is used for executing named entity recognition operation on the confidence answer and obtaining an extension query answer in combination with a pre-constructed small knowledge graph; and the context memory pool module is used for storing the context information input for the first time and related information fragments obtained in each round of retrieval process, preferentially performing information retrieval from the memory pool in the subsequent retrieval process, and accessing the external index database only when no matched content exists in the memory pool.

The invention discloses a multi-agent cooperation performance evaluation method and a medium. The method comprises the following steps: determining a task structure index according to task splitting information and task scheduling execution information; performing time sequence analysis and behavior pattern recognition according to the communication information among the intelligent agents to determine a cooperative communication index; determining a task consistency index according to the sub-task execution information and the main task execution information of each agent; determining a time resource efficiency index according to the task execution time information of each agent and the execution capability information of each agent; and determining an evaluation result of the multi-agent cooperation performance according to the task structure index, the cooperative communication index, the task consistency index and the time resource efficiency index. According to the invention, evaluation is carried out from multiple dimensions according to related information of multi-agent cooperation, the comprehensiveness of the evaluation result is improved, and the accuracy of the evaluation result is further improved.

The invention discloses a university purchase performance supervision comprehensive management system and management method, and the system comprises a purchase plan management module which makes a purchase plan according to the actual demands of a university, and carries out the verification of the purchase plan; the purchase execution management module is used for issuing purchase information, inviting suppliers to participate in bidding, performing qualification auditing and reputation evaluation on the suppliers, recording and tracking a purchase negotiation process, and performing electronic signing and management on contracts; the performance acceptance management module is used for supervising performance conditions of suppliers and is responsible for recording and tracking an acceptance process; the performance supervision and evaluation module is used for carrying out regular evaluation on purchasing activities, forming a performance evaluation report, providing rectification measures for problems found in evaluation, and tracking rectification conditions; and the information query and statistics module is used for providing a function of querying related information of purchasing activities and carrying out statistics and analysis on the purchasing data.

The invention discloses a general security risk monitoring method and device based on image scene recognition knowledge retrieval enhancement, computer equipment and a readable storage medium, and the method comprises the steps: firstly obtaining video data and extracting a video image, and then obtaining a scene recognition result through a pre-trained model and a multi-modal large model, the method comprises the following steps of: firstly, searching corresponding potential safety hazard rule knowledge by utilizing an RAG search engine, then carrying out potential hazard identification to obtain a result and a suggestion, and finally, carrying out query structured rewriting on related information based on a thinking chain to obtain a target safety risk monitoring result, thereby realizing efficient and accurate safety risk monitoring.

The invention discloses an emergency command control method and system based on a Beidou emergency patrol car, and the method comprises the steps: obtaining various signal data from a complex environment through the deployment of a multi-source sensor network, carrying out the data fusion processing under the condition of communication signal interruption, and determining a preliminary position estimation result; according to the preliminary position estimation result, a positioning algorithm based on multi-source data correction is adopted to optimize and adjust the positioning precision, and high-precision positioning data is obtained; through high-precision positioning data, a live-action dynamic model framework is constructed, terrain and obstacle distribution characteristics are fused, related information of environment change perception is acquired, and three-dimensional scene description updated in real time is determined; and according to the three-dimensional scene description updated in real time, analyzing the demand of dynamic resource allocation, identifying key nodes and resource distribution states in multi-party cooperative command, and obtaining a priority sequence of resource allocation. According to the invention, full-process automation and intelligentization are realized, the manual intervention cost is reduced, and the emergency response speed is improved.

The invention provides an intelligent assistant method and system based on a large model, relates to the field of large model application, is used for providing a question and answer result for a user question, and comprises the following steps: constructing an entity recognition cue word, and recognizing an entity in the user question through the large model; constructing intention recognition and tool selection prompt words, recognizing user intentions in the user questions through a large model, and determining tools to be used; based on the assembled user questions and entities, related information is retrieved from a pre-constructed vector knowledge base, and a large model is combined with the retrieved related information to enhance and generate an answer text; processing the answer text according to the user intention and the tool, and outputting a final question and answer result; according to the method, the limitation that a traditional intelligent assistant cannot deeply understand user semantics and only can mechanically carry out rule matching is solved, and the requirements of the user can be more accurately grasped to provide a more accurate problem solving strategy.

According to embodiments of the disclosure, a method, an apparatus, a device and a storage medium for live streaming interface interaction are provided. The method includes receiving a predetermined request for a live streaming interface, the live streaming interface providing, in real time, an audio-visual content associated with a target session established in a live streaming room; causing a target interface corresponding to the predetermined request to be presented; and superimposing, on the target interface, a window associated with the live streaming interface, the window at least displaying description information associated with at least one participant in the target session. In this way, with embodiments of the disclosure, it may present relevant information of a target session (e.g., voice chat or video chat) established in the live streaming room that the user is interested in, thereby improving efficiency of the user in obtaining information in the live streaming room.

The present disclosure relates to a 5G or 6G communication system for supporting higher data transmission rates. According to an embodiment of the present disclosure, proposed are a method for reporting an IDC problem between 3GPP and non-3GPP systems in an MR-DC scenario, a method for reporting an IDC problem in BWP or PRB units in more detail compared to existing methods, a method for reporting a TDM-based solution preferred by a terminal, a method for introducing an autonomous denial function for NR, and a method for improving SON / MDT considering IDC problems. According to various embodiments of the present disclosure, provided are a method for reporting IDC-related information and a preferred solution, and a device capable of performing same. Accordingly, an effect of improving a method for reporting IDC-related information and a preferred solution may be obtained.

The invention discloses a data transaction security assessment method and system, and relates to the technical field of data security and intelligent assessment. The method comprises the steps of performing feature analysis on a data field, determining a sensitivity weight and generating a sensitivity vector; the fields are graded according to the sensitivity vectors, and dynamic adjustment is carried out in combination with transaction related information to obtain a grading result; calculating a data content risk, a field association risk, and a transaction environment risk based on the sensitivity feature set; determining a weight according to a transaction scene, and weighting various risks to obtain a comprehensive score; and judging the risk level according to the comprehensive score and a threshold value dynamically determined based on historical data. According to the invention, through hierarchical sensitivity modeling and dynamic risk calculation, fine-grained security assessment of different types and sensitivity data is realized, and the risk result can be adaptively adjusted along with changes of data contents, transmission paths and transaction environments, so that the accuracy, real-time performance and scene adaptability of assessment are improved, and the risk assessment efficiency is improved. The defects of a static evaluation method in the prior art are overcome.

The invention belongs to the technical field of user management, and provides a risk type identification method and device for a social session, and the method comprises the steps: obtaining to-be-detected information which comprises session information and related information; according to the to-be-detected information, obtaining a first risk type label and an initial confidence coefficient thereof; if the initial confidence coefficient is not smaller than a first threshold value, obtaining a cue word character string according to the first risk type label; inputting the cue word character string into a large language model to obtain a first confidence coefficient of the first risk type tag; and if the first confidence coefficient is not less than a second threshold value, determining that the to-be-detected information is a risk type corresponding to the first risk type label.