319 results about "Event type" patented technology

Devices and techniques are generally described for key-value store having improved support for indexing and querying. The proposed system can expand query functionality by adding compound indexing. In some implementations, compound index may allow multiple simple key-value store queries (e.g., for multiple event types) to be replaced with a single query. In some implementations, compound index may allow for query filtering otherwise unavailable for the key-value store. The system may return results from the compound query in timestamp order and with appropriate pagination. Indexing may be updated dynamically; for example, manually via a self-service portal and / or automatically in response to frequent query combinations. The expanded query functionality can improve the efficiency and usability of, for example, an event timeline system.

Techniques are presented to provide an event review dashboard. One method relates to a user interface (UI) for the event review dashboard that provides customers with a comprehensive view of their event engagement over time. The UI includes interactive elements, information fields, and filters to assist in the analysis and review of customer actions in response to behavioral events detected in vehicles. These actions may include coaching or dismissal. The UI provides filters for date range selection, customer selection, dismissal rate visualization, and minimum event thresholds, enabling customers to assess the relevance and effectiveness of specific event types and their coaching program performance. Additionally, the UI also includes a table and panel for detailed analysis of event dismissal by type and direct access to dismissed event details. The UI is designed for ease of use and efficient analysis, with feedback mechanisms to improve the AI model learning process.

The invention discloses a multi-sensor data fusion method and system for an industrial park unmanned inspection machine. The method comprises the following steps: determining a current event type and a scene environment where the current event type is located based on various monitoring data; judging an influence area of the current event according to the monitoring data, the scene environment and the event type; obtaining and storing an association relationship between each position coordinate in the current event influence area and each monitoring data weight configuration, and an association relationship between the scene environment where the current event is located and each monitoring data weight configuration; acquiring sampling position coordinates of the current monitoring data, and preprocessing the monitoring data based on the fusion equation to obtain at least one fusion value; according to the method, the event type and the scene environment are judged through the data features of the monitoring data, then the event influence area corresponding to the event is obtained, and different weights are given to the monitoring data of various types according to the event, so that the data obtained after fusion is more accurate, and the accuracy of later early warning is improved.

The invention relates to a progressive memory delay monitoring and diagnosis method oriented to a virtual memory subsystem. The method comprises the following steps: mounting a BPF program to a plurality of key event points on a kernel; when the key event point is triggered, acquiring state information of a corresponding event; packaging the state information into an event, and writing the event into a perf ring buffer associated with the outputmap; and the user mode program asynchronously reads the packaged event from the perf ring buffer, performs classification and aggregation according to the process and the event type, generates a delay terminal log and a histogram, and outputs a diagnosis result. Through systematic architecture design, the state keeping capability and the kernel context access capability of the eBPF are combined with an event model of a virtual memory subsystem, and a set of closed-loop monitoring system oriented to a diagnosis target is constructed. High-precision and high-reliability memory operation delay measurement is realized.

The invention discloses a data processing method and system for a dynamic knowledge graph, particularly relates to the technical field of knowledge graph data processing, and is used for solving the problem of park multi-source data consistency. The method is oriented to a park, system records are standardized as park event frames carrying object identifiers, event types and time information, association is achieved through a unified object identifier set, sub-graph templates are inquired according to the event types, object nodes are positioned, the sub-graphs are expanded according to template paths, affected sub-graphs are limited, and incremental updating is executed only within the range. The method comprises the steps of recording and writing effective time, failure time and a source event identifier, constructing a time version chain, generating a current state in combination with conflict detection of a preset time window and a source priority decision, constructing a current view and a historical view, adding a time filtering condition to query, and realizing time sequence retrieval of scenes such as equipment operation and lease change. And the updating efficiency and the data consistency of the park knowledge graph are improved.

Aspects of the subject technology include receiving a request to generate an event-based workflow associated with a first event type, which includes a state machine that includes at least a state and an associated transition and receiving an event including a second event type and an event attribute. Aspects also include determining whether the event attribute satisfies the triggering condition of the transition associated with the state, in response to determining that the second event type corresponds to the first event type, and when a current state of the event-based workflow corresponds to the state. Aspects also include performing the transition action of the transition and updating the current state based at least in part on the performed transition action, in response to determining that the event attribute satisfies the triggering condition of the transition associated with the state.

