250 results about "Content retrieval" patented technology

The invention belongs to the technical field of air traffic control and conduction, and particularly relates to an intelligent question answering system method for air traffic control and conduction business knowledge. According to the method and the system, the refined and context-aware information retrieval capability of the air traffic control communication service knowledge and the expert-level air traffic control communication service knowledge question and answer capability are provided, the knowledge management and application efficiency is effectively improved, and powerful support is provided for digital transformation of related services. Comprising the following steps: S1, a document content extraction and storage process; s2, a content retrieval and generation process; s3, content slice optimization is carried out through extraction and similarity calculation of adjacent paragraphs or contents, complete contents are in the same slice, and the content retrieval efficiency is improved; according to the method, the label library and the business rule library are continuously iteratively optimized, so that the provided service is always in the optimal state.

The invention relates to the technical field of data processing, and discloses a government affair intelligent questioning and answering method, device and equipment and a storage medium, data existing in an FAQ questioning and answering pair database is enhanced by using a large model, and FAQ questioning and answering pair extraction and document paragraph splitting are performed on a government affair handling document transmitted by a government affair network API interface; the method comprises the following steps of: searching an FAQ question and answer pair of a query request by utilizing a structbert algorithm, outputting when the similarity is higher than a preset threshold value, otherwise, executing the query request and three decision mixed retrieval including bce-embed-base-V1 vectorization retrieval, BM25-scSenteTransformer mixed retrieval and dynamic self-attention DynAttenBiLSTM content retrieval for each government affair handling document to obtain a mixed retrieval result, and outputting the mixed retrieval result to each government affair handling document. And finally, outputting a question and answer result of the query based on the mixed retrieval result by utilizing a government affair answer large model, thereby realizing traceability of document answers, high answer reliability and high accuracy through a mixed retrieval module fusing a three-way decision module and a plurality of similarity algorithms.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

The invention provides a game strategy retrieval method and device based on event-driven knowledge graph embedding. The method comprises the following steps: performing structured analysis on strategy data, and updating entities and relationships; performing graph embedding calculation on entities and relationships in the knowledge graph to obtain vector representation among the entities, and constructing a searchable vector index; vectorizing a strategy query request of a user, and performing similarity retrieval on the strategy query request and the vector index to obtain a first candidate entity set similar to the query vector; performing relation reasoning by taking the first candidate entity set as a starting point in the knowledge graph to obtain a second candidate entity set in semantic association with the first candidate entity set, and combining the second candidate entity set with the first candidate entity set to form a target entity set; and performing correlation sorting on the target entity set to obtain a strategy result. According to the method, the strategy data can be automatically and structurally managed, and deep semantic retrieval is supported, so that the accuracy of game strategy content retrieval is improved, and the dynamic expansion capability is achieved.

Disclosed are methods, systems, devices, apparatus, media, and other implementations for improved search-time content retrieval performed by an information retrieval platform. The implementations include a method including determining by a searching system, at a first time instance, one or more first search results for a first query comprising one or more query terms associated with a first concept, modifying the query, based on the determined one or more first search results, to include one or more modified query terms associated with one or more concepts hierarchically related to the first concept, and determining at a subsequent time instance one or more subsequent search results for the modified query comprising the one or more modified query terms.

A method for using a local large language model (LLM) within a user's secure computing environment is disclosed. The LLM operates behind a firewall to prevent transmission of sensitive data, and utilizes an encrypted vector database and artificial intelligence techniques for content retrieval, response generation, and task anticipation. This system can be used on mobile, wearable, vehicle, or IoT devices and offers various services such as health monitoring, financial advice, automated communications handling, and personalized daily activity optimization. It also has the ability to detect fraud, fine-tune responses using augmented user data, assist in negotiations, identify personal interests, and provide health recommendations based on dietary and physical activity data.

Devices and techniques are generally described for LM-based content retrieval. First query data including a first request related to first content may be received. First action data associated with the first query data may be determined. First prompt data including a representation of the first query data and data representing the first action data may be generated. The first prompt data may instructs a first LM to recognize entities in the first query data relevant to the first action data. The first LM may determine a first recognized entity from the first request. The first recognized entity may be associated with the first content. A request to resolve the first recognized entity may be generated. A first resolved entity for the first recognized entity may be determined. The first LM may generate first instructions to perform the first action data using the first resolved entity.

