614 results about "Data search" patented technology

The invention relates to the technical field of computers, in particular to a multi-modal data search method, device and equipment based on a generative AI large model, a storage medium and a product. The method comprises the following steps: acquiring various types of data from a plurality of heterogeneous data sources to obtain acquired data; performing feature information extraction on the acquired data based on a preset generative AI large model to obtain feature data; constructing a multi-modal index structure based on the feature data; matching the search instruction with index data in the multi-modal index structure; and fusing and sorting the matching results to obtain a target search result. According to the method, various types of data are collected from a plurality of heterogeneous data sources, a multi-modal index structure is constructed after feature information extraction is performed on the data by adopting a generative AI large model, and the search instruction is efficiently matched with the various types of data, so that the efficiency and accuracy of data query are improved.

A knowledge management system may receive a set of data instances. The system may extract a plurality of entities from the set of data instances. The system may convert the plurality of entities into a plurality of entity embeddings, each entity embedding representing an entity in a latent space. The system may generate a reference embedding that has the same length as the plurality of entity embeddings. The system may compare, for each value in each entity embedding, the value to a corresponding value of the reference embedding. The system may generate a plurality of entity fingerprints, each entity fingerprint corresponding to an entity embedding, each entity fingerprint comprising Boolean values that are generated based on comparing values in each entity embedding to corresponding values of the reference embedding. The system may store the plurality of entity fingerprints to represent the plurality of entities.

A method includes receiving a request to generate a formal language query to search cybersecurity data associated with a plurality of computing resources of one or more entities, wherein the request specifies a natural language query pertaining to the cybersecurity data. The method further includes generating a prompt comprising: (i) at least part of the natural language query (ii) a set of instructions for generating the formal language query and (iii) one or more examples pertaining to the natural language query. The method further includes providing the prompt as input to a trained generative artificial intelligence (AI) model. The method further includes obtaining one or more outputs of the trained generative AI model, the one or more outputs indicating a formal language query corresponding to the natural language query. The method further includes causing the formal language query to be executed to search the cybersecurity data.

The invention discloses an AI-based conference record data searching method and system, and the method comprises the steps: carrying out the feature extraction and alignment through a multi-mode fusion neural network according to the voice, text, image and video data collected in a conference process, and obtaining a semantic representation vector; according to the semantic representation vector, combining context information of the conference scene, and utilizing a pre-trained context perception model to perform semantic enhancement processing to generate an enhanced semantic vector with context association; according to the enhanced semantic vector, combining with an external knowledge base, and utilizing a dynamic knowledge graph construction algorithm to generate a knowledge graph related to the conference theme in real time; and according to the knowledge graph, intelligent retrieval and recommendation of conference record data are carried out by using a graph neural network. By utilizing the embodiment of the invention, the intelligent retrieval efficiency and accuracy of the conference record can be improved.

Methods, systems, and techniques for data searching and querying. A query for retrieving information is received, the information corresponds to a subset of data comprised in a dataset. A response to the query is generated, comprising the information retrieved from the dataset using a series of machine learning models configured to parse datasets. The generating comprises: processing the query; generating an instruction for parsing the dataset according to the processing; and parsing the database using the instruction to return the information. Semantic context for the query can be determined using a machine learning model. Search results determined by parsing the database can be translated into natural language using a large language model. The instructions and search results can be evaluated using one or more arrays of large language models.

The invention relates to a meteorological environment information crawling and analyzing method based on a large language model, belongs to the technical field of meteorological data acquisition and analysis, and solves the problems that the efficiency of acquiring meteorological data by depending on manual data search is low, and unstructured data cannot be fully utilized. Comprising the steps of obtaining a meteorological environment information crawler demand, a meteorological environment information analysis demand and a meteorological environment information report generation demand, and constructing a meteorological environment information crawling cue word, a meteorological environment information analysis cue word and a meteorological environment information report generation cue word in a grading manner based on respective preset cue word templates; performing data crawling on the data source website based on the meteorological environment information crawling cue word and a preset meteorological environment information extraction cue word, and performing similarity measurement on a crawling result and an ERA5 data set to obtain meteorological environment information; and generating cue words based on the meteorological environment information analysis cue words and the meteorological environment information report, and performing information analysis on the meteorological environment information to obtain a meteorological environment information analysis report.

