34 results about "Event retrieval" patented technology

The invention discloses an operation and maintenance knowledge base analysis system and method based on deep learning, and is applied to unified operation and maintenance management of a hospital information system and medical equipment. The system collects operation and maintenance data such as operation logs, monitoring indexes, alarm events, work orders, maintenance records and the like, constructs a minute-level time window through equipment identification and technology triggering time, and merges multi-source heterogeneous data into operation and maintenance sub-events and operation and maintenance events. Log, index and text feature extraction is performed on each operation and maintenance sub-event, multi-modal feature fusion is performed to generate an operation and maintenance event feature vector, the operation and maintenance event feature vector is stored in a vector index database and is associated with an operation and maintenance knowledge graph, and similar historical event retrieval and root cause and processing scheme recommendation of a new operation and maintenance event are realized. In combination with the adoption and processing results of recommended schemes by operation and maintenance personnel, the system performs hierarchical management on the operation and maintenance knowledge and performs incremental updating on the feature modeling network, so that the operation and maintenance knowledge retrieval accuracy and the fault positioning efficiency are improved.

The invention discloses a bank data analysis processing method and system, particularly relates to the technical field of bank data processing, and is used for solving the problem that multi-source data is difficult to trace uniformly. Multi-service system records are accessed through a unified time reference and a subject identifier, scattered records are recombined into event frames with event types, time and subject sets based on event anchor point rules, conflict resolution is performed on multi-source same-name fields according to authoritative source priorities and delay propagation thresholds, main field values and alternative field values are reserved, and multi-source same-name fields are obtained. On this basis, an event frame table, a state sequence table and a participating entity table are constructed, indexes are established according to subject identifiers, time intervals, event types and state codes, retrieval and statistics around customer events are achieved, data consanguinity among source fields, event frame fields and analysis fields is synchronously established when the analysis fields are generated, and the data consanguinity among the source fields, the event frame fields and the analysis fields is established; and in combination with the version information, tracing of index sources in a rule change and late data scene is supported.

The invention provides a distributed data storage method, device and equipment and a readable storage medium, and the method comprises the steps: responding to an event created by a storage target, obtaining metadata of the storage target, and submitting the metadata to a key-value pair database in a key-value pair manner; a distributed file system is called to split the specific file into distributed storage objects, and the distributed storage objects obtained through splitting are sent to object storage equipment of a distributed storage cluster; and in response to an event of storage target change, retrieving the corresponding key value pair and modifying the metadata recorded by the corresponding key value pair according to the change condition. Through the technical scheme of the specification, the metadata is stored by the key-value pair granularity, the problem of directory-level read-write amplification is relieved, single file metadata update only needs to modify the corresponding key-value pair, overall directory rewriting is avoided, and IO consumption and network delay are reduced in combination with a write-in merging mechanism of an embedded database and the transparent object splitting capability of a distributed file system.

The invention relates to the technical field of information engineering knowledge graph construction, in particular to a supervision knowledge graph dynamic modeling method based on multi-source heterogeneous data fusion, and the method comprises the steps: designing a four-dimensional knowledge graph modeling framework, and combining the entity alignment of a graph neural network, the relation extraction of remote supervision and the attribute processing of weight fusion. A dynamic evolution and cross-source consistent knowledge network is constructed, virtual features are generated through a virtual feature compensation mechanism (historical event retrieval and multi-dimensional feature weighted fusion) for a multi-modal data missing scene and mapped to a graph, data are effectively filled, the problem of incomplete knowledge coverage in a complex engineering scene is solved, a compliance entropy evaluation model is introduced, and the knowledge coverage is evaluated. The compliance state of the knowledge graph is quantitatively supervised from the three dimensions of rule coverage rate, data consistency and tracing integrity, and the hysteresis and subjectivity limitation of traditional manual compliance check is broken through.

The present invention relates to a method and device for rapid retrieval of seismic events. The beneficial effect of the present invention is that, in view of the impact characteristics of earthquakes, a set of rapid retrieval methods are designed, which can quickly retrieve seismic events that may cause losses. This method first needs to create a spatial index of seismic events. Although traditional indexes can quickly retrieve the locations of data, since the relevant data are often stored in different places, it is impossible to read them in one piece at a time. Frequent reading operations reduce the speed of data retrieval. The present invention reorganizes the storage order and location of data according to the spatial positions of earthquakes and ensures that the time complexity of retrieval is O(1).

