122 results about "Fuzzy query" patented technology

The invention relates to the cross technical field of business intelligence and natural language processing, in particular to an interactive AI report generation method and system based on intelligent semantic driving, and the method comprises the steps: (1) a large language model analyzes user question semantics, calculates the matching degree with a report subject, and dynamically selects a question correction or report generation process; (2) the fuzzy query is converted into a deterministic request based on the domain knowledge base, and semantic ambiguity is eliminated; (3) analyzing field association in combination with database metadata, and generating an executable SQL (Structured Query Language); (4) dynamically rewriting SQL (Structured Query Language) according to user roles, adding permission filtering conditions, executing query and desensitizing sensitive data; (5) analyzing result features, automatically matching a visual form and generating natural language interpretation; and (6) collecting user feedback, and optimizing a semantic model and a query strategy. According to the scheme, the accuracy of natural language query and the adaptive capacity of the system can be remarkably improved, and the security of data access is guaranteed.

The invention relates to a railway train equipment fault diagnosis method and system based on a domain knowledge graph. The method comprises the following steps: acquiring and screening railway train equipment fault data; extracting a structured entity in the fault data of the railway train equipment, linking the structured entity and the defined relationship, and generating a triple; calculating the similarity between the structured entities, and performing short alignment updating on the triple according to the similarity between the structured entities; the updated triple is stored in a graph database, and construction of the knowledge graph is completed; and performing fault diagnosis by combining retrieval of a graph database and reasoning of a knowledge graph, and determining a fault reason. According to the technical scheme, railway train equipment fault diagnosis based on the domain knowledge graph is achieved, the problem that historical text data cannot be fully utilized in traditional fault diagnosis can be solved, and the problems that fault analysis association is weak and efficiency is low are solved by combining fuzzy query and knowledge graph reasoning.

The invention relates to the technical field of communication, and discloses a switch fault elimination method and device, equipment, a storage medium and a product, and the method comprises the steps: monitoring a multi-network-layer performance index of a switch through integrating a plurality of network protocols, building a fault prediction model based on a machine learning algorithm, and identifying the multi-network-layer performance index by using a fault prediction model to obtain an identification result, and when the identification result is an abnormal mode, performing fuzzy query by using a media access control address and an internet protocol address to obtain a fault source, and removing the fault source according to a preset repair strategy. According to the method, multiple network protocols are integrated, the multi-network-layer performance indexes of the switch are comprehensively monitored, the fault is identified by using the model constructed by the machine learning algorithm, the fault source is positioned through the media access control address and the internet protocol address, and the fault is eliminated according to the preset repair strategy, so that the operation and maintenance efficiency of the switch is effectively improved; and the fault influence range is reduced.

The invention relates to an encryption method, a decryption method, a word segmentation one-way encryption method, equipment and a medium. The method comprises the following steps: when plaintext service data is obtained, querying whether a memory stores a corresponding local service key or not; if it is queried that the memory does not store the corresponding local service key, signature verification information is generated, and the signature verification information and the master key identifier are sent to the master device; the signature verification information and the master key identifier are used for indicating that the master device generates a first ciphertext key based on a symmetric encryption algorithm and the master key identifier after verification based on the signature verification information and the master key identifier is passed, and generates a second ciphertext key based on an asymmetric encryption algorithm and the signature verification information; receiving a first ciphertext key and a second ciphertext key sent by the master device, and encrypting the plaintext service data by using the second ciphertext key to obtain ciphertext service data; and outputting the ciphertext service data and the first ciphertext key. Therefore, the security level of data encryption storage can be improved, and the availability of a fuzzy query function is guaranteed.

The invention discloses a multi-modal design work intelligent classification and retrieval system based on deep learning, and relates to the technical field of multi-modal deep learning retrieval. Image, text and audio features are extracted through MS-CNN and Transform; realizing cross-modal semantic fusion by using a knowledge graph and GNN; the hierarchical cascade classifier is combined with incremental learning to realize rapid and accurate classification; the semantic enhancement retrieval supports fuzzy query and cross-modal retrieval; in addition, the system also has the functions of design collaboration, quality evaluation and safety operation and maintenance, and the design resource management efficiency is improved. According to the method, multi-modal data are fused, design features are accurately extracted, cross-modal deep correlation analysis is achieved, through intelligent classification, semantic retrieval and personalized recommendation, the design resource retrieval efficiency and accuracy are improved, meanwhile, data safety is guaranteed, design cooperation is supported, a designer is assisted to rapidly obtain inspiration and grasp the design trend, and the design quality is improved. And the intelligent development of the design industry is promoted.

