195 results about "Database retrieval" patented technology

The invention relates to the field of medical information processing and traditional Chinese medicine curative effect evaluation, in particular to a diabetic nephropathy traditional Chinese medicine curative effect evaluation method based on patient report outcome. The method comprises the following steps: searching related symptoms and clinical characterization data of diabetic nephropathy through a medical database, extracting target entries, performing language standardization processing, constructing an initial candidate entry set, calculating the occurrence frequency of each symptom entry, and screening entries meeting a set threshold value to form an entry set; carrying out dimension division on the entry set according to feature attributes to form a preliminary dimension structure set; forming a screening result set through preset logic screening conditions; and carrying out weighted regression fusion on the comprehensive curative effect score and clinical detection data, and outputting a patient curative effect index. In an item weight determination process, dynamic balance between subjective experience and objective statistical information is realized through a mixed weighting model, and the defects of strong subjectivity of expert scoring and large result fluctuation in a traditional method are overcome.

A disclosed method facilitates translation of natural language queries into query language statements usable to retrieve data from or write data to a particular database. The method includes obtaining a pool of shots. Each shot in the pool includes a natural language query component and a corresponding database translation component. The method further provides for vectorizing the natural language query component for each of the shots into a common vector space; receiving a natural language query from a user interface; vectorizing the natural language query within the common vector space; identifying a subset of vectorized natural language query components that satisfy a similarity metric when compared to the vectorized natural language query; and generating an LLM prompt that includes shots from the pool corresponding to the subset of the vectorized natural language query.

In embodiments, an apparatus includes a user data interpretation circuit structured to interpret user data corresponding to a first user; a bootstrap circuit structured to: match the first user to a second user via querying one or more databases based at least in part on the user data; retrieve historical time sequence data associated with the second user via querying the one or more databases; extract a time sequence trend from the historical time sequence data; identify a portion of the historical time sequence data corresponding to the extracted time sequence trend; and generate, based at least in part on the identified portion, time sequence data corresponding to the first user; and a time sequence data provisioning circuit structured to transmit the time sequence data.

The invention discloses a music database retrieval method and system based on feature extraction, and relates to the technical field of data analysis, and the method comprises the steps: carrying out the preprocessing of an audio signal of a query track input by a user, dividing the audio into equal-length frame sequences, and generating three-channel spectrogram tensors, including a Mel spectrogram, a logarithmic amplitude spectrogram and a CQT spectrogram; extracting multi-modal features of the equal-length frame sequence, dividing melody motivation segments according to pitch change and stability of the audio signal, performing differential coding, generating a melody differential sequence, and modeling the melody differential sequence into a melody topological graph; and calculating the structural similarity between the melody topological graph and a database melody graph, screening a similar melody candidate set P, mapping a melody curve into a topological manifold through a topological data analysis method, extracting persistent homology features, and converting the persistent homology features into a persistent bar graph. According to the method, the retrieval precision and the matching credibility of the complex melody in the music database are remarkably improved.

A system for confirming an advisory interaction with an artificial intelligence platform. The system includes a constitutional generator module configured to receive a first advisory input, retrieve an expert input, select a machine-learning process as a function of the expert input, and generate a therapeutic corrector. The system includes a constitutional advisory module configured to display a therapeutic corrector on a graphical user interface and receive a second advisory input. The system includes a best practices module the best practices module designed and configured to retrieve from an expert database a best practices training set, calculate an optimal vector output, generate an optimal vector output containing an expected therapeutic corrector implementation response, authenticate a second advisory input, and update the best practices module.

The invention relates to the technical field of data retrieval, in particular to a FastGPT-based intelligent question-answering system for construction project quality inspection and detection standards. According to the technical scheme, the method comprises the steps of external knowledge acquisition, document processing, vectorization, vector database, retrieval and context generation and intelligent question and answer, data can be collected by a system, a semantic segmentation technology, a QA pair generation technology and a high-dimensional vectorization technology are utilized, in combination with M3E and OpenAIEmbedding models, Top-K similarity retrieval and context dynamic recombination are achieved, and structured and hierarchical professional answers are generated. According to the method, the intelligent management and real-time application capability of the construction project quality inspection and detection standard can be remarkably improved, the manual retrieval and interpretation cost is reduced, and the digital and intelligent requirements of an engineering project are met.