The present invention relates to a Chinese-Vietnamese cross-language event retrieval method incorporating event knowledge, and belongs to the technical field of natural language processing. The present invention includes: constructing a Chinese-Vietnamese cross-language event pre-training module for continuous pre-training to improve the representation effect of the model on the low-resource languages ​​of Chinese and Vietnamese, and distinguishing the difference between the masked predicted value and the true value of the event knowledge based on contrastive learning, so as to enable the model to better understand and capture the characteristics of event knowledge. The Chinese-Vietnamese cross-language event retrieval method incorporating event knowledge proposed by the present invention, compared with information retrieval, cross-language event retrieval enhances the focus on event elements in the query to ensure the consistency between the target retrieval event and the query, and plays an important role in tasks such as accurate monitoring of public opinion events.

An information processing device (100) is provided with: a log acquisition unit (101) that acquires a log of an in-vehicle device (112); a determination unit (102) that determines, on the basis of the acquired log, whether or not a predetermined target event has occurred among events occurring in the in-vehicle device (112); a search unit (103) that executes a log search process when it is determined that the target event has occurred; and a transmission unit (104) that transmits the log acquired by the search process to the center, the search process including: a specifying process that specifies an associated event associated with the target event; an acquisition process for acquiring a log for determining whether or not the associated event identified by the identification process has occurred; and a determination process for determining whether or not an associated event has occurred on the basis of the log acquired by the acquisition process.

The present application relates to the field of large-scale industrial automation system. An event collection method of large-scale industrial automation system classifies the equipment involved in the large-scale industrial automation system and defines four-level standard events, and takes an event subject as the minimum collection unit when an event corresponding to each event subject occurs. When the submission period is met in time or the number of events in the event stack meets the batch submission number, each field of each event in the event stack is serialized, and the events in the event stack are packed to generate a data frame by a protocol stack program and sent to a central event server. In the central event server, the received events are stored in the time sequence database, the event subscription and query steps, the event retrieval terminal is connected with the central event server, and the events archived in the central event server are pushed to the event retrieval terminal through the subscription or query mode.

The present application relates to the technical field of intelligent transportation, and more particularly to a traffic event image-text mutual search method and system based on cross-modal retrieval, which comprises the following steps: obtaining query data of a traffic event, structurally processing the query data to obtain query semantic units; performing feature coding on the query semantic units to generate query semantic vectors; constructing a weak common semantic space, and setting an image index channel and a text index channel for the weak common semantic units; selecting an index channel according to the query data, mapping the query semantic vectors to the weak common semantic space for similarity matching, and generating a traffic event preliminary search result set; and performing fine sorting on the traffic event preliminary search result to output a traffic event search result set. Through the present application, the problems of low search efficiency and insufficient search accuracy in large-scale search are effectively solved, the matching deviation caused by modal difference is reduced, and the efficiency and business adaptability of traffic event search are effectively improved.

The present invention relates to a cross-border ethnic cultural event retrieval method and device based on an event element graph, and belongs to the field of natural language processing technology. The text used for query in the cross-border ethnic cultural event retrieval task is usually some brief descriptions or keywords of certain events, but the domain entities existing in the brief descriptions or keywords often lead to the retrieval results being mostly popular science texts about these domain entities, resulting in a low relevance between the cross-border ethnic cultural event retrieval results and the query events. In view of the above problems, the present invention proposes a cross-border ethnic cultural event retrieval method based on an event element graph, which mainly includes three parts: cross-border ethnic cultural event data construction and preprocessing, cross-border ethnic cultural event element graph construction, and cross-border ethnic cultural event retrieval model training based on the event element graph. According to these three functional modules, a cross-border ethnic cultural event retrieval device based on the event element graph is made. The present invention effectively improves the effect of cross-border ethnic cultural event retrieval.

