160 results about "Text searching" patented technology

The invention provides a cross-modal image-text retrieval processing method and a cross-modal image-text retrieval processing system, which are applied to the field of information retrieval, and the method comprises the following steps: obtaining a query text input by a user in an image-text retrieval process; encoding the query text through a text encoder to generate a query text feature vector; through a cross-modal image-text retrieval model, similarity matching is carried out based on query text feature vectors and multi-modal embedding representations stored in an external knowledge base, related results corresponding to the multi-modal embedding representations larger than a matching threshold value are returned, and the multi-modal embedding representations are used for representing joint features of images and texts; when the related result comprises the image and the text at the same time, the related result and the query text are input into a preset multi-modal large model, image question answering with text assistance is carried out, and a retrieval result output by the multi-modal large model is obtained; according to the method, the semantic association between the image and the text can be better captured, so that the accuracy of image-text retrieval is improved.

The invention provides a text search method and system based on vector retrieval and large model optimization, and relates to the technical field of text search, and the method comprises the following steps: obtaining a to-be-retrieved text and generating a semantic vector; retrieving similar texts in a vector database based on the semantic vectors; calculating the correlation of the text pairs by using a cross encoder model and sorting the text pairs; and extracting key entities by adopting a knowledge graph optimization model, analyzing an entity relationship, and reordering and filtering search results. According to the method, through semantic vector retrieval, cross coding calculation of correlation and knowledge graph optimization, the accuracy and correlation of text search are improved, user intentions can be better understood, and more accurate search results can be returned.

Generating responses to queries with text extracts from unstructured data using AI models includes (i) extracting text from unstructured data sources to create machine-searchable documents, (ii) replacing PII and PHI with entity types and attributes, (iii) determining text extracts that indicate criteria, (iv) using a small-scale ML model to perform text searches and find conceptually associated text strings, (v) generating a custom context for a large language model (LLM), (vi) prompting the LLM to generate a response, (vii) combining the response with an extractive QA model to obtain relevant text extracts as response basis, and (viii) providing system-generated recommendations for next best actions based on responses that produce the most optimal outcomes in historical input documents for manually selected or automatically recommended resolution paths.

The invention provides a full-text retrieval method and system fusing various types of documents, and relates to the technical field of information retrieval, and the method comprises the following steps: obtaining document representation through document content extraction and structure recognition, generating a cross-modal semantic vector by using word embedding and nonlinear transformation, constructing a hierarchical index and a cross-document association graph, and obtaining a full-text retrieval result; the basic correlation score is calculated after the query request is received, and the comprehensive score of the candidate content segments is calculated based on the association graph to determine the optimal retrieval result, so that unified representation and retrieval of heterogeneous documents are realized, the cross-document retrieval precision and relevance are improved, and the processing capability of a retrieval system on complex queries is enhanced.

The embodiment of the invention provides a cross-modal data search method and device based on Surreal DB. The method comprises the steps that multi-modal data input by a user at a data query interface is received, and the multi-modal data comprises text, picture, audio, video, webpage and document data; the method comprises the following steps: converting audio, video, webpage and document data into texts and pictures, performing keyword extraction on the texts to obtain text cues, and performing vectorization processing on the texts and the pictures to obtain query vectors; performing full-text retrieval on the text cue word based on a Surreal DB database to obtain a text search result, and performing vector retrieval on the query vector to obtain a vector search result; reordering the text search result and the vector search result by using a ranking-based search result fusion algorithm, and outputting a preliminary search result; and performing associated query on the preliminary retrieval result to obtain associated data.

The invention provides a novel large model traditional Chinese medicine course resource intelligent question answering method and system, and the method comprises the steps: enabling a large model to convert a user question into a question vector, and carrying out the similarity retrieval matching in a Fast vector library, and constructing a first reference answer; performing entity relationship and different noun mining on the question by the large model, performing knowledge graph filtering, analyzing the real intention of the question asked by the user, generating a corresponding Cypher statement according to the filtered entity and relationship, executing the Cypher statement in Neo4j, and constructing a second reference answer; performing fine word segmentation on the questions by the large model by using a predefined word segmentation device, executing full-text search in a pre-constructed Elasticsearch engine index kernel, sorting search results according to a characteristic sorting strategy, and constructing a third reference answer; and the large model carries out knowledge summarization and generation according to the first, second and third reference answers, strictly screens data reference sources through a verification mechanism, and generates the most accurate comprehensive answer. Intelligent question answering can be performed on traditional Chinese medicine course resources.