The invention belongs to the technical field of information, and particularly relates to an event co-reference resolution method based on multiple agents. The method specifically comprises the following steps: splicing prompt words of an event attribute recognition agent with a chapter text to be subjected to event co-reference analysis, and then inputting the event attribute recognition agent; the event attribute recognition agent follows the input content output event type and role or the output is null; when the output of the event attribute recognition agent is null, performing question query on the exogenous information integration agent; after a return result of the exogenous information integration agent is added, the event attribute identification agent generates a corresponding event type and role again; splicing the event type, the role and the chapter text, and inputting an event co-reference prediction agent; and the event co-reference prediction agent realizes event co-reference resolution for each event mention according to the sequence.

Automated detection of events in content can be performed using regions of information associated with various user interface or display elements. Certain elements can be indicative of a type of event, and regions associated with these elements can be analyzed on a per-frame basis. If one of these primary regions shows a state or transition that is indicative of one of these events, one or more secondary regions can be analyzed as well to attempt to verify whether that event occurred, as well as whether that event qualifies for selection for additional use. Selected events can be used for purposes such as to generate highlight montages, training videos, or user profiles. These events may be positioned at different layers of an event hierarchy, where child regions are only analyzed for frames where a parent region is indicative of a type of event.

The invention discloses a rainstorm disaster event argument extraction method and device based on event text enhancement, and the method comprises the steps: constructing a rainstorm disaster event template, and defining an event type and an argument role; extracting data related to the rainstorm disaster from the microblog platform; preprocessing the data; labeling the preprocessed data to obtain a data set; generating a problem template; performing event text enhancement; integrating the problem template and the enhanced event text as model input; encoding the integrated text by using a pre-trained Chine-BERT-WWM model, and obtaining a hidden layer representation; deep features are extracted through an intermediate linear layer, and starting and ending positions of an input sequence are predicted by using a full connection layer; according to the method, the rich MRC data set can be directly utilized to enhance event extraction, the problem of data scarcity is relieved, and possibility is provided for zero sample event extraction of invisible event types.

The invention discloses an abnormal event processing method and device, a storage medium and a computing program product. The method comprises the following steps: acquiring a first video frame sequence corresponding to a first event occurring in a first time period in a target area; identifying each first video frame in the first video frame sequence by using an image identification model to obtain first action generation information corresponding to each first video frame, and analyzing the first action generation information corresponding to each first video frame by using an event classification model to obtain a first event type of the first event; determining a first event influence index and a first event influence development index of the first event based on the first event type, and further determining a risk level corresponding to the first event; and processing the first event according to a processing strategy corresponding to the risk level. The technical problem that abnormal event processing is not timely due to the fact that related personnel are commanded and dispatched to process the abnormal event only according to the event type in the related technology is solved.

The invention discloses a document-level event extraction method based on an interleaving argument association matching algorithm, which relates to the field of natural language processing and comprises the following steps of: performing data enhancement on original data of a document-level event to generate an enhanced training data set; defining event types and argument roles corresponding to the event types, and constructing a structured event template; constructing a prompt template, and performing multi-task optimization on the UIE model in combination with the enhanced training data set; extracting an entity, a trigger word and an argument in the target document, and generating a structured recognition result; and carrying out structure recombination by adopting an interleaving argument association matching algorithm to generate a document-level event extraction result. According to the method, through data enhancement, prompt template construction and an interleaving argument association matching algorithm, the adaptability of the model under the condition of data deficiency is improved, error accumulation is reduced, cross-paragraph argument association is accurately recognized, and the accuracy and integrity of document-level event extraction are remarkably improved.

