363 results about "Recordset" patented technology

The invention provides a data flow monitoring method and system based on a large model, and the method comprises the steps: obtaining a data flow record set generated by a to-be-monitored system in a continuous operation period, carrying out the correlation path construction of the data flow record set, generating a data flow topological graph containing a node interaction relation and a time sequence dependency relation, and carrying out the correlation path construction of the data flow record set; calling a pre-trained circulation behavior analysis large model to perform node sequence pattern recognition on the data circulation topological graph, and generating behavior abnormal confidence and abnormal pattern labels of each node in the data circulation topological graph; and according to the abnormal behavior confidence and the abnormal mode label, screening an abnormal interaction node cluster in the data flow topological graph. According to the method, relevance between abnormal nodes and time sequence relevance are considered, missing detection or false detection is avoided, and the reliability of the monitoring effect is improved.

The invention provides a financial analysis method and system based on big data, and the method comprises the steps: analyzing the dependency relationship between a non-standard code combination and a fuzzy text mode in a material purchasing scene based on a credible rule library, extracting a new attribute combination feature, and forming an optimization rule feature set if the new attribute combination feature can improve the matching accuracy; performing rule-based key field and attribute set verification matching on the real-time non-standard transaction data according to the optimization rule feature set in combination with a dependency relationship between a non-standard code combination and a fuzzy text mode, and outputting a matched transaction record set; and comparing the difference between the matched transaction record set and the historical manual matching record, extracting and judging whether the newly added non-standard attribute combination is applicable to the non-standard transaction data which is not covered or not after a matching rule is adjusted by adopting an incremental learning algorithm, and if so, forming a dynamic matching table.

Distributed media content history and preferences can be stored and maintained by media playback systems including one or more blockchain-capable playback devices. Content record sets, such as content experience record sets and content network record sets, can be stored via distributed ledgers and updated at least in part based on media consumption events performed or detected by playback devices, service providers, or other participants. Such distributed data can also be accessed to facilitate playback of media content for particular users, devices, households, or environments.

The invention provides a document collaboration method and system based on cloud office, and the method comprises the steps: firstly obtaining a target document operation record set of a cloud office platform, including user terminal operation event sequences (operation types and timestamps), and then recognizing document collaboration mode features according to the operation event sequences, operation overlapping time periods, type relevance and frequency distribution are covered, then a pre-training model is used for analysis to obtain a cooperation demand prediction result containing a cooperation object set and a cooperation strength index, dynamic permission configuration is conducted on cooperation objects according to the cooperation strength index, and a permission hierarchical structure is generated. And finally, in response to a cooperation request of the target user terminal, controlling the data synchronization process of the document based on the permission range. According to the method, the efficiency, the safety and the intelligent degree of cloud office document collaboration are effectively improved.

The invention discloses an electric power big data privacy protection method and system based on federated learning, and belongs to the technical field of data processing, and the method comprises the steps: obtaining a historical session record set of an electric power user, carrying out the standardization preprocessing of the historical session record set, and obtaining a standardized session data set, extracting a time sequence feature set from the standardized session data set, calling a pre-configured federal learning framework to carry out privacy protection processing on the time sequence feature set, generating a privacy enhancement feature set, generating a power data privacy protection result based on the privacy enhancement feature set, and sending the power data privacy protection result to the server. And feeding back the power data privacy protection result to the power service system. According to the method, the privacy security in the data use process is guaranteed, the utilization value of the power big data in the unstructured session scene is improved, and the problem of adaptability of a traditional power privacy protection technology in unstructured session data processing is effectively solved.

Distributed media content history and preferences can be stored and maintained by media playback systems including one or more blockchain-capable playback devices. Content record sets, such as content experience record sets and content network record sets, can be stored via distributed ledgers and updated at least in part based on media consumption events performed or detected by playback devices, service providers, or other participants. Such distributed data can also be accessed to facilitate playback of media content for particular users, devices, households, or environments.