The present invention relates to the field of artificial intelligence technology, and in particular to a dynamic relevance enhanced retrieval generation system and method driven by an intelligent knowledge graph. The knowledge graph construction module of the present invention identifies and extracts entities and entity relationships from a text document collection with a massive amount of text documents to construct a knowledge graph and a knowledge graph index, and optimizes the index of the knowledge graph, which greatly shortens the query response time and improves the user experience. The related document collection module performs in-depth analysis and relevance evaluation on the relationship between text documents and user queries to extract related text documents, thereby ensuring the diversity and depth of the retrieval results. The retrieval enhancement generation module retrieves relevant information from the knowledge graph based on user queries and related text documents, and combines the retrieved relevant information with the user query to generate an answer, which helps to achieve more fine-grained related content retrieval, thereby improving the quality of the answer.

Systems and methods for verifying content delivery in a content delivery network (CDN) are described. Content retrieval and routing in a CDN are tested using multiple test sequences that are each assigned to a different value of a parameter P and are generated using the assigned value of P. A client device can verify whether a test sequence received at the client device matches a test sequence requested by the client device (e.g., the correct content was) and verify that the received test sequence is assigned to the same value of P as the requested test sequence. The value of P assigned to the received test sequence can be extracted, by the client device, from the received test sequence to determine which test sequence was actually received, thereby providing information that can be used to help debug content delivery errors.

One example method includes enabling a user to define a query that comprises a hybrid search syntax (HSS), and the HSS is in the form of a single string that comprises a lexical component and a semantic component, receiving the query from the user, parsing the lexical component and the semantic component into respective groups of one or more sub-components, performing a lexical search based on the sub-components of the lexical component, and performing a semantic search based on the sub-components of the semantic component, ranking, separately from each other, results of the lexical search and results of the semantic search, combining the results of the lexical search and the results of the semantic search to create aggregate results, and re-ranking the aggregate results.

The invention relates to an information retrieval method and device for hierarchical planning reinforcement learning based on retrieval enhancement. The method comprises the following steps: acquiring a natural language query request of a user; calling a large language model of hierarchical planning reinforcement learning training based on retrieval enhancement to generate semantic keywords; the high-level strategy splits the natural language query request into a series of sub-query requests; the low-level strategy generates a retrieval query according to the context of the current sub-query request, and obtains a result verification condition from an external knowledge base through an RAG model; calling a search engine to execute multiple rounds of fine-grained information retrieval to obtain a plurality of candidate retrieval results; and performing deep semantic matching analysis on the candidate retrieval results and the result verification conditions by utilizing the post-trained large language model to calculate a matching degree score, and screening the candidate results according to the matching degree to obtain a final information retrieval result. Compared with the prior art, the method has the advantages that high-quality content retrieval and result display of complex query problems of users in various scenes can be realized.

Disclosed in the present application are a data processing method and apparatus, and a device and a readable storage medium. The method comprises: obtaining M candidate results which are sorted and displayed on a page, wherein the M candidate results are retrieved on the basis of an initial query statement; if an interaction operation meets a re-retrieval condition, acquiring historical interaction information, which comprises N historical query statements and a set of historical interaction results, wherein the N historical query statements comprise the initial query statement, and the set of historical interaction results comprises a candidate result which is included in an interaction record corresponding to an object; and generating context content vectors corresponding to the historical interaction results in the historical interaction information, and generating an updated query statement by means of the context content vectors and the N historical query statements, wherein the updated query statement is used for being displayed in a retrieval prompt box, and the retrieval prompt box is used for guiding the object to perform re-retrieval by means of the updated query statement. By means of the present application, the accuracy and efficiency of content retrieval can be improved.

The invention belongs to the technical field of brain-computer interfaces, multi-modal feature alignment and information retrieval, and discloses a visual content retrieval method based on electroencephalogram signals. Cross-subject standardized electroencephalogram samples are obtained and input into an electroencephalogram encoder to extract low-dimensional electroencephalogram signal feature vectors; an image encoder is adopted to process the corresponding retrieval images to extract visual feature vectors; the low-dimensional electroencephalogram signal feature vector and the visual feature vector are jointly input into a prototype attention enhancement module to form a dynamic prototype pool, and prototype enhanced electroencephalogram signal representation is obtained through processing; the method comprises the following steps: performing classification training according to existing prototype enhanced electroencephalogram signal representation and image data pairs; for a plurality of time slices of the to-be-queried electroencephalogram signal sample, calculating a reconstruction error or a signal-to-noise ratio of each time slice to obtain a confidence coefficient; and adopting a weighted average or voting mechanism to fuse a plurality of time slice results, and outputting a stable and robust final visual retrieval classification result.