The invention belongs to the field of big data processing, and particularly relates to an event analysis method, device and equipment and a storage medium, target event information is obtained, the target event information is converted into event feature vectors, the event feature vectors are input into multiple analysis models respectively, and the analysis models output corresponding event types and initial risk levels respectively. Performing similarity matching on the event feature vector and a historical event feature vector of a historical event in a preset knowledge base, screening one or more pieces of historical event information of which the similarity score is greater than a preset threshold, and determining the credibility of each analysis model based on the historical event information and the event type, performing weighted fusion on the initial analysis result based on the credibility of each analysis model, and determining a target risk level corresponding to the target event information; according to the method, by combining multi-model analysis, historical data similarity matching and credibility weighted fusion, the accuracy of risk level judgment of the target event is improved.

The invention discloses a security event management method and device. The method comprises the following steps: acquiring multiple groups of first event data of different modes corresponding to a target security event; for each group of first event data, determining a pre-processing mode corresponding to the modal type of the first event data to pre-process the first event data to obtain second event data; performing format conversion on each group of second event data to obtain multiple groups of third event data matched with the input format of the security event classification model; the multiple sets of third event data are analyzed through a security event classification model, the target event type of the target security event is obtained, and the security event classification model is provided with a multi-head attention mechanism; and determining a security event processing strategy corresponding to the target event type, and executing the security event processing strategy. According to the method and the device, the technical problem that the system security is easily influenced due to difficulty in accurately identifying and processing the security event in a related scheme is solved.

The embodiment of the invention provides a process monitoring method and computing equipment, running information of a target process at a detection point of a process management function is obtained, a process change event is generated according to the running information, at least one detection point is set in the process management function, and the process change event comprises an identifier and an event type of the target process. The event type comprises a creation type, a destruction type and an update type; and notifying the target object of the process change event. According to the process monitoring method and the computing device, the target object can timely sense the process change event in the operating system and the event type of the process change event, the real-time performance of process monitoring is improved, all processes in the operating system do not need to be inquired every time, and the system overhead is low.

The invention discloses a door lock video recording method and system based on event value driving, and the method comprises the steps: detecting an event of a person according to a first door lock, obtaining a video stream address of a second door lock through door relation information, and synchronously caching video streams of the door locks of both parties; judging event types according to video analysis results, storing complete video streams of both parties for important events, and only storing panoramic images for non-important events; according to the door lock face detection time difference and the residual storage space of the two parties, negotiating to determine a single door lock to store video streams of the two parties; and according to a user query request, locally and directly responding or obtaining video data through door collaboration to finish query display. By utilizing the embodiment of the invention, efficient video acquisition and storage can be realized through cooperation of event driving and a door lock, the integrity of security and protection video records is improved, the storage space is saved, and more efficient and reliable intelligent query response is supported.

An automatic annotation method is implemented as part of an image activated cell sorter. A user inputs descriptive information about the events the user is trying to purify. Unsupervised clustering is used to group events with similar image features. Once clustering is complete, the automatic annotation algorithm uses the prior information and the features extracted during clustering to predict the identity of the events in each cluster and annotate the events.

The invention provides a traffic event fusion method and device, equipment, a medium and a product, and relates to the technical field of intelligent traffic, and the method comprises the steps: receiving a plurality of pieces of traffic event information reported by a multi-access edge computing MEC device; wherein the traffic event information comprises an event type, a detection equipment type, detection time, event end time and an event position; according to the event type, the detection time and the event position, grouping different traffic event information to obtain at least one traffic event information group; determining a first comprehensive confidence coefficient of each traffic event information group according to the event type, the detection equipment type, the detection time and the event end time; and generating a unique event identifier corresponding to the traffic event information group according to the first comprehensive confidence coefficient. Therefore, the same event forms a record, the accuracy of the data is improved, and the difficulty of handling, tracking and publishing the event is reduced.

The invention provides a target event detection method based on natural language processing and related equipment. The method comprises the following steps: acquiring event data of a to-be-detected event; detecting the event data based on a trained target event model, and determining that the to-be-detected event is a target event; wherein the trained target event model is obtained by training based on training text data about a target event, and the method comprises the steps that the training text data are acquired, and event types and target features of the target event are marked on the training text data; performing data preprocessing and data enhancement on the training text data to obtain enhanced text data; and training a natural language processing model based on historical text data and the enhanced text data to obtain the trained target event model.