The invention belongs to the technical field of intelligent document processing, and discloses an intelligent data processing method for collected files based on artificial intelligence, which comprises the following steps: acquiring a multi-source multi-version file to carry out layout rectification and OCR (Optical Character Recognition) to obtain a page fragment object set; using a controlled decoding language model to extract clause records according to preset Schema to form a clause record set; performing cross-version alignment on homonymous or synonymous terms, and constructing a time sequence knowledge graph; compiling the cross-document consistency rule into an executable rule set which can be evaluated on the time sequence knowledge graph by adopting an executable collection constraint language; evaluating the scope of action of each rule to generate conflict candidates; and calculating a minimum hit set to obtain a minimum conflict interpretation set, positioning a root cause term instance, and generating a minimum repair suggestion according to a normalization result of the operator and the node violating the rule. According to the method, the unification of clauses and calibers and the automatic judgment of the latest effective state, the accurate positioning of conflicts and the minimum cost repair are realized.

Systems and methods disclosed herein automatically register, monitor, and authenticate distributed artificial intelligence (AI) agents and their operational contexts using a distributed or federated ledger-based agent knowledge registry. The system obtains a registration or query request (e.g., from an AI agent, orchestrator, or user interface) to identify or store operational context linked to each AI-based agent. The system determines a feature set of agent metadata and operational parameters using a first AI model set, and dynamically generates a cryptographically verifiable registry record set using a second AI model set (same as or different from the first AI model set) based on the operational feature set, to be stored in a distributed ledger database. The system automatically executes registry updating, agent selection, or operational verification workflows using a third AI model set (same as or different from the first and / or second AI model sets) to maintain records that trace inter-agent interactions.

The subject technology implements a unified query frame that may retrieve identity records from multiple, asymmetric identity spaces. The unified queries of the unified query framework may include one or more steps, one or more paths, and a resolution scheme that may extract sets of identity records from multiple identity spaces. The unified query framework may be implemented in a graph analysis system that generates one or more identity subgraphs using the extracted sets of identity records. One or more aspects of the unified queries and or identity subgraphs may be configured to customize the data retrieval process for one or more applications. One or more search operations of the graph analysis system may be optimized to improve the speed and efficiency of data retrieval and reduce compute resources and cost.

The invention discloses a quality monitoring abnormity positioning method and system for multi-source heterogeneous media data, and particularly relates to the technical field of quality monitoring of the multi-source heterogeneous media data.The method comprises the steps that through access and time base normalization, sources such as RTSP, HLS / DASH, offline files and message buses are mapped to a unified time reference, and out-of-order rearrangement and late cutting are carried out; basic quality elements are extracted from A / V / S in a sliding window, a dynamic threshold value is formed by adopting a trimming mean value and a median absolute deviation, and a window-level quality event is generated; using event anchor points as common reference to estimate cross-modal time delay and fuse evidences, outputting scene / mode labels by means of a lightweight online classifier, entering a confidence reduction mode when the evidences are missing, and outputting an availability bitmap and a reason code; and then event confirmation, time-space range refinement and hierarchical root cause posterior determination are completed, influence measurement and priority are calculated, and finally an anomaly positioning and root cause analysis record set including an event timeline, severity / influence degree, root causes and disposal suggestions is formed.

The invention provides a product scheme PPT automatic generation method, system and device and a medium, and belongs to the technical field of artificial intelligence. The method comprises the steps that product demand information is collected, an NLP tool is called for entity recognition and relation extraction, and a demand feature vector is generated; based on a MySQL database, retrieval is performed according to the demand feature vector, a structured record set is returned, and an associated document ID is obtained; based on a Milvus vector database, retrieval is carried out according to the demand feature vectors, and an unstructured document fragment set is returned; filtering the unstructured document fragment set according to the document ID, retrieving the unstructured document fragment set by adopting a mixed strategy of a BM25 algorithm and semantic retrieval, comprehensively sequencing retrieval results through a weighted scoring mechanism, and generating a final content fragment set; and calling a PPT template according to user requirements, and filling the final content fragment set into the PPT template to generate a PPT draft file.

The embodiment of the invention discloses a large model training method for query conversion, a database query method, computer equipment and a computer readable storage medium. The training method comprises the steps of obtaining an original large model and a training record set; and processing all the training records to obtain the first prompt statement, the second prompt statement, the first output and the target SQL query so as to train the original large model, and deploying the trained original large model as a natural language conversion module in the database management system. According to the database query method, a historical query cache module and a natural language conversion module are newly added in a database management system. The historical query cache module is used for executing text vectorization, vector indexing and nearest neighbor retrieval according to an input query; the natural language conversion module is used for collecting related forms and fields according to input queries and converting the input queries into SQL (structured query language) queries. According to the method and the device, the natural language query can be more accurately converted into the SQL query by using fewer computing resources.