The invention relates to a book content retrieval method and device based on intelligent word segmentation and computer equipment. The method comprises the steps of obtaining a word segmentation result of a newly added book, and performing block processing on the word segmentation result to obtain a plurality of blocks; obtaining an extraction type abstract of each block, adjusting the original prompt template according to the extraction type abstract to obtain a first semantic extraction prompt template, and performing semantic extraction on each block by utilizing the fine-tuned local semantic extraction large model and the first semantic extraction prompt template to obtain an output text of each block; obtaining a generative abstract of the newly added book, constructing a second semantic extraction prompt template according to the generative abstract and the original prompt template, inputting the output text of each block and the second semantic extraction prompt template into a global semantic extraction large model, outputting a semantic introduction of the newly added book, and storing the semantic introduction into a semantic introduction library; and performing retrieval in the semantic brief introduction library according to the user retrieval statement. By adopting the method, the efficiency and accuracy of intelligent retrieval can be improved.

An example may provide at least one first generative machine learning model (GMLM) instruction and an intent to a GMLM. The at least one first GMLM instruction is to cause the GMLM to use the intent to generate first GMLM output. The first GMLM output includes GMLM-generated output sections. A device may provide the first GMLM output including the GMLM-generated output sections and at least one second GMLM instruction to the GMLM. The at least one second GMLM instruction is to cause the GMLM to use the intent, the GMLM-generated output sections, and a first data set to generate second GMLM output including at least one first digital element. A device may validate the second GMLM output by comparing the at least one first digital element to at least one second digital element. The at least one second digital element is accessible via a second data set.

The invention relates to the technical field of Internet video content distribution and distribution, in particular to a micro and short play content distribution and distribution system. The system comprises a content management module, a user portrait module, a copyright protection module, a commercial realization module and a data analysis module, the content management module realizes efficient uploading, auditing, storage and intelligent distribution of a movie, and content retrieval and popularization efficiency is improved through accurate classification and tagging management; the user portrait module utilizes data preprocessing, feature extraction and clustering analysis to construct an accurate user model, and user experience is improved based on a personalized recommendation algorithm; the copyright protection module comprehensively guarantees content security through request verification, URL encryption, anti-theft link and a dynamic access control mechanism; the commercial realization module adopts various strategies to improve the platform profitability; and the data analysis module optimizes a content recommendation and distribution strategy through big data collection and mining, and improves the overall operation effect. According to the invention, high-quality experience is provided for the user while the rights and interests of the content creator are ensured.

The invention discloses a fusion movie and television play content retrieval method based on a large language model, face recognition, target detection and a cross-modal vector. The method comprises the steps that videos are preprocessed and stored; performing word segmentation and optimization processing by using a large language model according to a retrieval text of the video content input by a user; performing OCR (optical character recognition) on the staff table of the video content and matching a character role association relationship; performing target detection on the object; for scenes and event contents involved in user retrieval, video frames are converted into vector representation through cross-modal mapping established by a CLIP model, the vector representation is compared with vector representation of a query text, and the similarity between the video frames and the query text is calculated; and finally, carrying out secondary sorting through the hit number and the final weighted score. The invention further discloses electronic equipment, a medium and a product. According to the method, the movie and television play media video material content retrieval capability is improved, comprehensive judgment is carried out through a fusion algorithm, and a high-quality video retrieval scheme is obtained.

Systems and methods for retrieving regional content via remote access point servers are disclosed. In one embodiment, the disclosure relates to a network system for content retrieval from remote network regions. The network system may comprise a first device. The first device may be configured to receive a request for content. The content may be on one or more content servers located in a remote network region. The first device may be further configured to at least one of forwarding the request, via tunneling, to a destination access point server located in proximity to the one or more content servers and receiving the content from the destination access point server, obtaining the content from a cache of the first device.

