28 results about "Keyword search" patented technology

The present disclosure provides an event search method and device and a storage medium, wherein the method comprises: obtaining event words corresponding to event description information, and generating word vector information corresponding to the event words; constructing an event phrase based on the event words, and determining weight information of each event word constituting the event phrase; generating phrase vector information corresponding to the event phrase according to the word vector information and the corresponding weight information; performing expansion processing on a search word based on the word vector information and the phrase vector information to obtain an expanded word corresponding to the search word, and performing event search processing. The present disclosure can avoid the case of partial search result loss caused by searching according to an input keyword, can avoid the case of returning a large number of irrelevant results according to word-level retrieval, and improves the accuracy of search results.

The application provides a kind of synchronous radiation light source data migration method, system and electronic equipment, relate to data storage technical field, the method can be based on the creation time, access time, access frequency and keyword search word frequency of data and other factors Quantification of the temperature of data, and according to this temperature, the future access mode of data is estimated, the accurate judgment of hot temperature cold data is realized, and the hot temperature cold data can be more reasonably stored in the corresponding hot temperature cold storage pool, solve the problem that the synchronous radiation light source data in the prior art exists in the process of data migration Data migration is not reasonable, the problem of low data migration efficiency.

Outputs information for children. [Solution] The drive plan generation system (1) includes a determination means (11) that determines whether or not a facility searched according to the user's request is a facility for children, a first generation means (12) that generates child-friendly keywords related to the searched facility if it is determined that the searched facility is not a facility for children, a search means (13) that searches for child-friendly information related to the searched facility using the generated keywords, and an output means (15) that outputs facility information indicating the searched facility and child-friendly information that was searched.

It is difficult for users to quickly find the documents they want. [Solution] The information processing system disclosed herein comprises a storage unit for storing document data, a reception unit for receiving search keywords entered on a search screen displayed on a user terminal, and a search unit for displaying search results obtained by searching document data based on the search keywords on the search screen. The storage unit stores document data associated with complementary keywords, the reception unit displays complementary keywords associated with the received search keywords on the search screen so that the user can select them, and accepts the selected complementary keywords, and the search unit searches document data based on the accepted complementary keywords.

A computing device receives a query and determines one or more alternative query terms based on the query. The computing device identifies application modules that match the alternative query terms. The computing device identifies content by performing at least one queryless query based on the one or more alternative query terms. The computing device outputs at least one query preview that includes a reference to at least one application module from the one or more application modules, or at least one query result that includes a reference to the content.

Techniques for improved generation of a search response are disclosed herein. An example computer-implemented method includes receiving an initial input from a user; determining, by applying at least a keyword search transformer and a semantic search transformer to the initial input, a plurality of search queries; applying, at least a keyword search engine and a semantic search engine corresponding to the keyword search transformer and the semantic search transformer to process the plurality of search queries to obtain a plurality of search results; ranking the plurality of search results based on their respective search scores; and generating by applying a large language model to the ranked plurality of search results and the initial input, a search response.

The application provides a mass log analysis method based on log template compression and a large language model, comprising the following steps: S1, task receiving and analysis, analyzing a natural language analysis task into structured task information; S2, agent decision and analysis strategy generation, dynamically determining an analysis strategy and tool calling parameters; S3, double-path data acquisition and compression, compressing GB-level original logs into KB-level structured abstracts through template matching statistics, and acquiring detailed information through keyword search; S4, result integration and semantic enhancement, adding business semantic information to the template matching statistics result; S5, agent iterative analysis and reasoning, performing pattern recognition and iterative in-depth analysis based on the semantic enhancement abstract; and S6, generating an analysis report; the application solves the problem that a large language model cannot directly process mass logs, realizes a high compression ratio, completely retains key information, and endows the log data with business semantics.

This invention discloses a data processing method for horizontal pipe lifting. This method utilizes Python's keyword search function to retrieve and extract all data requiring processing. It includes the paths to the text files to be processed, the paths to the processed output files, and the ship's side length. A Bayesian parameter optimization algorithm is introduced to optimize data requiring maximum values, leading to more accurate determination of these values. The output report is in Excel format, providing a clear view of the processed data. The entire system is encapsulated into an application using Python for rapid horizontal pipe lifting calculations. This invention provides a horizontal pipe lifting data processing method that uses Python as the development language and employs a Bayesian parameter optimization algorithm to process data during the horizontal pipe lifting process. This algorithm can better determine the maximum and minimum values ​​of key parameters such as axial force, stress, and bending moment during the lifting process, thereby determining the feasibility and safety of the lifting operation.