A computer-implemented method for computational textual search to find and display search identified information in documents. Search queries are processed over one or more documents either at a server or user device using match schemes that produce both binary (match or no match) and non-binary (i.e. multiple matching values) results and have relative fuzziness relationships. A fuzzier match scheme implies more results and fewer false negatives and a less fuzzy match scheme implies fewer results and fewer false positives. This fuzziness relationship allows, without changing a search string, for users to quickly change from a match scheme to a fuzzier or less fuzzy match scheme depending on user evaluation of results as containing too many false negatives or too many false positives—without becoming a programmer of complex search string metadata or an expert user of advanced search capabilities.

A text processing method includes obtaining a query text, invoking a search engine interface based on the query text to obtain a plurality of text search results corresponding to the query text, obtaining, from the plurality of text search results, a plurality of answer text segments matching the query text, determining a relevance between the query text and each of the plurality of answer text segments, determining one of the plurality of answer text segments that corresponds to a maximum relevance as a reference text of the query text, and invoking a language model based on the query text and the reference text to obtain a reply text of the query text.

Embodiments of the present invention provide systems, methods, and computer storage media for a visual and text search interface used to navigate a video transcript. In an example embodiment, a freeform text query triggers a visual search for frames of a loaded video that match the freeform text query (e.g., frame embeddings that match a corresponding embedding of the freeform query), and triggers a text search for matching words from a corresponding transcript or from tags of detected features from the loaded video. Visual search results are displayed (e.g., in a row of tiles that can be scrolled to the left and right), and textual search results are displayed (e.g., in a row of tiles that can be scrolled up and down). Selecting (e.g., clicking or tapping on) a search result tile navigates a transcript interface to a corresponding portion of the transcript.

A system for automated processing and analysis of audio files for large data sets in a cloud environment. A unified analytic environment can integrate audio machine learning models for processing and analysis with a knowledge management system, including graph presentations of tracked entities, linked to audio files and / or associated translations and transcripts. Entities within such data can be searched or filtered and proposed for tracking, or identified as tracked objects. These features can allow triage and prioritization of audio files for analysis. User interfaces can facilitate feedback on transcription and translation outputs, thereby improving present outputs and future inputs and outputs. Entities speaking or referred to can be found, tagged, and distinguished in audio files (e.g., using speaker identification in audio files, text searching in transcripts, etc.) Users can provide feedback and input on various aspects of a system, to enhance or adjust initial automated or other machine learning outputs.

The invention discloses a question answering method and device for credit review knowledge based on a large model and a medium, and the method comprises the steps: obtaining a to-be-processed credit review question, extracting a core keyword from the question through a natural language processing algorithm, and converting the question into a deep semantic vector through a semantic vector model; inputting the questions into an intention classification model, generating filtering labels, inputting the questions into a distributed full-text search engine, screening a target knowledge base according to the filtering labels, and performing retrieval in the target knowledge base based on the core keywords and the deep semantic vectors to obtain a preliminary retrieval result set; calculating the score of each preliminary retrieval result in the result set according to the core keyword, the deep semantic vector and the weight factor, and screening out final reference content in a descending order; and on the basis of credit and loan business compliance requirements, risk control rules and question and answer output specifications, the credit and loan prompt words are constructed, and the final reference content is input into the large model to obtain structured credit and loan review answers, so that the question and answer efficiency and accuracy are improved.

Systems or methods of the present disclosure may provide a design tool for adjusting designs implemented on programmable logic devices. The present disclosure includes receiving documentation and receiving a full text search. The documentation may include user guides, technical specifications, and design files such as HDL code, constraints, timing reports, and / or design assistant / rule violation (DRC) reports. The present disclosure also includes determining semantic search for embedding vectors based on the documentation and the full text search. Furthermore, the present disclosure includes providing the semantic search to a large language model (LLM).