The invention provides a multi-model intelligent routing method and system with memory and self-adaptive capabilities in the technical field of artificial intelligence and computer system resource scheduling. The method comprises the following steps: S1, executing an authentication operation based on a user request and extracting a user identifier; s2, performing intention recognition on the user request to extract multi-dimensional request features; s3, retrieving user preference information and a candidate model list related to the user request from a vector database based on the user identifier or the multi-dimensional request feature; s4, acquiring real-time service state information of each model in the candidate model list; s5, based on the multi-dimensional request features, the user preference information and the real-time service state information, a target model is selected from the candidate model list through a mixed decision strategy; and S6, the user request is routed to the target model, and a returned response result is received. The method has the advantages that the model scheduling accuracy, the resource utilization efficiency and the user experience are greatly improved.

The invention provides a satellite image fuzzy query method and system based on multi-dimensional vectorization indexing, and relates to the technical field of satellite image retrieval, the method comprises the following steps: mapping a structured query condition generated based on natural language query into a three-dimensional hierarchical index condition structured database to retrieve and output three-dimensional index metadata; and after the three-dimensional index result set is loaded according to the three-dimensional index metadata, space-time interaction visual output for generating the three-dimensional index result set is carried out by taking dynamic weight distribution as a sorting basis. The technical problems that in the prior art, satellite image high-response query cannot be carried out based on user fuzzy expression, so that the satellite image data query and calling efficiency is low, and the query result practicability is insufficient are solved. The technical effects that full-link closed-loop retrieval driven by natural languages is achieved, query flexibility is improved through intelligent mapping, efficient positioning is guaranteed through multi-dimensional indexing, the accuracy of dynamic sorting optimization results is guaranteed, and interaction friendliness is visually enhanced are achieved.

The invention discloses a retrieval enhancement generation method and system based on long-term memory and multi-source knowledge iterative fusion. The method comprises the following steps: firstly, after user inquiry is received, triggering long-term memory database retrieval, external knowledge base retrieval and large language model internal knowledge generation in parallel to construct a multi-source candidate knowledge base, and improving result correlation by adopting a self-adaptive retrieval method based on a dynamic top-k value; secondly, inputting user query and multi-source knowledge into the large language model for iterative fusion, and generating a final answer through conflict detection, fusion processing and confidence evaluation; and finally updating the long-term memory database. The method can improve the accuracy and stability of the generated answers in a multi-round interaction and complex task scene, reduces the risk of answer one-sidedness, inference incompleteness or fact deviation, enhances the multi-source knowledge utilization ability and long-term learning ability of the system, and improves the user experience. Therefore, the comprehensive performance and reliability of the system in applications such as intelligent question answering, information retrieval assistance and text generation are obviously expanded.

Example implementations include methods and systems that relate to search results and recommendations in a media content delivery system. An example method includes providing a search query to a multi-task language model associated with a media content delivery system. The method also includes providing user engagement information to the multi-task language model. The user engagement information indicates user engagement activity with the media content delivery system. The method also includes retrieving, using the multi-task language model and based on the search query, one or more candidate media items from a media item database of the media content delivery system. The method also includes identifying, using the multi-task language model and based on the user engagement information, one or more recommended media items from the media item database.

The present document discloses a method to generate a database for synchronization of a text, a video and / or audio media, namely a computer-implemented method to generate a database for synchronization of a text, a video and / or audio media with a video stream to be generated using said database, comprising the steps of: receiving an input text; splitting the input text into text segments; clustering the text segments into at least one text group; labelling each text segment with a sequential timestamp; and, storing each text segment with the label on a data record wherein the text group comprises a time interval label which corresponds to the duration of at least a portion of a video and / or audio media. It is further disclosed a method for retrieving information from said database, a system, and a computer program thereof.