Performance monitoring circuitry (40) has event counters (42) that each maintain a respective event count value based on monitoring events during processing of software by the processing circuitry. A control circuit (44) configures the event counter based on the counter configuration information. For at least a subset of the event counters, a given event counter (42) within the subset supports a chained counter operation that includes incrementing the given event count value by an increment value determined based on a logical combination of a first event state indication and a second event state indication, the first event state indication indicates a state of a first event type assigned by the counter configuration information to be monitored by a given event counter, and the second event state indication indicates a state of a second event type assigned by the counter configuration information to be monitored by a further event counter.

The invention relates to the field of natural language processing, in particular to a text processing method and device, electronic equipment and a medium. The text processing method comprises the steps of determining a first prompt word based on an event description text; inputting the first prompt word and the event description text into a first model for processing to obtain a first event type described by the event description text and a first trigger word of the first event type; determining a second prompt word based on the first event type, the first trigger word and the event description text; and inputting the second cue word and the event description text into a second model for argument extraction to obtain a first argument of the event description text. According to the invention, the event extraction accuracy can be improved.

The invention provides a power demand transaction assessment method, device and equipment considering the action of event factors, and the method comprises the steps: collecting the related information of a target event, and extracting the event entity information related to the power demand from the information; determining an event type according to a preset event classification system based on the event entity information, and determining an influence industry of the target event and influence coefficients of the target event on different industries based on event classification and an influence quantification knowledge base according to the event type; taking the influence industry as a processing group, adjusting the basic weight of each control unit in the control group corresponding to the processing group according to the influence coefficient, and obtaining the dynamic weight of each control unit; according to the dynamic weight, constructing an anti-factual power utilization path of the processing group under the condition that no target event occurs; and calculating the difference between the actual power consumption data of the processing group and the anti-fact power consumption path, and obtaining the net influence quantity of the target event on the power consumption demand of the processing group. According to the invention, the influence of emergencies on power demands can be accurately identified and quantified.

The invention discloses a semantic conflict recognition method and device based on event element extraction, and the method comprises the steps: carrying out the event detection of an input text, recognizing whether an event exists in the text, and determining the type of the event; determining an event element mode according to the event type; performing event element extraction on the event element mode corresponding to the text by adopting a pre-training model to obtain a labeling sequence of event elements; aligning events from different sources, and mapping the events to the same event framework after successful matching; performing semantic similarity calculation on event elements in the successfully matched multi-source event pairs; and judging whether the event elements have semantic conflicts or not according to a preset similarity threshold. According to the method, the accuracy and reliability of semantic conflict recognition can be improved, and the requirements for high-quality information processing in the fields of multi-source information fusion, public opinion monitoring, news reports and the like are met.

A check code reuse method based on a knowledge graph, an apparatus, and a storage medium. The method comprises: acquiring a description document corresponding to at least one check step in a check project; generating event types and parameter lists: by means of an event type classification model and a parameter list extraction model, generating an event type and a parameter list corresponding to each check step on the basis of the description document; searching for related code segments: by means of a knowledge graph, performing searching on the check steps on the basis of the event types and the parameter lists, so as to obtain N most related code segments; and generating candidate code segments: on the basis of the parameter lists, modifying the related code segments to generate candidate code segments. By means of the knowledge graph and the related models, the method can find code segments with similar structures and parameters with respect to description texts of operation steps, so as to complete conversion of the code segments, thereby facilitating check and reasonable combination of same, and finally realizing the overall check logic.

Example embodiments described herein therefore relate to an event detection system that comprises a plurality of sensor devices, to perform operations that include: generating sensor data at the plurality of sensor devices; accessing the sensor data generated by the plurality of sensor devices; detecting an event, or precursor to an event, based on the sensor data, wherein the detected event corresponds to an event category; accessing an object model associated with the event type in response to detecting the event, wherein the object model defines a procedure to be applied by the event detection system to the sensor data; and streaming at least a portion of a plurality of data streams generated by the plurality of sensor devices to a server system based on the procedure, wherein the server system may perform further analysis or visualization based on the portion of the plurality of data streams.