One or more trained embedding generation artificial intelligence models are executed to generate a plurality of record attribute embeddings. The plurality of record attribute embeddings represents a plurality of attributes of data of a plurality of records. Grouping of the plurality of record attribute embeddings is performed. The grouping of a record attribute embedding includes grouping attribute values of the record attribute embedding into one or more groups of attribute values. The performing grouping provides a plurality of groups of attribute values for the plurality of record attribute embeddings. Selected records are compared to provide a set of matched records. The comparing, based on a group of attribute values, includes comparing records that include one or more attribute values grouped in the group of attribute values providing a subset of matched records of the set of matched records. The set of matched records is stored in an accessible computer location.

This disclosure describes example techniques for automatically configuring domain name system (DNS) servers to handle custom hostnames assigned to hosted zones. The techniques monitor DNS record sets of the hosted zones for special DNS records registering new hostnames. When such a special DNS record is detected, the central DNS server checks a database to see if that hostname is already assigned to another hosted zone. If the hostname is not assigned to another hosted zone, the central DNS server automatically updates its own DNS configuration data pair the new hostname with the Internet Protocol (IP) address of the hosted zone requesting the hostname. This allows the central DNS server to resolve future DNS queries for the new hostname by routing requests to the proper zone.

The embodiment of the invention provides a data query method and device based on multi-agent iteration, and relates to the technical field of data query. The method comprises the steps that through iterative analysis of a decomposition agent and an optimization agent, a user question text is decomposed, and a plurality of corresponding sub-target query statements are generated; retrieving in a query database based on the plurality of sub-target query statements to generate a first talent information record set; vectorizing the user question text to obtain a question text feature vector, and obtaining a second talent information record from a vector query library based on the question text feature vector to generate a second talent information record set; talent information records in the first talent information record set and the second talent information record set are matched and fused, a target comprehensive talent information record set is obtained, and a query result corresponding to the user question text is obtained. The talent recommendation method and device are used for improving talent recommendation efficiency and accuracy, and meanwhile computing resource consumption is reduced.

The invention provides a multi-dimensional knowledge extraction construction method and system applied to operation and maintenance technology services, and relates to the field of operation and maintenance technology services, and the method comprises the steps: firstly obtaining an operation and maintenance service full record generated in an operation and maintenance technology service process, and then carrying out the association network construction processing of the operation and maintenance service full record, and obtaining a target association network structure. And based on the structure, identifying the core record cluster, extracting complementary operation and maintenance information, and fusing to form an operation and maintenance knowledge module set. And then performing dynamic knowledge system construction processing on the operation and maintenance knowledge module set to form a target operation and maintenance knowledge system with a self-adjustment capability. And finally, based on the target operation and maintenance knowledge system, aiming at the newly received operation and maintenance service request, generating operation and maintenance service response content containing the resource optimization suggestion, thereby effectively improving the operation and maintenance service quality and efficiency.

A high availability controller for combining and unifying aspects of a process controller and an electrical controller. A unified namespace combines a process domain namespace and a power domain namespace in a common database of the controller without altering either. The unified namespace maps source device names of the power domain and unique process control names of the process domain. A common record set of sequence of events (SOEs) for the process domain and the power domain is generated and SOEs arising from the power domain are incorporated into the common record set. The controller performs process control and monitoring along with electrical control signaling and monitoring within a single control strategy directly from the controller.

A method comprises receiving a set of raw worker data records associated with one or more worker activities of a worker, each raw worker data record comprising one or more of an image, a video, information from a sensor, information from interaction with a tool, and information from interaction with a device. A first analysis, configured to analyze the set of raw worker data records for one or more indications regarding whether any worker activities include one or more undesired behaviors, is performed on the set of raw worker data records. Based on the first analysis, a second analysis, configured to categorize and document worker behavior as a function of time, is performed. Based on the second analysis, a third analysis, configured to analyze worker behavior for undesired conditions, is performed. Based on at least one of the second and third analysis, a summary of worker activity is generated.