The application provides a large model-based intelligent work order processing method, system, device and medium, and relates to the technical field of computer data processing and artificial intelligence. The method comprises the following steps: acquiring work order data containing text and images, calling a large language model and a visual large model to extract structured fault features; after the fault features are vectorized, searching in a multi-type knowledge base, and constructing prompt words through a three-level weighted fusion mechanism to input the large model to generate an optimal processing scheme; meanwhile, combining historical maintenance data and a variance threshold algorithm to predict accessories and dispatch. In addition, the system supports front-end interception and real-time push of self-service solutions. Through multi-modal analysis, structured knowledge fusion and large model proxy mechanism, the application breaks through the limitations of traditional keyword search, realizes accurate fault recommendation, on-demand preposition of accessories and simple work order intelligent interception, and significantly improves after-sales efficiency and customer experience.

In an example embodiment, embeddings are used to securely search sensitive encrypted data stored in a database without the need to retrieve and decrypt all data in a volume. Specifically, a piece of text is embedded into an embedding, which is then stored in a vector database. Then the piece of text can be encrypted and stored in another database. A linkage between the embedding and the ciphertext can also be stored. When a search is performed, one or more keywords from the search can be embedded and the keyword embedding can be compared to the embeddings in the vector database to locate similar embeddings. The ciphertexts corresponding to those similar embeddings can then be retrieved from the other database and decrypted. The decrypted ciphertexts can then be searched based on the keywords to find exact matches.

The application provides a keyword search method for a table document and an electronic device. The method comprises: analyzing the table document to obtain a plurality of candidate text blocks containing position information and text content; dividing all the candidate text blocks into a plurality of virtual columns according to the position information of each candidate text block; for each virtual column, determining a column semantic label of the virtual column according to the text content of the candidate text blocks in the virtual column; screening a virtual column with the same column semantic label as a query field contained in a to-be-searched keyword to form a semantic matching group according to the query field and the column semantic label of each virtual column; and searching an effective text block matching query content contained in the to-be-searched keyword from the virtual columns contained in the semantic matching group. The scheme has low cost and high efficiency, and through semantic understanding, the false recall rate is reduced and the precision rate is improved.

Provided is a method for analyzing technology including an information collection step of designing a metaframe structure for keywords to be analyzed, deriving a technology structure based on the metaframe structure using a generative AI model, generating search keywords based on the derived technology structure, and searching and obtaining a plurality of documents based on the search keywords; and a technology classification step of refining the plurality of documents according to a similarity between the documents, performing preprocessing to utilize contents of the plurality of documents, and then performing detailed technology classification based on results obtained by performing content-based clustering, and a device for processing the method.

The application discloses an attribute-based encryption method and system supporting quick multi-keyword search with access strategy hiding, and the method comprises the following steps: step one, a trusted agency generates a master key, generates system parameters according to the master key, and sends the system parameters to a medical data owner and all users; step two, the medical data owner generates a user key according to the system parameters, and sends the user key to all users; step three, the medical data owner generates ciphertext, and sends the ciphertext to a cloud server; step four, a user generates a trapdoor according to a search keyword set and the user key, and sends the trapdoor to the cloud server; and step five, the cloud server matches the keywords in a medical data plaintext keyword set with the keywords in the search keyword set in the trapdoor, if the matching is successful, decryption is performed, and if the matching fails, no matching result is displayed. The application improves the privacy of user information, and also provides multi-keyword search and quick search functions.

A method performed by an electronic device is provided. The method includes receiving, from a user, a request to search for content of a video; identifying, among scenes included in the video, a target scene associated with the request; collecting metadata associated with the video; extracting scene information representing the target scene based on the metadata; generating keywords based on the metadata and the scene information; performing a search based on a first keyword among the keywords; and controlling a display to display a keyword search user interface (UI), the keyword search UI including a search result UI element that represents a result of the search based on the first keyword.

The application relates to the technical field of computer software and front-end development, and discloses a standard parameter quick query system and method based on front-end technology, which comprises an administrator end and a user end; a data management module of the administrator end parses a table file and saves standard data to a local storage, and a dynamic generation module combines the standard data with interface code and algorithm code to generate an independent HTML file; the independent HTML file is transmitted to the user end and runs in a terminal browser; a query interface module and a core processing module are integrated in the independent HTML file, and the core processing module executes keyword search, range matching and expression calculation logic in the browser front-end environment. The application can realize parameter query without establishing a network connection with a back-end server, solves the problem that the application cannot run in a network-free environment, avoids front-end and back-end communication delay, and reduces deployment cost.