The invention relates to the crossing field of an artificial intelligence technology and an automotive electronic technology, and discloses a voice interaction question answering method and system based on a vehicle-mounted large model knowledge base, and the method comprises the following steps: receiving a user query text, and executing intention recognition and structured analysis; based on an analysis result, constructing and executing a mixed retrieval request including structured filtering, full-text keyword retrieval and semantic vector retrieval; fusing and reordering the plurality of retrieval result sets obtained respectively to obtain a high-quality final retrieval result set; and finally, constructing a context based on the final retrieval result set and a user query text, and calling a large language model to generate and output a final answer. By introducing a hybrid retrieval and fusion reordering mechanism, comprehensive context information is provided for a large language model, the accuracy and reliability of questions and answers are improved, and the ability of a system to understand and process complex fuzzy queries is enhanced.

The invention relates to a retrieval method and device based on multiple fuzzy keywords, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring locality sensitive hash data corresponding to a query keyword, wherein the locality sensitive hash data is obtained by processing the query keyword through a locality sensitive hash algorithm; and based on the locality sensitive hash data corresponding to the query keyword and the target index vector of each document, calculating an evaluation score corresponding to each document, the evaluation score representing the matching degree of the document and the query keyword, and obtaining a target document. By adopting the method, fuzzy query can be realized by combining the locality sensitive hash data calculated by a p-stable locality sensitive hash (LSH) algorithm, the retrieval flexibility in the field of ciphertext retrieval of the document is improved, the degree of correlation between the target document and the query keyword is improved, the accuracy and effectiveness of the query result are ensured, and the query efficiency is improved. And the data retrieval efficiency is further improved.

The invention relates to a network equipment alarm analysis method based on a user-defined multi-layer analysis rule, which is characterized by comprising the following steps of: 1, carrying out segmentation and slicing on a processing rule by customizing the multi-layer analysis rule according to requirements, namely, carrying out segmentation processing on a complex analysis processing requirement, and solving the problems of high complexity and poor flexibility of analysis rule configuration in the existing scheme. Defining an alarm analysis range tuple, and constructing a multi-level alarm analysis rule according to service requirements and the analysis range tuple; 2, receiving an alarm message according to an alarm message object structure defined by a system, performing fuzzy query on an alarm analysis rule according to analysis range tuple information and an alarm category identifier in an alarm message object, and analyzing an alarm object attribute according to the analysis rule; and step 3, outputting analyzed alarm object information after completing alarm analysis processes of all levels in multiple cycles.

The invention relates to the technical field of natural language processing, in particular to a verifiable large model retrieval enhancement generation system and method based on an evidence chain, and the method comprises the steps: receiving an initial query, recognizing the fuzziness and information gap of the initial query in combination with an associated retrieval document, and generating a supplementary query set; based on the initial query, the supplementary query and the corresponding retrieval document, generating candidate answers with references and verifying the information supportability of the candidate answers; for the candidate answers passing the verification, extracting support information and constructing a hierarchical attribution mapping relation; and integrating the information to form to-be-evaluated information, and if the current verified to-be-evaluated information meets a preset sufficiency condition, integrating the generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The method effectively overcomes the defects that a traditional RAG system is fragmented in information integration, has one-sided fuzzy query and answer, is low in attribution efficiency and excessively depends on retrieval content, and has the advantages of answer comprehensiveness, verifiability and deployment lightweighting.

The invention relates to the technical field of government affair services, in particular to an NLP entity recognition method based on semantic extension, which comprises the following steps: collecting multi-source time sequence data and generating an entrepreneurship ecological data graph through a dynamic time warping algorithm; dynamic evolution of a term library is realized by using a generative adversarial network, and a term semantic association graph is constructed in combination with a graph convolutional network; a double-path attention mechanism is deployed in a Transform encoder, and global semantics and local attention guided by terms are fused through a gating loop unit; modeling fuzzy query analysis into a Markov decision process, and optimizing a semantic extension strategy by adopting a reinforcement learning agent; multi-granularity features are extracted through a feature pyramid network, and model parameters are optimized in combination with a bidirectional long-short-term memory network and an online learning feedback loop; and finally, calculating entity service association strength by using a graph attention network, and generating an interpretable report based on a Shapley value attribution algorithm. A closed-loop learning system is formed, and the business starting policy matching accuracy is improved.