A method of operating a health tracking system is disclosed herein. The health tracking system includes a processor and a database configured to store a plurality of data records, each of the plurality of data records comprising at least a descriptive string and nutritional data regarding a respective consumable item. The method includes receiving, with the processor, a query string. The method further includes searching, with the processor, based on the query string, the database to retrieve a list of data records in the plurality of data records from the database. The method also includes determining, with the processor, a ranked list of data records by ranking the list of data records using a machine learning-based ranking model, based on the descriptive string and the nutritional data of data records in the list of data records. The method then includes transmitting the ranked list of data records to an electronic device of a user of the health tracking system, the ranked list of data records being presented on the electronic device of the user.

Systems and methods for evaluating multimodal retrieval augmented generation (RAG) performance. The systems and methods include generating an internal response from a user input and a RAG database and generating a relevancy score for quantifying a relevance of the internal response to information retrieved from the RAG database based on the user input and a correctness score quantifying accuracy of the internal response to the information retrieved from the RAG database. The systems and methods further include generating a combined score from the relevancy score and correctness score and selectively performing a task based on the relevancy score, the correctness score, or the combined score.

A method and system of masking, redacting, filtering, and encrypting data retrieved from or stored into a database using policies in an information management system. The system comprises application, data protection, and database components. A data protection component is placed between an application component and a database component to provide protection to data in a database by applying data access policies to requests sent from the application component to the database component.

Methods and systems for retrieving data from at least one database based on a query input related to a clinical trial. A system processes a received query input related to a clinical trial using a pre-trained language model neural network. The neural network generates a structured representation of the query input. The system maps a first data field of the structured representation to a first column name and maps a second data field of the structured representation to a second column name. The system generates a database query based on (i) a database schema, (ii) the first column name, (iii) the second column name, (iv) data values associated with the first data field, and (v) data values associated with the second data field. The database query specifies an operation for joining data associated with the first column name with data associated with the second column name.

The invention discloses a method and a system for quality inspection of change survey data. The method comprises the following steps of 1, performing format identification on the change survey data; 2, calling an improved MacBERT model to carry out error correction processing, and generating standardized data; 3, performing integrity check and authenticity check on the attachment file corresponding to the standardized data; 4, performing field-by-field comparison on the material verification data and the data model retrieved from the database to generate comparison data; 5, inputting the spatial features of the comparison data into a cross-modal topology adapter of the improved MacBERT model, and generating topology verification data; and step 6, recording quality inspection result information. The method is suitable for data standardization processing and topology compliance verification scenes in the fields of natural resources, urban and rural construction and the like.

Methods and systems for retrieving data from at least one database based on a query input related to a clinical trial. A system processes a received query input related to a clinical trial using a pre-trained language model neural network. The neural network generates a structured representation of the query input. The system maps a first data field of the structured representation to a first column name and maps a second data field of the structured representation to a second column name. The system generates a database query based on (i) a database schema, (ii) the first column name, (iii) the second column name, (iv) data values associated with the first data field, and (v) data values associated with the second data field. The database query specifies an operation for joining data associated with the first column name with data associated with the second column name.

The invention discloses a multi-source fault diagnosis method and system based on a large language model and vector retrieval, and the method comprises the following steps: constructing a fault vector, collecting equipment multi-source fault heterogeneous data, carrying out the modal preprocessing to obtain the multi-modal data, inputting a large language model, carrying out the fusion through a cross-modal alignment module to generate a specific content, and carrying out the multi-source fault diagnosis. Generating a structured fault description text, and mapping the structured fault description text into a vector by using a dense embedding model; constructing a historical fault vector database; when a fault occurs, vectors are generated according to the above steps according to the collected data, historical similar cases are retrieved and obtained in the database, structured cue words are constructed and input into the large language model, finally, the large language model outputs structured results containing confidence estimation, and efficient fault diagnosis is achieved.