When searching for data using information about drawings, it can flexibly accommodate a variety of use cases. [Solution] A program to be executed by a computer having a processor and a memory. The program causes the processor to execute an output step of inputting drawing information related to a drawing, estimate information related to an estimate for an illustrated object illustrated in the drawing, and a first prompt instructing output of first information related to the illustrated object to a generative AI model and outputting the first information from the generative AI model, a construction step of storing the outputted first information in a database and constructing a search database, an input step of accepting input of second information related to a search target, and a presentation step of searching the search database for first information similar to the second information based on the accepted second information, as similar information, and presenting search information related to the search result.

Systems and methods for searching data management systems. Administrative users may define rules for hashtags, and then the rules are dynamically applied on the fly when an end user searches customer data. Hashtags are used to filter records for specific data, so as to improve data search accuracy and efficiency.

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 embodiment of the invention provides a conference management system and method fusing a large language model and multi-agent collaboration. The system comprises a multi-modal central language large model and a multi-agent platform, and the multi-modal central language large model comprises a multi-modal interaction module, a full-duplex interaction interface, a task reasoning module, a task planning module and an agent scheduling module; the multi-agent platform comprises a data searching and issuing agent, a agenda management agent, a voice transcription agent and a knowledge base updating agent. According to the embodiment of the invention, the conference process is divided into a plurality of independent intelligent agents, and then the intelligent agents are scheduled and dynamically arranged in a unified manner by the central big model. Strategies can be flexibly adjusted according to real-time situations, and intelligence and high adaptability of the whole process are guaranteed. The conference process and the emotional state are monitored. And the central big model sends an intervention instruction. The active conference management can be realized, a targeted intervention means is provided, and the conference efficiency and the communication effect can be improved.

The invention discloses a data search method and system based on artificial intelligence, and relates to the technical field of information retrieval, and the method comprises the steps: receiving a user query, carrying out query analysis, and calculating the similarity between the query analysis and a data point feature vector; constructing a distance matrix, constructing a simple form, and calculating topological characteristics of the simple form through a boundary operator; and converting the topological features into topological feature vectors, fusing the topological feature vectors with the data point feature vectors, constructing a deep neural network DNN, and generating a search result. The method comprises the following steps: receiving a user inquiry, carrying out inquiry analysis, and calculating the similarity with a data point feature vector; constructing a distance matrix, constructing a simple form, and calculating topological characteristics of the simple form through a boundary operator; the topological features are converted into topological feature vectors to be fused with the data point feature vectors, a deep neural network DNN is constructed, and a search result is generated; the discrimination capability of similarity difference is obviously improved, the efficiency of data processing and query response is enhanced, and the accuracy and correlation of search results are improved.

The invention relates to a single-transistor ternary content addressable memory based on a gate-induced leakage current effect and a preparation method of the single-transistor ternary content addressable memory. The memory comprises a substrate, a ferroelectric layer and a grid electrode which are arranged from bottom to top, a drain electrode doped region and a source electrode doped region are arranged in an active region of the substrate, and a drain electrode and a source electrode are respectively formed by depositing contact metal. The polarization state of the ferroelectric layer is adjusted by applying different pulse voltages to the grid electrode, and data storage and high-speed parallel search of ternary logic states (the state 0, the state 1 and the state X) are achieved. By utilizing the nonvolatile storage characteristic of the ferroelectric layer and the high-speed search characteristic of the GIDL effect, efficient ternary logic storage and data search functions are realized under extremely low area consumption, and the device has the advantages of high storage density, low power consumption, quick response and good process compatibility; the method can be widely applied to the fields of artificial intelligence, big data and efficient data processing.

The invention discloses a geographic space data search method, a geographic space data transaction method and a related device. The search method comprises the following steps: acquiring a search range; according to the search range and a pre-constructed hybrid tree index, searching a data set A intersecting with the search range from all data sets corresponding to the hybrid tree index; wherein the hybrid tree index is composed of a ball tree index and a KD tree index; and performing multi-dimensional similarity calculation on the search range and the data set A, and determining a search result according to a multi-dimensional similarity calculation result. According to the search method, the mixed tree index composed of the ball tree and the KD tree is adopted for first-stage search, the node access frequency during search is reduced through the complementary advantages of the two tree structures, and the search efficiency is remarkably improved when high-dimensional and large-scale data are processed; and multi-dimensional similarity search is further performed based on the search result of the first stage, so that complex search requirements are met.

