458 results about "Data search" patented technology

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 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 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.

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 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 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 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.

The invention discloses a hybrid encryption method supporting access control and controllable data search, and relates to the field of secure data sharing. According to the method, a CP-ABE (Ciphertext Policy Attribute Based Encryption) technology and a symmetric searchable Encryption (SSE) technology are creatively combined, and a data authorization access function and a data controllable search function are integrated. As for data authorization access, CP-ABE is dominated, fine-grained access control is achieved by embedding attribute information, and it is ensured that only authorized users conforming to a preset strategy can decrypt data. For data controllable search, SSE is dominated, a data storage service provider is allowed to execute a search task based on keywords on the premise of not decrypting data, and expansion of fuzzy keyword search is supported in combination with a trusted execution environment technology. According to the method, the problems that user access is not limited and data sharing is easy to leak to an untrusted party are effectively solved. Through strict user right control, unauthorized access is prevented. And meanwhile, the targeted search of the shared data is realized, and bidirectional requirements are met.

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.

The invention discloses a data search processing method and a host. A host processor obtains a query vector and a centroid of each to-be-searched graph; the to-be-searched graph is constructed for the query scene, so that the number of candidate vectors of the corresponding to-be-searched graph is determined according to the query vector and the centroid; a query request is sent to the hardware accelerator, the query request comprises query vectors and the number of candidate vectors, the hardware accelerator distributes the query request to different search units, and candidate vector search is conducted on the corresponding graphs to be searched in the external storage through the different search units.

The invention provides a method for searching structured data based on natural language driven by a large model, which comprises the following steps of: preprocessing interface parameters through a data interface of an openAPI (Application Program Interface) to generate an interface file, and adding the preprocessed interface parameters into an agent tool chain; the large model extracts keyword parameters from a question input by a user through a natural language and performs semantic analysis on the extracted keyword parameters, so that the keyword parameters are converted into interface fields or table fields in an interface file; the large model adapts an analyzed result to a tool name in the agent tool chain; calling an adaptive interface name by the large model, and calling a corresponding tool to query a data result; the large model outputs the result according to the form of the user demand, standardization processing is performed on the interface of the traditional data, the agent tool is added, the large model is used, different data search requirements are met, and the personalized data query requirement is met.

A content-addressable memory includes a pre-search content-addressable memory array, a control circuit, and a main search content-addressable memory array. The pre-search content-addressable memory array is configured to perform a first data search to selectively adjust levels of a plurality of match lines in the pre-search content-addressable memory array. The control circuit is configured to generate a detection signal according to the levels of the plurality of match lines after the first data search is performed, and to generate an enable signal according to the detection signal. The main search content-addressable memory array is configured to selectively perform a second data search according to the enable signal.

The invention discloses a multi-path data search fuzzy recommendation method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, analyzing fuzzy semantics input by a user through a pre-trained BioBERT model, and generating a structured query logic containing an entity type and a relation path; s02, constructing a dynamic multi-dimensional relation graph based on the obtained structured query logic, synchronously querying a relational database and a non-relational graph database, and returning a candidate set; s03, aggregating encryption parameters by adopting a federated learning framework to generate a global model; s04, generating a recommendation list based on the real-time physiological indexes of the patient and the diagnosis stage; and S05, capturing the latest literature through a medical knowledge updating engine, and updating graph nodes. According to the method, the problems that a traditional method depends on manual maintenance and lacks dynamic and context understanding are solved, and adaptive support for complex medical scenes is realized by combining relational and non-relational databases, a federal learning framework and a semantic analysis technology.

Systems and methods for performing user data search can include obtaining a search query, processing the search query with one or more machine-learned planning model to generate one or more specialized queries and instructions to search one or more specific user datasets with the one or more specialized queries, and processing the obtained search results with a generative response model to generate a response to the search query. The systems and methods can search across local databases and server databases. An on-device generative response model can be utilized for device local search results, while a server generative response model may be utilized for server-based search results.

The present disclosure provides a memory device and a data search method thereof. The data search method of the memory device includes vectorizing a data to be searched to obtain a data to be searched vector according to a compression mode recorded, wherein the data to be searched and a plurality of objects of a database are compressed by the compression mode; setting a search condition; searching the objects of the database with the data to be searched vector to determine whether the data to be searched matches the objects in the database; and recording and outputting at least one matched object in the database that matches the data to be searched.

The invention relates to a block backup indexing method, system and device based on a B + tree and a storage medium, and belongs to the technical field of disaster recovery backup. The method comprises the steps of intercepting a QEMU block write-in request and extracting an IO descriptor, writing block data into a disk and obtaining a physical offset, initializing a two-dimensional B + tree index structure, inserting the block IO descriptor and offset information into a two-dimensional B + tree, querying the position of the block data according to a logic offset and / or timestamp range, and deleting and updating index nodes according to a specified range. The system comprises a block data interception module, a block data writing module, a B + tree initialization module, a block data insertion module, a block data search module and a block data deletion module. According to the method, through a two-dimensional hierarchical index structure of the logic offset and the timestamp, joint efficient positioning of time and space dimensions is achieved, sharing of timestamp leaf nodes between local and global B + trees is supported, data redundancy is effectively avoided, and range query efficiency is improved.

The invention discloses a three-dimensional geologic body spatial interpolation system and method, and belongs to the field of three-dimensional geologic body spatial interpolation, and the system comprises a data collection and judgment module, an interpolation calculation module, a modeling analysis module, a drilling geological point recommendation module, a geological data search and supplement module, and a result output module. The data acquisition and judgment module is used for acquiring drilling geological data, geological profile data, topographic data and geological interface data, setting a matching rule and matching an optimal interpolation algorithm combination; according to the method, accurate matching of geological data and an optimal algorithm, effective processing of abnormal data, rapid positioning of an abnormal area and continuous supplement of key geological information are realized, the accuracy and reliability of three-dimensional geologic body spatial interpolation are remarkably improved, and a powerful technical support is provided for geological exploration and research work.

The invention provides a three-dimensional geological modeling method and device based on attribute variable joint simulation, and relates to the technical field of computers, and the method comprises the steps: obtaining lithology data and grade data of a mining area; classifying the lithologic data, converting lithologic variables in the lithologic data into indication variables by utilizing an indication criterion, performing Gaussian variation on the grade data, and converting the grade data into normal distribution data with a mean value of 0 and a variance of 1; determining the boundary type of the lithologic boundary by using the lagging scatter diagram, and carrying out joint modeling based on the spatial correlation of the boundary grade under the condition that the boundary type is a soft boundary to obtain an initial model; and determining the number of Gaussian random fields, a truncation rule, a truncation threshold, a suite structure and a common region matrix by using the indication variable and the normal distribution data so as to adjust the parameters of the initial model to obtain a target three-dimensional geologic model. According to the method, the data processing flow is simplified, the data search and simulation efficiency is improved, and the adaptability and accuracy of the model are enhanced.

In embodiments of field value search drill down, a search system exposes a search interface that displays one or more events returned as a search result set. A field-value pair can be emphasized in the field-value pairs of an event displayed in the search interface, and a menu is displayed with search options that are selectable to operate on the emphasized field-value pair of the event. The menu includes the search options to add search criteria of the emphasized field-value pair to a search command in a search bar of the search interface, exclude the search criteria of the emphasized field-value pair from a search, or create a new data search based on the emphasized field-value pair. A selection of one of the search options in the menu can be received, and the search command in the search bar is updated based on the search option that is selected.