The invention belongs to the technical field of traffic management and image processing, and discloses a traffic accident detection method based on a multi-modal video classification model, which comprises the following steps: S1, detecting and tracking a vehicle; s2, searching a parking vehicle in the current frame; s3, clustering and outputting parking areas; s4, extracting an ROI image sequence of the parking area; and S5, performing video classification by using a multi-mode large model Video CLIP, and judging whether an accident occurs or not. The invention also discloses a traffic accident detection system based on the multi-modal video classification model. The system comprises a video stream acquisition unit, a traffic accident detection unit, an alarm unit and an event retrieval and query unit. The method is high in operation speed, firstly, whether a potential accident exists or not is judged through parking, a potential accident area can be accurately positioned, and the calculation pressure of a follow-up video classification network is relieved; the robustness is better, and the problem of poor model generalization caused by insufficient video training samples can be relieved by utilizing the prior of text information.

Devices and techniques for recovering damaged storage portions in a memory device are described herein. During a garbage collection operation on a collection of storage portions (e.g., pages) in a memory array, a failure event is detected. Here, members of the collection of storage portions are moved from previous physical locations to new physical locations by the garbage collection operation. In response to the failure event, a reference to the previous physical location of a potentially damaged storage portion in the collection of storage portions can be retrieved. Here, as part of the garbage collection operation, the potentially damaged storage portion has been written to the new physical location. The potentially damaged storage portion can then be overwritten at the new physical location using data from the previous physical location.

This disclosure describes, in part, techniques for retrieving images based on detecting events. For instance, system(s) may detect an event, such as an event associated with a collection of images for an item. Based on detecting the event, the system(s) may determine an area within a facility, such as an inventory location, for retrieving image data. The system(s) may then determine one or more imaging devices that have field(s) of view of the area. Additionally, the system(s) may score the imaging device(s) based on visibility data associated with the imaging device(s). The system(s) may also determine occlusion data for image data generated by the imaging device(s). Using the scores and the occlusion data, the system(s) may then select image data that represents the area. The system(s) may then store the image data in one or more data stores, such as with the collection of images.

The present application relates to an optical measurement method for high-dynamic high-speed target motion parameters using an event camera network. The method includes: arranging a multi-view event camera synchronous observation system in the area to be observed and performing parameter calibration, observing a high-dynamic high-speed target to obtain observation event stream data; constructing a two-dimensional map of event-starting point distance versus time for each view according to the observation event stream data, and obtaining a target head feature event set from the two-dimensional map of event-starting point distance versus time; using the target head feature event sets in multiple views to intersect the target motion straight-line trajectory in three-dimensional space; retrieving the target motion straight-line trajectory according to the three-dimensional straight-line point homologous event retrieval method based on reprojection error, establishing the correspondence between three-dimensional space position and time, and using a fitting method to achieve motion parameter measurement calculation and reconstruct a three-dimensional motion field. Using this method can achieve high time resolution and high dynamic range.

The application belongs to the technical field of computers and provides a fault diagnosis method and system based on equipment maintenance knowledge base. The method comprises the following steps: constructing an equipment maintenance knowledge base, wherein the equipment maintenance knowledge base comprises phenomenon events, fault causes and the relationship between the phenomenon events and the fault causes, the relationship is a fault scene, and the fault scene comprises a single cause scene and a combined cause scene; acquiring a last node in a fault diagnosis path as a phenomenon event, retrieving a fault scene of the phenomenon event, and if the retrieval result is empty, the phenomenon event is a fault diagnosis result. The single cause scene can realize the reasoning ability of the traditional decision tree rule, the combined cause scene is combined with the single cause scene, the fault combination condition traversal with exponential complexity can be automatically expanded based on a small amount of structured expression, the knowledge representation is simplified, and the complexity and workload of the construction and maintenance of the knowledge base are reduced.

The invention discloses a video event retrieval method based on space-time interlacing, which is characterized by comprising the following steps of: firstly, acquiring a hash code of a training sample, a video event classification prediction result of the training sample and action classification prediction of a single object through a feature extraction model to be trained, a space-time interlacing model to be trained and a hash retrieval model to be trained; performing training based on the constraint of the total loss function to obtain a trained feature extraction model, a trained space-time interlacing model and a trained Hash retrieval model; enabling a query sample and a retrieval sample to pass through each trained model to obtain a corresponding hash code of the query sample and a corresponding hash code of the retrieval sample; searching a Hash code closest to the Hash code of the query sample in a retrieval set Hash code retrieval library as a retrieval result, and displaying the retrieval result to complete the retrieval process of the query sample; the method has the advantages that the output hash codes are efficient and compact, and the retrieval accuracy is high.