A computer-implemented method is provided. The method includes launching a streaming media interface application in response to a user input, performing a first memory check to determine presence or absence of first cached data, locating first cached data that includes content of a home page of the user's account, retrieving and processing the first cached data to display the content included therein, concurrently with displaying the content included in the first cached data, performing a process for user authentication, and performing the process for user authentication is delayed until after initiating displaying the content included in the first cached data, sending a user request for content of a video stream selected by the user, receiving the content of the user-selected video stream in response to a determination that the user is authenticated, and initiating a first streaming session to play the content of the user-selected video stream.

The invention discloses an unsafe behavior monitoring system, and the system comprises a real-time monitoring module which is used for obtaining a video image of a construction site scene in real time; the early warning module is used for detecting unsafe behaviors of the video picture and performing early warning on the unsafe behaviors; the personnel safety file management module is used for identifying identity information of construction personnel and recording working states and unsafe behaviors of the construction personnel; the site safety management module is used for calculating a coverage area and a blind area of the camera according to the planar graph information of the construction site, the position of the camera and the visual field; the conversational query module is used for analyzing the query request content of the user, retrieving the related video content according to the query request content and outputting a retrieval result meeting the query requirement; and the safety education training module is used for generating education training contents according to the detected unsafe behaviors. The monitoring efficiency is improved; and meanwhile, analysis of video contents based on different fine granularities can be completed, so that the safety monitoring precision and the monitoring effect are improved.

The invention relates to the technical field of artificial intelligence, in particular to an intelligent file editing and auditing system and method and a storage medium, and the method comprises the following steps: receiving a purchase file; vectorization processing is carried out on the purchase file; newly establishing a purchase document; relevant data are recalled from the vectorized data according to target information required by the chapters, structured conversion is carried out, and the data are added into the corresponding chapters, so that compilation of the purchase document is completed; the compiled purchase document is preprocessed; the method comprises the following steps: reading review requirements from a preset document review point library, extracting related review contents from vectorized data of a purchase document, performing review judgment on the related review contents according to the review requirements by utilizing a large language model, and outputting a review judgment result, thereby completing intelligent review of the purchase document. According to the method, manual content retrieval, extraction, integration, filling and auditing work can be replaced, the workload and time are greatly saved, and meanwhile the accuracy and speed of information retrieval are obviously improved compared with manual information retrieval.

Devices and techniques are generally described for LM-based content retrieval. First query data including a first request related to first content may be received. First action data associated with the first query data may be determined. First prompt data including a representation of the first query data and data representing the first action data may be generated. The first prompt data may instructs a first LM to recognize entities in the first query data relevant to the first action data. The first LM may determine a first recognized entity from the first request. The first recognized entity may be associated with the first content. A request to resolve the first recognized entity may be generated. A first resolved entity for the first recognized entity may be determined. The first LM may generate first instructions to perform the first action data using the first resolved entity.

The invention relates to a knowledge question-answering system based on a middle table operation manual and an implementation and use method thereof, and belongs to the technical field of computer technology, data management and knowledge management. The system designed by the invention comprises five parts, namely data access and data analysis, entity definition, entity relationship definition and entity attribute definition, graph construction, question and answer system construction and user feedback. According to the method, an optimal and most efficient data processing mode is designed for current questions and customer requirements, operation manual data are integrated, and efficient operation manual content retrieval and intelligent question answering are realized for the user questions by combining natural language processing (NLP) and a knowledge graph technology, so that timely and accurate operation process guidance is provided for the user, and the user experience is improved. The device can be used for assisting a middle table operator to quickly master, and the training time and training cost are reduced.

The invention relates to a content retrieval method and device, computer equipment, a storage medium and a program product. The method comprises the steps of obtaining a keyword of a target problem; according to the keyword, performing retrieval processing in a pre-established knowledge base constructed by at least one knowledge data in a text, a table and a picture through an index nested structure to obtain target retrieval content; and determining target reply content according to the target retrieval content. By obtaining the keyword of the target question and performing retrieval in the knowledge base with the index nested structure, the target retrieval content highly related to the question can be quickly and accurately positioned. In this way, blind search in a large amount of unorganized data is avoided, and the efficiency and accuracy of question answering are greatly improved.