The invention provides a robot repositioning method in a dynamic environment based on laser visual complementation. The robot repositioning method comprises two stages of offline mapping and online repositioning. In the off-line stage, two-dimensional and three-dimensional elimination of a dynamic target is realized through a lightweight detection network and geometric projection, and the purity of a prior map is improved; visual and laser radar static features are respectively extracted, a complementary double descriptor database is constructed, and laser radar descriptors fuse geometry and reflection intensity information to enhance discrimination. In the online stage, a coarse-to-fine strategy is adopted, rapid and robust global matching is achieved by combining GPS coarse positioning and radius search-based database retrieval, and scene recognition and accurate pose recovery are completed by using vision and radar dual channels. According to the method, a high-purity priori library is constructed through dynamic target collaborative elimination and multi-modal feature fusion, and autonomous high-precision global repositioning without manual initial pose input is realized in combination with GPS coarse positioning and a self-adaptive channel switching mechanism.

This invention provides a method, apparatus, and storage medium for generating SQL statements based on context enhancement. The method includes: acquiring enhanced context related to a user-submitted natural language query; based on the enhanced context, using a large language model to identify the core data table most relevant to the natural language query from relevant data tables; obtaining several data records with the highest data density from the core data table as data samples; integrating the enhanced context, the structure definition of the core data table, the data samples, and the natural language query to construct Text-to-SQL prompts; inputting these prompts into the large language model to generate an executable SQL statement. This invention leverages vector database retrieval of enhanced context, uses a large language model to parse the user's natural language query and identify relevant core data tables, collects data samples from the core tables according to data density, constructs Text-to-SQL prompts, and generates an executable SQL statement through the large language model, achieving reliable responses to complex queries in specialized domains.

A method uses natural language processing for visual analysis of a dataset by a computer. The computer displays a data visualization based on a dataset retrieved from a database. The computer computes an initial visualization state that includes elements corresponding to data attributes of the data visualization. The computer receives user input to specify a natural language command related to the displayed data visualization. The computer extracts cue phrases from the natural language command. The computer also determines a transitional goal, to transform the data visualization, based on the cue phrases. The computer derives an updated visualization state based on the transitional goal, by applying transitional rules to each element of the initial visualization state. The computer subsequently computes analytical functions associated with the visualization states, thereby creating functional phrases. The computer then updates the data visualization based on the functional phrases.

The application relates to the technical field of active recommendation, and discloses an active recommendation method and system based on a large language model and multi-agent cooperation. The method comprises the following steps: analyzing user historical interaction records through an image analysis agent to generate and maintain a preference set of the user; generating a recommendation sub-target sequence based on the preference set of the user and a target item through a strategy planning agent; generating an ideal item abstract description according to a current recommendation sub-target through an item selection agent, searching a candidate item set by using a vector database, and selecting a recommended item set based on a large language model evaluation; and scheduling the image analysis agent, the strategy planning agent and the item selection agent in the form of a state machine through a process management agent to execute a cycle of recommendation-feedback-decision-reflection, so as to plan a migration path of user interest from a current state to the target item. The application has stronger adaptability because the recommendation sub-target and content are dynamically adjusted according to the preference of the user.

An example method includes receiving a request for a transaction; associating the request with a user; receiving, from the user, identification information; retrieving, from a database, first stored authentication information associated with the user; retrieving, from a distributed ledger, second stored authentication information associated with the user; and determining that the received authentication information matches the first stored authentication details and the second stored authentication details and, in response, outputting, by the computing system, a proof of authentication to enable the transaction.

The invention discloses a vehicle-ground communication quality prediction method and system based on a large model and intelligent workflow, and the method comprises the steps: S1, receiving an original communication message file uploaded by a user through a data access module, and extracting a structured data signal from the message file through a document analysis module; s2, searching the structured data signal from a database through a code execution module, and generating an effective abnormal event signal; s3, inputting the effective abnormal event signal and a communication quality statistical data signal derived from the structured data signal into a large language model service; s4, integrating the professional analysis text signal and the visual chart signal to a predefined report template through a report rendering module, and generating an analysis report signal; and S5, presenting the analysis report signal to a user through a user interface module. According to the train-ground communication quality prediction method and system based on the large model and the intelligent workflow, the problems that the train-ground communication quality analysis is high in false alarm rate, low in automation degree and lack of deep insight can be solved.