The invention relates to the technical field of data processing, and discloses a data query method and device, computer equipment and a storage medium. The method comprises the following steps: receiving text content input to a platform front-end page to obtain a target text; when it is determined that the target text comprises the screening parameters, the screening parameters are transmitted to the target mapping file through the annotations. And in the target mapping file, constructing a fuzzy query statement, and performing fuzzy query to obtain a first standard file information list. When revocation operation is carried out, the standard numbers of the standard files in the revocation state are received, after the operation is repeatedly executed to obtain the first standard file information list, the state of the first standard file information list is modified into a doubt state, and the revocation operation is used for uniformly modifying the states of the standard files quoting the revocation state into the doubt state. According to the method and the device, the quick retrieval and query of the terms and the normative reference file and the function of associating the standard state with the normative reference file are realized, and the retrieval efficiency and accuracy are 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 provides an entity enhancement and context-aware paragraph retrieval method for an RAG system for solving the problems of fuzzy query intention and insufficient paragraph context modeling in RAG retrieval. The method comprises the following steps: firstly, identifying and extracting a key entity by using a named entity, carrying out weighted fusion on the key entity and question representation obtained by a pre-training model to form an enhanced query vector, and accurately describing a core semantic intention of the question; secondly, performing semantic modeling on paragraphs in a document library, mining a potential semantic association relationship between the paragraphs, and constructing a context interaction model between the paragraphs based on a graph neural network and a gating loop unit mechanism, so as to obtain paragraph vector representation with complete semantics and clear hierarchy; and finally, calculating the similarity between the enhanced query and the paragraph vector, and completing high-precision paragraph-level retrieval. According to the method, the correlation and the recall rate are remarkably improved, insufficient entity utilization and weak context modeling are relieved, and good expansibility and cross-domain applicability are achieved.

The invention provides a server and a knowledge base construction method, and relates to the technical field of database processing. The server obtains medium resource information and a query category set, the medium resource information comprises a plurality of medium resource labels and medium resource information contents corresponding to the plurality of medium resource labels, and the query category set comprises a plurality of query categories; determining at least one media asset label combination of the query category; wherein the media asset label combination comprises one or more media asset label categories; determining at least one prompt template corresponding to the media asset label combination, wherein the prompt template is used for indicating the number of data documents corresponding to the query category and media asset information content corresponding to media asset labels in the media asset label combination; inputting the prompt template into a first preset training model to obtain a data document; wherein the data document is used for representing to-be-queried data corresponding to the prompt template; and constructing a knowledge base according to the data document. According to the server provided by the embodiment of the invention, the knowledge base meeting the fuzzy query requirement can be constructed, and the user experience of a user during fuzzy query is improved.

Systems and methods are described herein for providing a search result based on an ambiguous voice query. The system comprises receiving an ambiguous voice query relating to an object from a user, retrieving a viewing history of the user for about a list of media assets viewed by the user, determining, from the list of media asset, a media asset that is likely to contain the object based at least in part on metadata of the media asset and the ambiguous voice query, searching content of the determined media asset to identify a segment within the media asset that contains the object, and generating a display of information about the object identified from the segment.

The invention relates to the technical field of ship track area retrieval, in particular to a ship historical track area retrieval method which comprises the following steps: S1, constructing an index; s2, searching a historical track area; the method comprises the following steps: (1) a user gives a geographic space area and a time range as query conditions; (2) adjusting a coding mode of the Google S2; (3) decomposing a geographic space region input by a user by adopting a region coverage algorithm of Google S2 to obtain a group of geographic coding values containing the region; and (4) converting the obtained geocoding value, carrying out quick retrieval by utilizing a MySql database leftmost prefix matching principle and fuzzy query, and giving track data meeting conditions by the database. According to the method, the required query times are reduced, the response speed of the database is accelerated in combination with concurrent query, and the storage pressure of the index is relieved.

This invention belongs to the field of natural language processing and information extraction technology, and provides a method and system for extracting parameters from boiler design documents based on multi-round self-feedback RAG. The method includes: preprocessing the boiler design document and the original query, converting them into several text segments and expected inputs respectively; encoding the text segments and expected inputs into high-dimensional vectors and query vectors respectively, storing the high-dimensional vectors and constructing a vector index; generating a response based on retrieved external knowledge to assist a large language model, and iteratively optimizing the generated results through multiple rounds. This invention effectively solves the problems of incorrect and missing parameter extraction in complex or fuzzy query scenarios, significantly improving the reliability of the final results; it overcomes the limitations of traditional methods and standard large language models in handling multimodal data, enhancing the processing capability for complex multimodal documents; and it improves the accuracy of information retrieval, laying a solid foundation for subsequent accurate parameter extraction.