The embodiment of the invention relates to a processing method and device for updating model knowledge by optimizing MLP weight. The method comprises the following steps: creating corresponding first and second data records for knowledge entries of an update knowledge set specified by a user; extracting pre-training knowledge corpora irrelevant to the updated knowledge set from a pre-training knowledge corpus of a target model specified by a user to form a third data record set; weight parameter optimization is carried out on all MLP layers of the target model based on all the first data records; performing anti-fact problem evaluation on the updated target model based on all the second data records; performing irrelevant knowledge problem evaluation on the updated target model based on the third data record set; and identifying whether the first evaluation result and the second evaluation result are both passed, if not, continuing to optimize until the latest first evaluation result and the latest second evaluation result are both passed, and if yes, feeding back updating completion to the current user. The updating efficiency can be improved, and the updating cost can be reduced.

The present disclosure provides techniques for fast record matching using machine learning. One example method includes receiving a request indicating one or more attributes, identifying, from a plurality of records using a first machine learning model, a set of records, wherein each record of the set of records indicates the one or more attributes, computing, for each record of the set of records using a second machine learning model, a first relevance score for the record, computing, for each record of the set of records using a third machine learning model, a second relevance score for the record, and identifying, based on the first relevance score for each record of the set of records and the second relevance score for each record of the set of records, a given record of the set of records best matching the request.

The invention belongs to the field of artificial intelligence and financial science and technology, and relates to a dynamic form generation method, which comprises the following steps: preprocessing unstructured text data requested by a client form to obtain preprocessed text data; inputting the preprocessed text data into an intention recognition model to obtain an intention category; form keywords are selected according to the weights, and the incidence relation of the form keywords is obtained; retrieving a candidate record set from historical query records according to the form keyword; calculating probability distribution of the candidate record set by adopting a maximum entropy model to obtain a prediction probability; according to the prediction probability, determining a candidate record most related to the client form request as a form generation reference knowledge base; and generating a personalized form based on the form generation reference knowledge base. The invention further provides a dynamic form generation device, computer equipment and a storage medium. In addition, the invention further relates to a block chain technology, and historical query records can be stored in a block chain. According to the invention, personalized services can be provided, the business process is simplified, and the error rate is reduced.

The invention discloses a query statement reconstruction method and device based on artificial intelligence, equipment and a medium, and relates to the technical field of natural language processing, and the method comprises the following steps: obtaining a current query statement input by a user and a historical interaction record; calculating a semantic association degree between the current query statement and each historical interaction record; performing descending sort according to the semantic association degree corresponding to each historical interaction record to obtain a historical interaction record sequence; historical interaction records are sequentially selected from the starting end of the historical interaction record sequence to serve as target historical interaction records, and when a preset selection stopping condition is met, a target historical interaction record set is constructed based on all the selected target historical interaction records; and inputting the current query statement and the target historical interaction record set into the query statement reconstruction large model, so that the query statement reconstruction large model outputs a reconstructed query statement corresponding to the current query statement. According to the scheme, the real intention of the user can be accurately restored, and the accuracy of querying the hit content is improved.

Computer implemented systems and methods are disclosed for automatically clustering and canonically identifying related data in various data structures. Data structures may include a plurality of records, wherein each record is associated with a respective entity. In accordance with some embodiments, the systems and methods further comprise identifying clusters of records associated with a respective entity by grouping the records into pairs, analyzing the respective pairs to determine a probability that both members of the pair relate to a common entity, and identifying a cluster of overlapping pairs to generate a collection of records relating to a common entity. Clusters may further be analyzed to determine canonical names or other properties for the respective entities by analyzing record fields and identifying similarities.

The invention provides a data synchronization method and device, equipment and a storage medium, and relates to the technical field of data storage. The method comprises the steps that N incremental operation record sets arranged according to the time sequence are obtained from an incremental log of a source database, N is an integer larger than 1, and the Nth incremental operation record set is a current to-be-synchronized incremental operation record set. The method further comprises the step of determining a target incremental operation record set based on the check code of the incremental operation record set before the Nth incremental operation record set, and the target incremental operation record set is the incremental operation record set which is successfully synchronized to the target database last time. And synchronizing the incremental operation record set after the target incremental operation record set in the N incremental operation record sets to the target database. According to the embodiment of the invention, when the incremental operation record set is synchronized, the synchronization abnormity can be quickly found and automatically repaired, so that accurate synchronization between the databases is realized, and the user experience is improved.