The invention provides a data retrieval method, system and device, and relates to the technical field of big data processing, the method comprises the following steps: obtaining a search text of a user; performing data permission assembly according to the search text to obtain a user permission set of the user; according to the user permission set, generating a retrieval filtering condition of the search text; according to the retrieval filtering condition, performing multi-source data search in combination with the search text to obtain an initial retrieval result corresponding to the search text; and performing unauthorized rejection operation on the initial retrieval result to obtain a final retrieval result of the search text. According to the method, the range is defined through permission assembly, the condition focusing target is filtered, the efficiency is improved through pre-matching, and the precision is guaranteed through post-removing, so that the retrieval data volume is compressed to improve the efficiency, and the matching pertinence is enhanced to improve the precision.

The invention provides a geographic data search method and device, and the method comprises the steps: obtaining a geographic data search request of a user, and the geographic data search request comprises geographic knowledge keywords; and in response to the geographic data search request, recalling target geographic data. The target geographic data is searched based on the geographic knowledge keyword and a geographic knowledge database, and the target geographic data comprises geographic knowledge, a POI identifier related to the geographic knowledge and geographic data of the POI. And displaying the target geographic data on an electronic map interface. According to the geographic data search method provided by the invention, the application scene of the electronic map can be expanded, and the use requirement of a user on the map in the education field is met.

The invention discloses a multi-modal data search method and system based on an AI large model, and relates to the technical field of multi-modal data processing, and the method comprises the steps: inputting multi-modal data into a quantum state propagation engine, mapping the multi-modal data to a quantum entanglement state through a quantum neural radiation field model, and generating a quantum entanglement state coding feature tensor; dynamically planning a quantum state propagation path of the quantum entangled state coding feature tensor based on a nonlinear soliton equation, and constructing a quantum topological index network and a knowledge graph; compiling a user search instruction into a quantum measurement operator, executing quantum state propagation path navigation in the quantum topological index network, and generating a candidate result set of cross-modal matching through a path interference effect; performing quantum de-coherence driven probability reordering on the candidate result set, and screening high-confidence results; through the amplitude damping channel and the fluctuation ratio weight calculation, the problem of high response delay caused by the calculation efficiency bottleneck is solved.

The present invention provides a high-reliability unit test automatic generation method and apparatus based on a conversational large language model. First, projects are parsed and analyzed to extract context information, then the testing necessity of a method to be tested is determined, and different test direction lists are generated on the basis of the division of testing purposes. After initial test cases are generated and repaired, input data searching is performed on passed test cases to improve test input data. Subsequently, mutation testing is performed on all test cases, and test cases are regenerated for failed mutations to improve assertion quality. Finally, successful test cases are reduced and merged to avoid overlapping. The present invention is superior to existing methods in terms of coverage, test data integrity, assertion quality, and the like, and has stable performance across projects of different scales and fields. The generated test cases have significant advantages in readability, understandability, maintainability, test input data integrity, assertion quality, and volume.

The invention discloses a database configuration method, system and device and a storage medium, and the method comprises the steps: determining tables needing to be queried by a user and data items needing to be queried in each table according to input information of the user; wherein the data items comprise main data items and sub-data items; according to a selection operation of a user, determining an association mode between the main data item and the sub-data item in different tables; generating data structure index information of the data search library and data synchronization general configuration from the data management library to the data search library; wherein the field type of the main data item in the data structure index information is the field type of the corresponding table of the data management library, and the field type of the sub-data item is an array; and performing data synchronization on the data search library according to the data structure index information and the data synchronization general configuration. According to the method, data synchronization between the data management library and the data search library can be flexibly and efficiently realized, and the practicability of the database can be improved. The method can be widely applied to the technical field of databases.

The invention provides an object searching method and device, equipment and a storage medium, and relates to the technical field of data searching. The method includes obtaining a reference quantized representation for a reference object in a search input and a set of attribute values for the reference object. The method further includes selecting, from the plurality of quantized representations, a set of candidate quantized representations related to the reference quantized representation based on the reference quantized representation and a quantized representation index generated from the plurality of quantized representations of the plurality of objects. The method further includes filtering the set of candidate quantized representations based on the set of attribute values and a set of inverted index tables associated with a set of partitions of the set of candidate quantized representations of the plurality of partitions formed by the plurality of quantized representations. The method further includes returning a plurality of target objects similar to the reference object based on the filtered set of candidate quantized representations. According to the embodiment of the invention, high-performance and low-delay retrieval under the conditions of large data volume and complex filtering is ensured.