The invention discloses an emergency report generation method and device, equipment and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: acquiring and preprocessing original data corresponding to a target event to obtain first preprocessed data; inputting the first preprocessed data into a preset event recognition model, and recognizing to obtain an event type and an event progress stage of the target event; based on the event type and the event progress stage, determining a corresponding target template from a preset report template library; calculating contribution degrees of different data in the first preprocessed data to event levels based on a preset data screening model, and determining key data; and based on a natural language processing algorithm, converting the key data into a descriptive text, and filling the target template to obtain an emergency report. According to the method, the readability of the emergency report is improved on the whole, and the method is suitable for report generation of various emergencies.

The invention provides a data synchronization desensitization method and device, computer equipment and a readable storage medium. The method comprises the following steps: pre-configuring synchronization parameters; receiving a change event of the source database output by the change data capture engine; performing desensitization processing on the event load of the change event according to a preset desensitization function and a desensitization parameter; judging the event type of the change event; according to the event type and the dialect identifier, mapping an abstract type of a corresponding field in the event load into a physical type which can be understood by the target database to obtain type information of the field; generating a parameterized equivalent SQL template compatible with the target database dialect according to the dialect identifier, the event type and the type information of the field; the event load is bound to the parameterized equivalent SQL template, and a bound parameterized SQL statement is obtained; and executing the parameterized SQL statement in the target database. According to the invention, a set of general data synchronization and desensitization mechanism is constructed.

Embodiments provide systems and methods for logging events. A computer-implemented method comprises receiving input for selecting one or more event types to receive from an event collector, receiving, based on the one or more event types, a plurality of security events from the event collector, transforming each of the plurality of security events to a standard format to generate a plurality of formatted security events and transmitting the plurality of formatted security events to a security information and event management (SIEM) server.

The invention discloses a booster station monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. Collecting and recording events occurring in the booster station according to a preset data collection device; calling a corresponding preset event processing program according to the event type, and processing the event; and pushing the event, the preset event processing program and the event processing result according to a preset mode. The preset data acquisition device is used for automatically acquiring and recording events occurring in the booster station, wherein the events comprise data exception and equipment faults. And the system calls a corresponding preset event processing program according to the event type, processes the event, and pushes the event, the processing program and a processing result according to a preset mode. According to the automatic monitoring and processing mechanism, the fault finding and processing efficiency of the booster station is greatly improved, the requirement of manual intervention is reduced, and stable operation and safety of the system are ensured.

The invention discloses an intelligent event allocation method and device based on machine learning, and the method comprises the steps: loading the weight and architecture of a pre-training model from a model library, and enabling the pre-training model to be a language representation model; the event text data is input into a pre-training model, a gradient descent method is used for updating the weight of the pre-training model, an intelligent event distribution model is obtained, and the training and deployment process of the intelligent event distribution model is directly completed at the front end based on an open source library TensorFlow.js; under the condition that the input event information is detected, word segmentation processing is carried out on the input event information according to the intelligent event distribution model to obtain a prediction result, and the prediction result comprises an event type corresponding to the input event information; and updating the intelligent event allocation model based on the input event information and a corresponding event type result obtained by interaction with the user.

The invention relates to the technical field of data analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a sound signal analysis-based event processing method, device, equipment and medium, and the method comprises the steps: obtaining a to-be-analyzed sound signal, carrying out the segmentation processing of the to-be-analyzed sound signal, and obtaining a target sound segment; extracting sound features of the target sound fragment, and comparing the sound features with reference sound features in a preset feature library to generate a comparison result; and determining an event type corresponding to the target sound segment based on the comparison result, and when the event type satisfies a preset condition, executing a processing operation corresponding to the event type. According to the method, through sound signal segmentation processing and feature extraction, event types such as snore, apnea and enzootic pneumonia are accurately recognized, the event recognition accuracy is improved by combining feature comparison, corresponding processing is automatically executed based on the event types, and self-adaptive response of multiple event types is achieved.