An enhanced pipeline for the generation, validation, and deployment of machine-based predictive models (PMs) is provided. The pipeline analyzes records to generate a graph that indicates various relationships between the records. A user provides a selection of a data element of interest (DEOI). The generated PM predicts values for the DEOI based on input records that do not include values for the DEOI. The user provides selections for values of the DEOI that represent positive outcomes associated with the DEOI. The user provides selections for values of the DEOI that represent negative outcomes associated with the DEOI. A subgraph of the graph is determined based on the DEOI. A relevant set of records is determined based on the subgraph. The PM is automatically trained, validated, and deployed based on the relevant set of records, the DEOI, and the representative values for the DEOI.

Random cut trees are generated with respective to respective samples of a baseline set of data records of a data set for which outlier detection is to be performed. To construct a particular random cut tree, an iterative splitting technique is used, in which the attribute along which a given set of data records is split is selected based on its value range. With respect to a newly-received data record of the stream, an outlier score is determined based at least partly on a potential insertion location of a node representing the data record in a particular random cut tree, without necessarily modifying the random cut tree.

Systems and methods for generating units of work in a collaboration environment are disclosed. Exemplary implementations may: manage environment state information including work units records describing units of work assigned to individual users within the collaboration environment, individual sets of work unit records being defined by a record hierarchy, individual units of work including one or more digital content items; obtain user input information conveying user input on, or relating to, individual digital content items of the individual units of work; generate one or more work unit records based on the user input information, such that responsive to the user input information conveying first user input by a first user on, or relating to, a first digital content item, generate a second work unit record describing a second unit of work, the second work unit record being subordinate to a first work unit record; and / or perform other operations.

The invention relates to the field of data processing, and discloses a customer feedback multi-source data cleaning and KPI pre-calculation system. Comprising a display terminal and a platform server. The platform server generates an import batch number for client feedback data from at least two types of data sources, completes mapping from a source field to a uniform field, and performs format normalization, deletion processing, logic consistency verification and duplicate removal and disambiguation on a uniform record set to obtain a cleaned record set; determining hierarchy affiliation based on the dealer hierarchy relationship; pre-calculation is carried out according to KPI aperture configuration, a pre-calculation result is stored according to time partitions and dimension keys, and meanwhile, an import batch number and an index version identifier are bound to generate an aperture identifier; and responding to the query request and returning a matched KPI result to the display terminal for display.

The invention provides a green construction building digital management system and method, and relates to the technical field of digital management. The system performs format unification and numerical value standardization processing on the original records to generate a preliminary record set associated with the process information; uniquely affiliating the record to a corresponding process according to the process time interval and the resource list to form a process record sequence; establishing cross-process one-way time association, and forming a deterministic mapping relation between previous and next process records; a three-section increment generation method is adopted to calculate a process resource usage amount, a weight group is generated by extracting a source attribute, a time continuous attribute and a preorder process inheritance attribute, weighted operation is carried out by combining a recorded numerical value, a time difference and a numerical value difference to obtain increment contribution, and finally accumulation is carried out to obtain a total process usage amount. And irreversible forward transmission of the resource usage amount along the process sequence is supported. According to the system, accurate calculation and dynamic management of resource loads in the construction process are realized.

The invention provides a financial data security management method based on a distributed account book, and the method comprises the steps: storing data to a distributed node database if a verification result shows that the data is not tampered, and generating a consistent data copy through a multi-node consensus mechanism; for the data copy, regularly extracting key field data and comparing the key field data with the initial data record set to obtain a consistency comparison result; if the consistency comparison result shows that inconsistency exists, marking and classifying inconsistent data, generating a risk assessment value, and determining a high-risk data point; performing deep analysis according to the high-risk data points, tracing a data modification history, and obtaining a timeline and responsibility attribution information of a tampering behavior; and according to the timeline and the responsibility affiliation information, generating a structured report and a risk early warning signal, and determining a subsequent processing direction.