The invention discloses a bridge engineering intelligent question answering method, device and equipment and a storage medium, and relates to the technical field of artificial intelligence and natural language process.The bridge engineering intelligent question answering method comprises the steps that a large model conducts natural language processing on an input question, and preprocessing information of the question is obtained, the preprocessing information comprises the bridge engineering field related to the problem; the question is divided into a plurality of sub-tasks according to the preprocessing information, the corresponding sub-tasks are executed through a plurality of agents sharing and transmitting intermediate results so as to complete question answering, and the sub-tasks comprise content retrieval, data structured processing and knowledge fusion and complementation. According to the method, professional and detailed bridge engineering knowledge question-answering services can be provided for users in multiple rounds of interaction, and the intelligent level and response efficiency of a question-answering system in bridge engineering application can be improved.

The invention relates to an academic paper abstract generation method based on an image-text fusion index, and belongs to the technical field of artificial intelligence and multi-modal information processing. The method comprises the following steps: acquiring academic paper data from a public data source; according to academic papers in the academic paper data, segmenting paper contents according to logic, establishing association between fragments and images, and constructing an image-text fusion index; performing semantic retrieval on four dimensions in the academic paper to obtain a final retrieval content set of all the dimensions; and generating an image-text fusion abstract based on the retrieval content set of the four dimensions. According to the method, by constructing the image-text fusion index, the image-text association strength and the chapter context coherence are enhanced, deep coupling of the image and the text in the semantic level is achieved, and the image-text collaborative expression ability of the abstract is improved; by designing a structured dimension template and a content retrieval mechanism driven by a standard problem, the structured coverage of key information is ensured, and the logic continuity and readability of the abstract are remarkably improved.

Apparatus and methods for automating pre-procedural coordination workflows in a digital environment include at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to generate, using a trained content retrieval data structure, a plurality of content retrieval parameters, receive, from a first entity, an input including an input data structure as a function of the plurality of content retrieval parameters, populate, using the input data structure, a content queue comprising a plurality of content elements, query a second entity using at least a content element of the plurality of content elements, update the content queue as a function of at least a query response received from the second entity, generate a recommended course of action as a function of the updated content queue, and perform the recommended course of action.

The invention relates to an infant teaching resource intelligent searching and recommending system based on an AI large model. The system comprises a resource acquisition module, a label indexing module, an A I semantic understanding module, a resource screening and adapting module, a recommendation sorting module and a compliance control module. Teachers input teaching requirements through natural languages, voices, teaching plans or pictures, and the system performs semantic analysis and keyword extension based on a large language model and completes multi-modal content retrieval in combination with a resource map. The system introduces a complexity analysis and right age adaptation mechanism, intelligently simplifies and reconstructs contents, and generates a personalized recommendation list based on teacher portraits and a collaborative filtering algorithm. And the resource use process is constrained by the compliance control module to ensure that the content copyright is legal. The system can significantly improve the lesson preparation efficiency of kindergarten teachers and the teaching resource adaptation degree, and is suitable for a digital teaching platform and an intelligent education system.

The invention relates to a document recognition method and device, electronic equipment and a storage medium. The method comprises the steps that a target document and title information of the target document are acquired; performing hierarchical analysis on the title information, and establishing a directed acyclic graph corresponding to the target document according to a hierarchical analysis result; based on the directed acyclic graph, a tree diagram corresponding to the target document is constructed, and each node of the tree diagram correspondingly records a document title of the target document; and according to the corresponding relationship between each node in the tree diagram and the document title, obtaining the document content of the target document by using the tree node of the tree diagram as an index. According to the method, the tree diagram corresponding to the document is constructed according to the support relationship, and the clear hierarchical structure is analyzed through the tree diagram, so that a document management system with the hierarchical structure is formed, the analysis requirements of different types of documents are met, and the legal content retrieval and analysis efficiency is remarkably improved.

The invention discloses an investigation report generation method based on large language model deep thinking and content retrieval, and belongs to the technical field of artificial intelligence. Generating requirement information input by a user is obtained, cue words are constructed according to the generating requirement information, the cue words are input into a preset large language model, and an article generating plan is generated; analyzing and partitioning the generated plan to obtain a plurality of structured chapter abstract contents and corresponding networking search keyword data; circulation is carried out until all the chapters are generated, retrieval is carried out according to networking search keywords needed by the current chapter, and reference content needed for writing the current chapter is obtained; and the reference content obtained through retrieval, the written previous chapter content and the abstract content needing to be written by the current chapter are used for constructing cue words required by writing of the current chapter. And inputting the cue word into a preset large language model, carrying out deep reasoning and thinking, generating the content of the current chapter, and giving a corresponding reference in a place where the related retrieval content is cited.