The invention provides a query method and device of a relational database, electronic equipment and a storage medium, and belongs to the technical field of database information management.The method comprises the steps that a user query request is obtained, and the user query request is divided into a fuzzy query condition and a non-fuzzy query condition; based on a search engine service provided with a fuzzy query data table in the relational database, querying by adopting a fuzzy query condition to obtain an identifier set conforming to the fuzzy query condition; and combining the identifier set with a non-fuzzy query condition to obtain a target query statement, and querying the relational database based on the target query statement. According to the invention, query is carried out based on the fuzzy query condition, and then query is carried out based on the fuzzy query result in combination with the non-fuzzy query condition; the problems that an existing database query method cannot meet the requirement for included query of meaningless character strings, the data size of a data table is very large, and the query requirement for accurate matching of an association table exists can be solved.

The embodiment of the invention provides an information processing method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring initial information input by a user; when the initial information is a data query task, determining at least one target database corresponding to the initial information; the at least one target database is screened from a plurality of databases; determining at least one piece of accurate query information corresponding to the initial information based on a first text processing model according to the initial information and the information of the at least one target database; according to the at least one piece of accurate query information, the query result corresponding to the initial information is determined, the query intention of the user can be more accurately understood, the uncertainty caused by fuzzy query is reduced, the correlation and accuracy of the query result are improved, at least one target database is screened out from the multiple databases, and the user experience is improved. The query is ensured to be performed in the most relevant data source, and the screening process can reduce unnecessary data processing and improve efficiency.

The application relates to the technical field of natural language processing, in particular to an evidence chain-based verifiable large model retrieval enhancement generation system and method, which comprises the following steps: receiving an initial query, identifying the ambiguity and information gap of the initial query in combination with associated retrieval documents, and generating a supplementary query set; generating a cited candidate answer based on the initial query, the supplementary query and the corresponding retrieval document, and verifying the information supportability of the cited candidate answer; extracting supportable information from the verified candidate answer and constructing a hierarchical attribution mapping relationship; integrating the above information to form to-be-evaluated information; if the to-be-evaluated information currently verified satisfies a preset sufficiency condition, integrating a generated preliminary answer and the to-be-evaluated information to synthesize a target answer. The application effectively solves the defects of the traditional RAG system, such as information integration fragmentation, one-sided query answering, inefficient attribution and excessive dependence on retrieval content, and has the advantages of comprehensive answer, verifiability and lightweight deployment.

The invention provides an anti-fraud early warning system based on multi-source cross-platform fusion, belongs to the field of network security and privacy computing, and aims to solve the problems of privacy set intersection matching failure and early warning missing report caused by data noise. According to the scheme, data are cleaned through a multi-modal normalization engine, and the cleaning distortion degree is calculated; generating a fuzzy feature vector containing a plurality of variants through a fuzzy feature mapper to avoid the Hash avalanche effect; performing privacy set intersection in a ciphertext domain through an encryption calculation unit; and finally, a risk decision-making module combines the variant weight and the time decay factor to carry out weighted scoring and generate an early warning. According to the method, accurate matching is upgraded into fuzzy query, so that the early warning robustness and accuracy are remarkably improved, and risk quantification and privacy security are realized at the same time.

This invention discloses a method and system for intelligent chart querying based on a large model of multimodal data. The method includes acquiring fuzzy query information input by the user and real-time monitoring data of a machine tool; performing intent recognition and entity extraction on the fuzzy query information, parsing it into structured query conditions; establishing a multimodal data association library based on a large model, inputting the real-time monitoring data of the machine tool into the multimodal data association library, and storing it according to preset association requirements; inputting the structured query conditions into the established multimodal data association library; and generating interactive charts based on the output information of the multimodal data association library, embedding key conclusion summaries. This application utilizes a large model to understand user intent and dynamically recommend related charts, breaking through the traditional fixed menu navigation mode and realizing intelligent interaction through joint analysis of data and charts.

A system including a processor and a non-transitory computer-readable media storing computing instructions that, when executed on the processor, cause the processor to perform certain operations: generating a first ambiguity score for a first query; propagating the first ambiguity score for the first query to generate a second ambiguity score for a second query; training a machine-learning classifier at least based on the first query and the second query; and generating, using the machine-learning classifier, a third ambiguity score for a third query. Other embodiments are described.

The invention provides a time sequence data query method and system, a readable storage medium and a computer, and the method comprises the steps: extracting a data label of each piece of time sequence data in a historical time sequence data set, and carrying out the data processing according to the data labels and each piece of time sequence data to obtain similar sequence data; inputting the similar sequence data, the time sequence data and the corresponding data labels into a preset model learning device to construct a condition generation model; performing data dimension raising processing on the obtained current time sequence data to obtain an ordered point list, and comparing the ordered point list of each current time sequence data with a data threshold to obtain a mark point; and inputting the fuzzy query condition and the mark point into a condition generation model to calculate the matching degree of the current time sequence data, and outputting a query result according to the matching degree. According to the method, the exploration and query capabilities of the time sequence data set are enhanced based on a fuzzy query mode, so that the data query efficiency is improved.