The invention discloses a BEV-based scene-level text search point cloud retrieval method and device and electronic equipment, and the method comprises the steps: projecting a three-dimensional point cloud into an aerial view, and generating a BEV image; encoding the image by using a pre-trained vision-language model to obtain BEV feature vectors, storing the BEV feature vectors in a vector database, and constructing a point cloud feature library; meanwhile, encoding a user query text to obtain a text feature vector; searching a matching scene from the feature library by calculating the cross-modal similarity between the text and the BEV feature vector; and finally, mapping a retrieval result to original point cloud data and outputting the original point cloud data. By means of the method, the feature alignment problem of the point cloud and the natural language is solved, and the retrieval method which directly and efficiently utilizes essential features of the point cloud data to be in seamless joint with the natural language is achieved.

A server receives and rebroadcasts live streaming video content from a video capture device, such as a mobile phone or unmanned surveillance vehicle. The server includes a media server configured to stream selected video content to a client device, a video analysis system configured to analyze the live video content and generate object detection data, a storage system configured to store the generated object detection data and an identifier of the associated live video content, and a search engine configured to receive a text-based search request, search the object detection data stored in the storage system for relevant search results, and generate a list of live and stored video content associated with the relevant search results.

A computing system may include an image access engine configured to access a panoramic point cloud image of a physical environment. The computing system may also include an environment location-aware text engine configured to transform the panoramic point cloud image into an alternate representation that reduces distortion in the panoramic point cloud image and perform an optical character recognition (OCR) process on the alternate representation to determine text in the panoramic point cloud image. The environment location-aware text engine may further be configured to construct text labels to track the text determined in the panoramic point cloud image and support text searches for the physical environment through the text labels.

The present application provides a kind of urban rail vehicle electronic history data processing method, the method establishes vehicle operation configuration in combination with vehicle structure design, and vehicle configuration data structure is structured using database technology;Vehicle history data granularity refined to the smallest maintainable unit is used, the correctness and timeliness of data are guaranteed through data analysis and integration technology based on business process, the whole life cycle stage document of vehicle is stored using data storage technology, and preliminary vehicle knowledge framework is established in combination with full-text search technology, to provide basic data support for later subway vehicle procurement, technical reform, operation.In history data management, block chain technology is added to ensure the confidentiality and integrity of data flow, to prevent sensitive data from being leaked and tampered with during transmission, and to enhance the security and correctness of vehicle history data, to provide reliable data security guarantee for subsequent history sharing.

Devices, systems, and methods for tokenizing search attributes and terms of a search query for an index-based search. A method may include receiving, by a search service of a provider network, a first search query to search a first searchable document set, the first search query including a first search term in a first language; applying a first tokenization rule to identify the first search term in the first search query; determining that the first search term is in the first language; applying a second tokenization rule to tokenize the first search term based on the first search term being in the first language; causing a launch of a search instance by a managed compute service of the provider network, the search instance to execute a search function for a keyword-based text search using the tokenized first search term.

A text search method is disclosed. The text search method includes, based on a query including a text being input, computing a vector value having a preset size by using a preset encoding algorithm, the vector value corresponding to the text, generating a query ciphertext by homomorphic encryption for the computed vector value, transmitting the generated query ciphertext to a server, receiving a calculation result ciphertext having similarity information with the query for each of a plurality of indexes, determining an index having a preset similarity by restoring the calculation result ciphertext, and receiving information corresponding to the index by transmitting the determined index to the server.

The invention belongs to the field of artificial intelligence, and particularly relates to an intelligent customer service question and answer processing method, a server and a storage medium. The intelligent customer service question and answer processing method comprises the following steps: acquiring consultation questions input by a user, and intelligently classifying the consultation questions to obtain category labels of the consultation questions; searching the consultation question through a vector search channel and a full-text search channel to obtain two search result sets; adjusting the initial weight based on the similarity score of each candidate answer in the two retrieval result sets to obtain a fusion weight of the consultation question in the two retrieval channels; calculating a comprehensive score of each candidate answer based on the fusion weight, and merging and sorting the candidate answers according to the comprehensive score to obtain a candidate answer set; and generating a final answer to the consultation question based on the candidate answer set. According to the method provided by the invention, the retrieval precision and recall ratio are improved, the sorting and correlation of retrieval results are optimized, and the solution rate of user questions is improved.