A method includes incorporating information from multi-modal embeddings in an indexed point-cloud data structure with three-dimensional (3D) spatial information for a captured scene. The method also includes performing at least one of querying or retrieving 3D-point-cloud data based on a user input including at least one of natural language or image references. The method also includes enabling global scene understanding and local scene understanding using instance segmentation in conjunction with the multi-modal embeddings.

The invention relates to the technical field of data processing, can be applied to the fields of financial information search, multi-dimensional information retrieval in intelligent investment advisers, medical information search and the like, and provides a multi-modal data search method and device, a storage medium and computer equipment. Performing multi-modal unified coding on different modal data in the knowledge base to obtain a multi-modal knowledge base; acquiring input information of a user; retrieving multi-modal information in a multi-modal knowledge base, wherein the similarity between the multi-modal information and the input information meets the requirement; the multi-modal information comprises feature vectors corresponding to the information of different modals, wherein the similarity of the information and the input information meets the requirement; and sorting the feature vectors corresponding to the information of different modes based on the historical behavior information of the user, and determining target search information corresponding to the input information based on a sorting result. According to the embodiment of the invention, a fusion retrieval mechanism of multi-modal data is introduced, so that the precision and correlation of information retrieval are effectively improved, and the user experience is improved.

The invention relates to the technical field of power services. The self-service intelligent business card printer comprises an interaction module, a storage module and a printing module, the interaction module is in communication connection with the storage module, and the interaction module and the storage module are respectively in communication connection with the printing module; the storage module is used for storing business card data of power service personnel; the interaction module is used for acquiring a user input instruction and searching target business card data in the storage module according to the user input instruction; and the printing module is used for receiving the printing instruction of the interaction module and printing the target business card data queried in the storage module. The latest business card data of the service personnel can be provided when the user needs, repeated printing is avoided, the cost is saved, printing is convenient and fast, the intelligent level is high, and the user experience degree is improved.

The invention discloses a large-scale vector approximate nearest neighbor search heterogeneous system based on a GPU-NVMe framework, which is characterized in that the system is based on a direct GPU-NVMe framework, and a hybrid index combining a clustering algorithm and a graph algorithm is designed. According to the hybrid index, vectors with good clustering are efficiently processed by utilizing the parallel processing capacity of the GPU, and meanwhile, the search accuracy of noise vectors is improved by taking a graph index as a compensation mechanism. According to the method, collaborative optimization of hardware and software is fully considered, vector index data deployment is implemented at an NVMe driving level, meanwhile, CPU and GPU hardware are cooperatively utilized to carry out a gigabit-level vector retrieval calculation process, and an extensible large-scale retrieval system on a direct GPU-NVMe architecture is constructed. Compared with the prior art, the method has the advantages that the performance bottleneck in the gigabit-level vector data search is effectively solved, the search throughput and accuracy are remarkably improved, and the search delay is reduced.

The invention belongs to the technical field of power system data processing, and relates to a data semantic understanding and intelligent cataloguing method based on power industry data, which comprises the following steps: acquiring real-time monitoring data, equipment operation data, historical operation and maintenance data and business system data of a power system; carrying out missing value processing, abnormal value elimination, repeated data deletion and normalization processing on the collected data, carrying out integration through a data fusion algorithm to form a unified data set, carrying out semantic analysis on industry text data by utilizing a natural language processing technology, extracting key entities and relationships, and carrying out semantic analysis on the key entities and relationships; mapping the data into a knowledge graph in combination with a power industry ontology model to generate structured and semantic industry knowledge data; finally, through the semantic analysis result and the knowledge graph, the data classification label is automatically generated, intelligent cataloguing and efficient management are achieved, the intelligent level of data management is improved, the data search efficiency and utilization value are remarkably improved, and the complexity of manual intervention is reduced.