This disclosure provides a method and apparatus for generating product description information, relating to computer technology and data processing, particularly big data. The specific implementation involves: extracting product keywords from historical product search information; searching for target products based on these keywords; and generating product description information for the target product based on its product information and historical search information. This approach reduces the complexity of user operations, improves the efficiency of generating product description information, and the product description information determined jointly by product information and historical search information is more unique, thus improving its relevance to user needs.

The invention relates to an alarm processing method and device. The method comprises the following steps: grouping a plurality of alarm condition texts in an alarm comprehensive database, and respectively screening high-risk important alarm condition texts from each group; after the multiple important alarm texts are classified through a large language model, the incidence relation among the multiple important alarm texts of each class is mined, and a corresponding knowledge graph is constructed for at least two important alarm texts with the incidence relation in each class; when a query request described by a natural language is received, performing mixed retrieval in a police comprehensive database to obtain a target alarm text matched with the query request; the mixed retrieval comprises keyword retrieval and semantic retrieval; and querying an associated alarm text associated with the target alarm text in the knowledge graph to perform case series-parallel analysis on the target alarm text and the associated alarm text. According to the scheme provided by the invention, the technical defects in the aspects of classification efficiency, correlation analysis and semantic retrieval in related technologies can be solved.

This invention discloses a multi-strategy retrieval intelligent question-answering system based on knowledge graphs. Through the collaboration of question parsing, knowledge retrieval, answer generation, and evaluation modules, intelligent question answering is achieved: The system receives user questions, parses the question intent using a large language model, and extracts entities, relation types, and query types; it then performs a multi-strategy progressive retrieval based on a graph database knowledge graph, sequentially performing batch exact matching of entities, batch querying of relations, full-text index search, fuzzy matching, and source file keyword search; it scores and filters the retrieval results based on relevance; it generates answers based on the filtered knowledge using a large language model and calculates the confidence level of the answers by integrating multiple factors; and it implements result caching. This invention, through the synergy of multi-strategy progressive retrieval and intelligent filtering, effectively solves the problems of inaccurate retrieval, poor answer quality, and slow response speed in traditional question-answering systems, significantly improving the accuracy, recall, and response speed of question answering.

This invention discloses a keyword search intent analysis method and system based on GEO, relating to the field of search engine optimization technology. The method includes: constructing an initial clustering structure; extracting locally anomalous node regions based on the local sparse distribution characteristics of semantic matching relationships between nodes and keywords in the initial clustering structure; reconstructing semantic paths between nodes based on the asymmetric topological characteristics of the contextual paths between nodes within the locally anomalous node regions, forming an optimized candidate semantic path set; and determining the subdivided search intent corresponding to the target keyword by combining the non-stationary topological characteristics of the state transition topology of the contextual sequences in the candidate semantic path set and using path state inference from a conditional random field model. This invention achieves the parsing of the multi-contextual semantic structure of search keywords, which is beneficial for the subdivided identification of search intent in a generative engine optimization environment.

The present invention addresses the problem of outputting child-oriented information. The driving plan generation system includes: a determination unit that determines whether or not a facility searched in accordance with a user's demand is a child-oriented facility; a first generation means that, when it is determined that the searched facility is not the child-oriented facility, generates a child-oriented keyword relating to the searched facility; a search unit that searches for child-oriented information related to the searched facility using the generated keyword; and an output unit that outputs facility information indicating the searched facility and the searched child-oriented information.

Techniques for improved generation of a search response are disclosed herein. An example computer-implemented method includes receiving an initial input from a user; determining, by applying at least a keyword search transformer and a semantic search transformer to the initial input, a plurality of search queries; applying, at least a keyword search engine and a semantic search engine corresponding to the keyword search transformer and the semantic search transformer to process the plurality of search queries to obtain a plurality of search results; ranking the plurality of search results based on their respective search scores; and generating by applying a large language model to the ranked plurality of search results and the initial input, a search response.

This application belongs to the field of R&D optimization technology and is applied to the R&D optimization process in the financial industry. It relates to a method, apparatus, device, and storage medium for accelerating cross-server data retrieval. The method includes using the Spark search engine as a retrieval engine, retrieving insurance business data required by each insurance branch to complete its business execution logic from the data source table of the financial data warehouse based on the retrieval fields input by the target user; inputting the required business data into the corresponding target data sub-table and sending it to a preset second data server. By introducing the Spark search engine, Lexica keyword search engine, and AI2SQL platform automatic generation components, the method automatically generates external forms corresponding to each insurance branch, using the Hive public data warehouse data of the insurance head office as the source data. This improves the efficiency of data retrieval from the financial data warehouse and also enables data separation on a per-branch basis.