The invention discloses a device for signing and extracting an original text based on a large model generation result, and the device is characterized in that a knowledge base management module manages an uploaded file, and analyzes and converts the file into an OFD file; the reasoning question-answering module selects a question-answering model to set a corresponding question-answering prompt word, returns reasoning content and records a file source and an address corresponding to the reasoning content; the original text searching module reads the reasoning result and the original text reference; the diversified endorsement module combines and displays the generated file and the original text, and carries out diversified endorsement and rendering; the combination file generation module synthesizes the signed files to form an OFD file combination file book with the signing effect, and meanwhile, the access of a third-party personnel organization structure is supported, and the files are audited. Based on an artificial intelligence large model and a private knowledge base, a user can initiate services fundamentally, and the user experience is improved. And the knowledge base and the business initiation content are quickly combined by adopting a file combination technology, so that the file organization time of the user is shortened.

The invention relates to the technical field of rich text processing display, in particular to a method for processing rich text highlighting through list display under a Harmony Next App, which comprises the following steps of: firstly, obtaining rich text contents containing HTML (Hypertext Markup Language) format tags, analyzing the rich text through modes such as regular expression matching, generating node data of a tree structure, and introducing a dynamic weight distribution algorithm to optimize tag analysis priority; and reducing redundant data by using a node similarity merging algorithm. Based on node data, a Harmony OS native component is used for carrying out fine-grained rendering, according to business logic or keywords input by a user, font color attributes of a Span component are dynamically adjusted, highlight display is achieved, and a style and rendering logic are decoupled to flexibly configure a highlight strategy. According to the method, a pre-analysis and caching mechanism, lightweight rendering and other strategies are adopted to optimize the performance, and the method is suitable for various scenes such as rich text search keyword highlighting, specific field style emphasizing and multi-theme switching real-time style adaptation.

The invention relates to an OA cloud service platform based on data sharing, and the platform comprises a data time sequence analysis module which is used for carrying out the seasonal decomposition and trend prediction of standardized historical sales data through employing a Prophet algorithm, and generating a sales prediction data set containing periodic features and a trend curve; the fusion module is used for receiving the structured product database and the sales prediction data set, performing feature alignment and dimension association with business data of an enterprise ERP system, and outputting a multi-source fusion data cube with a unified space-time label; and the spatio-temporal data warehouse architecture module is used for constructing a distributed data lake based on a Hadoop ecological system, implementing column type storage optimization on the multi-source fusion data cube, and integrating an Elasticsearch full-text retrieval engine to form a data warehouse supporting spatio-temporal dimension online analysis processing. According to the invention, the enterprise business process management efficiency, the data security and the decision intelligent level are improved.

A system for contextual matching video content based on multimodal metadata extraction generated by processing one or more scenes to extract metadata corresponding to multiple extraction modes, and an embedding model for each extraction mode wherein an aggregated embedding model responsive to said metadata embeddings for each mode formulates an aggregated embedding with an embedding extractor responsive to a text input with an embedding model coordinated with said embedding model wherein said embeddings are in the form of a vector, and a vector comparison processor for determining the distance between the query vector and a vector representing the aggregated embedding. The coordination between embedding models is established by training. The embedding extractor may accept a free-form text query and present one or more subqueries for embedding. A textual inversion engine may be provided to generate an image from the embeddings to provide feedback to a user. In this way a user can confirm the effectiveness of the text query. A text editor may be provided for a user to enter and to edit a query.