The application discloses a bank intelligent operation knowledge base implementation method and system based on a large language model and RAG. The method first extracts business terms from structured, semi-structured and unstructured multi-source heterogeneous multi-modal data of a bank, and then constructs a business dictionary and an ontology tree containing term similarity data. Then, the release agency weight, time effectiveness coefficient and penalty correlation degree of the regulatory provisions are quantitatively calculated to obtain an authoritative value and sort. Then, the pre-trained large language model is fine-tuned as a vector representation model using a double-constraint loss function, and the business data is vectorized and stored in a vector database. Finally, for user queries, the vector database is retrieved and combined with the regulatory provision sorting result for rearrangement, and a business response is generated after compliance verification. The method can improve the unstructured knowledge processing capability and retrieval accuracy of the bank, and realize efficient intelligent operation.

The present disclosure provides a system (102) and a method for preventing the unintentional operation of a sunroof in a vehicle. The system is configured to determine a multitude of facial attributes of an occupant in the vehicle using an imaging device. Furthermore, the system is configured to retrieve a profile of the occupant, corresponding to the determined multitude of facial attributes, from a profile database (218). In addition, the system is configured to calculate a occupant violation score based on the number of violation events committed by the occupant in relation to the operation of a sunroof unit (204). The calculated violation score corresponds to the occupant's profile. Furthermore, the system is configured to determine a violation level corresponding to the violation score.Furthermore, the system is configured to allow the locking of an occupant's seat belt based on the level of violation according to the violation point score.

The invention relates to the technical field of digital identity authentication, in particular to an online insurance policy verification method and system and a storage medium. The method comprises the following steps of: authenticating a user identity by adopting a living body detection and certificate OCR (Optical Character Recognition) technology, identifying tampering by using an image tampering detection model, and generating a structured request data packet through an improved OCR content extraction technology; retrieving benchmark insurance policy data in a distributed insurance policy database, and calling a multi-version data fingerprint sequence from a block chain; comparing the reference insurance policy data with the structured request data packet, and outputting a first verification result; matching the structured request data packet with the multi-version data fingerprint sequence, and outputting a second verification result; and generating a final verification conclusion based on the first and second verification results. According to the method, multiple technologies are fused to construct a whole-process verification system, compared with a single verification mode, the anti-fraud capability is improved through multi-dimensional cross verification, and related requirements of financial supervision on Internet insurance services are met.

The invention provides a retrieval processing method, device and equipment based on multi-source knowledge base data. The method comprises the following steps: acquiring multi-source heterogeneous data; standardizing the data format and the target term of the multi-source heterogeneous data to obtain standard data; performing repeated entity identification on the standard data, and removing repeated entities in the standard data to obtain target data; obtaining an entity relationship in the multi-source heterogeneous data according to the multi-source heterogeneous data, and constructing a knowledge graph; and obtaining a user target question, and querying in the target data and the knowledge graph to obtain a target output result. According to the scheme, the multi-source data can be managed in a unified manner, the cross-database retrieval accuracy of the data is improved through the knowledge graph, and the real-time response capability of the data is improved.

An electronic device includes a camera module, a communication module which detects one or more wireless communication devices located in a predetermined distance from the electronic device, and receives, from the one or more detected wireless communication devices, an identification code set in each of the one or more detected wireless communication devices, and a processor which receives a user profile from a corresponding wireless communication device of the one or more detected wireless communication devices in response to an identification code of the corresponding wireless communication device, which is retrieved from a pre-stored tag database, and applies a visual effect to an image captured by the camera module based on the received user profile.

This invention relates to a method and system for constructing a medical knowledge graph based on cross-dimensional alignment using artificial intelligence, belonging to the field of medical knowledge graphs. This method integrates authoritative databases from multiple medical domains by constructing a unified medical semantic space across scales and modalities; and combines deep representation learning and manifold alignment techniques to design a joint embedding and dynamic alignment framework for multi-source heterogeneous knowledge, achieving semantic unification and structure-fidelity mapping of different standard systems in a low-dimensional dense space. This invention not only effectively alleviates the semantic fragmentation problem between ontology but also significantly improves the system's semantic understanding and cross-database retrieval capabilities for complex clinical texts, providing a computable and reasonable knowledge foundation for clinical decision support, disease prediction, and precision medicine.