This invention provides an electronic records management system and application method based on WeChat Mini Programs. The system includes: a user management module responsible for user registration and login, permission allocation, and identity verification; a records management module for records management and version control; a storage management module responsible for records storage, backup, recovery, and cloud synchronization; a query and retrieval module providing query methods including keyword search, category filtering, tag filtering, and geographic information association; a sharing and permission control module for records sharing settings, access control, permission management, and dynamic permission adjustment; a site equipment interface module for data interaction and integration with equipment within the site; and a data analysis and reporting module for statistical analysis of records data, generating various reports and visualization charts to support decision analysis. This system is used to realize the electronic management, storage, query, sharing, and security control of records within a site.

This invention discloses an intelligent matching algorithm based on multi-dimensional knowledge fusion and deep thinking of a large model, belonging to the fields of natural language processing and machine learning. The algorithm includes: S1 collecting and preprocessing data around five core indicators; S2 constructing a high-dimensional vector knowledge base for the meat industry; S3 filtering 50-100 candidate orders through a hybrid vector and keyword search; S4 dynamically adjusting weights based on the scenario, and linearly normalizing the scoring and ranking; S5 re-ranking through deep reasoning using an LLM large model, outputting 3-5 accurate recommendations; S6 analyzing the reasons based on feedback from both buyers and sellers, and optimizing the model, knowledge base, and indicator system using LLM to form a closed loop. This invention provides an intelligent matching algorithm based on multi-dimensional knowledge fusion and deep thinking of a large model, achieving full-dimensional accurate matching of buy and sell orders in the meat industry, intelligent adaptation to dynamic scenarios, and controllable transaction risks, significantly improving the matching success rate and industry transaction efficiency.

The application discloses a kind of medical data searchable encryption systems based on block chain, including system initialization module, medical data file encryption module, medical data file update module, keyword search secret medical data module and medical data and search request supervision module.The application is based on the construction of alliance chain and public key searchable encryption, realizes the retrieval and supervision of ciphertext medical data in multi-user scene, and can realize the availability of medical data while ensuring data security and privacy.

The present application relates to the technical field of information retrieval, in particular to a kind of multi-stage mixed retrieval's meta-analysis literature intelligent screening method and device, wherein the method comprises the following steps: based on the integration of keyword search and semantic search mode in multiple source databases, and according to the query theme specificity to carry out dynamic weight adjustment, then perform all-around search to obtain initial search document set;Based on the multi-dimensional preprocessing of the initial search document set according to literature attribute and data integrity rule, and output structured original document set;Based on the preset screening criteria, the structured original document set is screened by using semantic similarity matching and keyword exact matching fusion technology, and the potential qualified document set is reserved;The potential qualified document set is sorted according to the correlation priority, and high correlation document is preferentially pushed to artificial audit, and multi-party coordination mechanism is established to complete rescreening and output rescreening qualified document set.

This invention discloses a method and system for correlation analysis of traffic violation behavior by rail transit drivers based on LLM (Local Language Model), belonging to the field of traffic violation analysis technology. The method includes: inputting the original text containing driver violation content into a large language model; analyzing and standardizing it using preset prompt words to obtain standardized text; converting it into a high-dimensional vector; calculating the cosine similarity between the standardized text and the standard clause vector; selecting a candidate set and judging it; if the candidate set is not empty, proceeding to the next step; if the candidate set is empty, setting an adaptive degradation and recall strategy; concatenating the original text, candidate set, zero-sample examples, and task instructions, inputting them into the large language model, and outputting the analysis results. If the relevance score is higher than a preset score, returning the matching violation standard; otherwise, returning the fallback standard. This application, through rewriting and rearranging, enables even non-standard descriptions to accurately find corresponding regulatory clauses, with an accuracy rate far exceeding traditional keyword search.

A method for implementing a knowledge-based question-answering system in the field of water conservancy engineering is disclosed. First, using the LangChain expression language and a prompting engineering approach, entities and relationships from the user's input question are extracted through a large language model and output in JSON format. Then, a hybrid search engine, comprising vector search, keyword search, and graph search, is configured sequentially. Based on the entities extracted from the user's input question, vector search, keyword search, and graph search are performed respectively, and the search results are merged. The merged search results are then filled into a preset prompt template, and the constructed prompt statement is output to the large language model to generate an answer, which is then returned to the user. This invention combines the excellent reasoning ability of a large language model with the contextual summarization ability of a knowledge graph, enabling accurate answers to questions within the knowledge scope of water conservancy engineering.