The present application relates to a system for acquiring natural medicinal material domain-specific knowledge. The system comprises a dialogue application program, a first learning model, a search engine, and a natural medicinal material domain-specific knowledge base. The dialogue application program provides a user interaction interface for a user, receives a user question of the user intending to acquire natural medicinal material domain-specific knowledge, and presents to the user an answer generated by the first learning model. The first learning model generates an answer to the latest user question on the basis of a dialogue history of the user, or uses the search engine to perform information retrieval on the natural medicinal material domain-specific knowledge base by employing at least one of coreference-based graph search, vector search and full-text search, to acquire background knowledge associated with the user question, and generates an answer to the user question on the basis of the dialogue history embedded with the background knowledge. According to the system of the present application, the user can intelligently and accurately acquire required authoritative, accurate, standardized and comprehensive natural medicinal material domain-specific knowledge in a friendly dialogue mode.

The invention discloses an RAG document splitting optimization method and system in the operator field, and belongs to the technical field of large model optimizing.The method comprises the steps that a document is uploaded, and source files and file information are stored through minio and paradeDB respectively; constructing a document loader, automatically selecting a corresponding loader according to a file type to carry out file processing, converting the file into a uniform Markdown text, analyzing a picture in the document, and converting the picture into a base64 format; constructing a picture processor, extracting a picture base64 character string in the text, processing a bitmap and a vector diagram, and converting the bitmap and the vector diagram into a Markdown picture reference format; constructing a document divider; vector conversion; and recalling the text. According to the method, the problem that picture extraction, conversion and processing are complex in the current RAG is solved, vector retrieval, full-text retrieval and mixed retrieval functions can be achieved through one database, and the operation and maintenance cost is reduced.

This application provides a data processing method, apparatus, device, and medium. The method includes: acquiring a first text containing business text data; performing a risk assessment on the first text to obtain a risk category result corresponding to the first text; if the risk category result is a first risk category, acquiring keywords of the business text data and searching for the keywords in a standard database; if a request text matching the keywords is found in the standard database, determining the feedback text corresponding to the request text as the business processing result corresponding to the business text data; if no request text matching the keywords is found in the standard database, performing text search processing on the business text data in a target knowledge graph to obtain a business processing result matching the business text data. Implementing this application embodiment can improve the security of text data.

The invention discloses a text search method and system, electronic equipment, a storage medium and a product, and relates to the field of large model technology and artificial intelligence. The method is applied to a server and comprises the steps that a first text sent by a client side and context information associated with the first text are received, the first text is used for representing a text selected in operation pages displayed on the client side, and the context information at least comprises page information of the operation pages and historical operation information of the operation pages; performing semantic analysis on the first text to obtain a semantic analysis result of the first text; searching based on the semantic analysis result and the context information to obtain a search result; and sending the search result to the client. According to the method and the device, the technical problem of relatively low accuracy of a search result during intelligent word segmentation search is solved.

To provide a sentence generation device, a control method of the same, an information processing system, and a program which simply determines reliability of a generated reply sentence.SOLUTION: A sentence generation device includes: a quoted sentence retrieval unit which acquires a sentence related to a question sentence as a quoted sentence; an answer generation unit which generates an answer sentence to the question sentence by using the quoted sentence; a reliability calculation unit which calculates the reliability of the answer sentence on the basis of the quoted sentence and the answer sentence; and a hallucination determination unit which verifies consistency of the answer sentence and the quoted sentence, and calculates the reliability with the reliability calculation unit.SELECTED DRAWING: Figure 1

The invention belongs to the field of information retrieval, particularly relates to a full-text retrieval method and system, computer equipment and a computer readable storage medium, and aims to solve the problem of improving the full-text retrieval accuracy. The method comprises the following steps: segmenting a document entering a corpus; calculating paragraph weights of words contained in each segmented document in the segmented document; calculating the document weight of the word in the document according to the paragraph weight of the word; calculating the query weight of the query word, wherein the calculation method of the query weight is the same as the calculation method of the paragraph weight; determining a corresponding target word in a corpus according to the query word; respectively calculating one or more query relevancy according to the query weight and the document weight of the target word; and taking the document corresponding to the document weight corresponding to the maximum n query relevancy as a query result. Semantic features are introduced into weight calculation, and document segmentation processing is combined, so that the full-text retrieval accuracy is effectively improved.