Disclosed in embodiments of the present invention are a scenario-based multi-source data fusion analysis method and system and a related device. The method comprises: acquiring multi-source data; preprocessing the multi-source data to obtain preprocessed data; performing feature fusion on the preprocessed data and then performing normalization fusion processing to form a multi-source data feature set; and performing data type division on feature data in the multi-source data feature set, and storing the feature data in the multi-source data feature set on the basis of the data types. By means of the method, multi-source data is classified and divided, contributing to data search, improving the efficiency of data utilization.

The invention relates to a data search method and device, computer equipment and a computer readable storage medium. The method comprises the steps of obtaining multi-modal service data corresponding to a data search request in response to the data search request; extracting single-mode service data characteristics of the single-mode service data; fusing the plurality of single-mode business data features and the plurality of attention weights into a multi-mode attention weight feature; fusing the multi-modal attention weight feature with each single-modal service data feature to obtain a target single-modal service data feature corresponding to each single-modal service data feature; for each data mode, searching similar service data corresponding to the single-mode service data in the data mode according to the target single-mode service data features, and detecting the similarity between the similar service data and the single-mode service data; and screening out the target similar business data with the highest similarity, and outputting the target similar business data. By adopting the method, data search can be accurately carried out.

The invention discloses a repeated data deletion method and system based on ZNS SSD, and belongs to the field of repeated data deletion.The method comprises the steps that a fingerprint index table and a fingerprint updating cache are maintained, three-time opportunity repeated data deletion is achieved, and repeated data search is conducted in the fingerprint index table, the fingerprint updating cache and an address mapping table respectively; an address mapping table, an address reverse mapping table and a reference counting table are maintained, physical space garbage collection / defragmentation and write request merging are achieved, the address mapping table, the address reverse mapping table and the reference counting table conduct garbage collection with partition as granularity when free space is insufficient, and a fingerprint index table is not updated after garbage collection data migration; and instead, the mapping of fingerprints to migration-in physical pages is stored in a fingerprint updating cache, the physical pages are sequentially distributed in partitions by the fingerprint updating cache, normal data write requests and garbage collection data migration write requests are respectively cached, and the write requests which are continuous in sequence are merged and then issued. According to the method, the high-performance and low-cost efficient storage system can be constructed on the basis of the ZNS SSD at relatively low overhead.

The invention relates to the crossing field of artificial intelligence technology and e-government, and discloses an e-government enterprise service intelligent response method based on AI cue word engineering, comprising: constructing and maintaining a government knowledge graph and a scenarized cue word template library; receiving and analyzing a service request input by an enterprise, and extracting an enterprise feature tag and a business intention; selecting a target cue word template based on the matching degree of the enterprise feature tag and the scene tag of the template in the scene cue word template library, and generating an adapted cue word template; retrieving associated knowledge data from the government affair knowledge graph according to the service request, and filling the adapted cue word template with the retrieved associated knowledge data to generate a structured cue word; inputting the structured cue word into an AI model to drive the AI model to generate a government affair service response; and collecting multi-dimensional evaluation feedback of government affair service response, and carrying out iterative optimization. The demand understanding precision is improved, and the risk of core information misjudgment is reduced.

The invention provides a distributed data search method and electronic equipment, and relates to the technical field of terminals. According to the method, a user can search data on other multiple devices on one device at a time, the search operation is simplified, and the man-machine interaction experience is improved. The method comprises the steps that a first device displays a first interface, and the first interface comprises a search box, a device name of a second device and a device name of a third device; in response to a search operation on a keyword input in the search box, displaying a second interface; wherein the second interface comprises a search result of the first equipment, a search result of the second equipment and a search result of the third equipment.

The invention discloses a metadata management method and device, electronic equipment and a storage medium, and relates to the technical field of data storage, and the method comprises the steps: receiving a metadata operation request sent by a client, determining a target logic partition based on a mapping relation between an identifier and the logic partition, and determining a target physical sub-book group through a mapping relationship between the logic partition and the physical sub-book group, and selecting a target storage node to process the metadata operation request based on the storage node state information in the target physical sub-book group. According to the method, the most suitable storage node can be intelligently determined to execute the metadata operation by introducing a mapping mechanism between the identifier and the logic partition as well as between the logic partition and the physical sub-book group and combining the state information of the storage node; the problems that in traditional metadata management, a single server becomes a performance bottleneck and data searching and maintaining efficiency is low are solved, and the technical effects of improving system performance, improving data processing efficiency and enhancing system reliability are achieved.