The present application provides a data verification method, device and computer readable storage medium, comprising: obtaining a received key encrypted to-be-verified user identifier, and constructing a fuzzy query condition based on the encrypted to-be-verified user identifier to query the serial number corresponding to the user identifier from a receiver; receiving the query result fed back by the receiver, wherein the query result comprises a plurality of receiver user identifier ciphertext values and corresponding serial numbers matched with the fuzzy query condition; matching the encrypted to-be-verified user identifier with the receiver user identifier ciphertext values in the query result, and if the matching is successful, obtaining the user attribute encrypted by a homomorphic encryption algorithm corresponding to the to-be-verified user identifier based on the corresponding serial number; calculating the difference between the homomorphic encryption value of the user attribute of the requester and the homomorphic encryption value of the user attribute obtained from the receiver through ciphertext calculation, and sending the difference to the receiver; receiving the verification result fed back by the receiver after decrypting and analyzing the difference.

The invention discloses a vehicle navigation data storage method and system. The method comprises the following steps: establishing a vehicle navigation rendering map user side and a vehicle navigation data storage cloud platform; storing the vehicle navigation data to a vehicle navigation data storage cloud platform; the vehicle navigation rendering map user side receives a user navigation destination request; the vehicle navigation rendering map user side sends a user navigation destination request to the vehicle navigation data storage cloud platform for query; the obtained user navigation destination request is subjected to fuzzy query in the vehicle navigation data, and the queried vehicle navigation data is ranked and fed back to the vehicle navigation rendering map user side for the user to select and confirm; and the vehicle navigation data storage cloud platform transmits the vehicle navigation data selected and confirmed by the user to the vehicle navigation rendering map user side for navigation display. The problem that the use efficiency of a storage system is influenced by the increase of the existing vehicle navigation data storage space is solved.

This application provides a method, apparatus, electronic device, and storage medium for generating network topology maps. The method includes: acquiring XDR data, core network configuration data, and B-domain data corresponding to a target enterprise; performing data filtering processing on the XDR data, core network configuration data, and B-domain data to generate a network data field table; constructing a network device service path table corresponding to the network devices within the target enterprise based on the network data field table; and drawing a network topology map corresponding to the target enterprise based on the core network node configuration conversion table and the network device service path table. This application can realize real-time updated full-path visualization applications, fuzzy queries by slice, enterprise name, or DNN, presentation of key indicators and alarms, and achieve functions such as visibility, manageability, and evaluation of private network services, adapting to the needs of refined management of private network resources.

The invention discloses a multi-modal data intelligent chart query method and system based on a large model. The method comprises the steps that fuzzy query information input by a user and real-time monitoring data of a machine tool are acquired; performing intention recognition and entity extraction on the fuzzy query information, and analyzing the fuzzy query information into a structured query condition; establishing a multi-modal data association library based on a large model, inputting the real-time monitoring data of the machine tool into the multi-modal data association library, and storing the real-time monitoring data according to a preset association requirement; and inputting a structured query condition into the established multi-modal data association library, generating an interactive chart according to output information of the multi-modal data association library, and embedding a key conclusion abstract. According to the method, the user intention is understood through a large model, the association chart is dynamically recommended, a traditional fixed menu navigation mode is broken through, and data and chart conjoint analysis intelligent interaction is achieved.

An exemplary system and method are disclosed that provide the private querying of a biometric scan, such as a person's photo, against a private database such that the client issuing the private query learns only the identity of the query if it is in the database while the server performing the processing learns nothing of the biometric scan. The exemplary system and method conduct privacy-preserving searches over fuzzy databases via a fuzzy labeled set intersection (FLPSI) protocol. FLPSI protocol computes an intersection of noisy input sets to assess for closeness / similarity metrics in an efficient and optimized search.

The invention relates to a data processing technology, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a data visualization configuration method, device and equipment and a storage medium, the method comprises the following steps: carrying out word segmentation on a preset target text to obtain a word segmentation text; performing keyword extraction on the word segmentation text according to a preset part-of-speech rule to obtain a target keyword; performing fuzzy query in a preset database according to the target keyword to obtain a query field; performing data query in the database according to the query field to obtain target data; and displaying the target data returned by the database on a visual interface. According to the method, the data visualization efficiency and the data query accuracy can be effectively improved.