The invention discloses a multi-level video group event retrieval method. The method is characterized by comprising the following steps: firstly, carrying out object-level visual feature reconstruction and establishing a space-time relation graph between objects; performing multi-level fusion through a multi-level space-time fusion module; an event classification prediction result corresponding to the multi-level fusion result and a corresponding Hash code are obtained through a Hash module retrieval module, and then network training is performed to obtain each trained model; the method has the advantages that by combining action classification loss, event classification loss, Hash loss, Hash filtering loss and reconstruction loss of a single object, feature representation and a Hash function can be learned from an input video at the same time, and an obtained Hash code is efficient and compact, so that video event retrieval is effectively performed; and finally, sequentially carrying out matrix multiplication on the obtained Hash codes through the filtering matrix, so that the Hash codes are close to the Hash codes output by the upper layer, and the storage space of the multi-layer Hash codes is effectively reduced.

The present invention relates to a system (108) and a method (600) for forecasting events in a network The method (600) includes step of retrieving, data pertaining to the forecasting event from an inventory unit (206). The method (600) further includes the step of training a model with trends / patterns of the historic data; forecasting one or more events utilizing the trained model (211) on new data; retrieving one or more actual values subsequent to occurrence of the one or more events; and rendering at least one of, the forecasted one or more events and the one or more actual values to a user. The invention facilitates consumers to identify and understand discrepancies between predicted values and actual values and assisting in diagnosing and improving forecasting models.

This invention provides a cross-modal livestock behavior retrieval method and device, relating to the field of text-video retrieval technology. The method comprises: obtaining a livestock video and user-entered input text, the input text including livestock behavior events; extracting a target sentence, nouns, and verbs from the input text; determining the target sentence's noun and verb retrieval tags based on a set of words corresponding to livestock behavior retrieval tags; searching for video features from a video-text multi-channel feature set that match the noun and verb retrieval tags and the sentence structure of the target sentence; and retrieving livestock behavior events from the livestock video based on the matched video features. This approach improves the accuracy of livestock behavior event retrieval from livestock videos based on the input text.

The invention relates to the technical field of intelligent traffic, in particular to a traffic incident secondary recognition method and system based on deep learning, and the method comprises the steps: monitoring and collecting traffic information in real time, reporting the traffic information when the traffic information is recognized as a traffic incident, processing the traffic incident information, and forming a database; an event target and an event type are confirmed, the event target is confirmed by using a secondary identification model, and if the event target does not accord with the event type, false alarm reminding is executed; for the traffic events, whether report records with the same event type exist in a database within unit time is retrieved, if not, normal report is executed, the report records of the database are updated, and if yes, repeated traffic event report filtering is executed; classifying the event types of the traffic events, and merging the multiple levels of traffic events; judging whether the event type of the traffic event is matched with a related business rule or not, and if yes, filtering the traffic event; and the safety, the stability and the working efficiency of the monitoring system are improved.

One embodiment comprises a non-transitory storage medium storing program code to receive one or more sensory events from a sensory event analytics module that receives sensory data about a physical environment from one or more sensors and processes the sensory data from the one or more sensors to detect the one or more sensory events. The one or more sensors include at least an Internet Protocol (IP) video camera. The one or more sensory events include one of a face detected, a vehicle detected, and a license plate detected. The program code includes code to store the sensory events for later retrieval as stored sensory events; and evaluate one or more historical correlations among the stored sensory events by evaluating the stored sensory events for the one or more historical correlations across at least one of time and space based on at least one weight vector.

The invention provides a short video false news detection method based on a thinking chain and mixed experts. The short video false news detection method comprises the steps of structured thinking chain construction, mixed verification expert module construction, mixed theme expert module construction, model training and parameter optimization and short video false news detection reasoning. According to the method, a structured thinking chain is designed, a multi-modal large language model is guided to simulate a human rumor recognition thinking process, news element extraction, event retrieval and multi-angle reasoning are completed in sequence, and fine-grained reasoning explanation is generated from three aspects of cross-modal consistency, fact verification and logic verification; meanwhile, a hybrid verification expert module is introduced, multi-angle evidences are integrated through a dynamic routing mechanism, key reasoning features are captured, and the judgment credibility is improved; and in combination with a mixed topic expert module, a discrimination standard is adaptively adjusted according to a short video topic scene, and the generalization ability and discrimination precision of the model under different topics are enhanced, so that interpretable robustness detection of the short video false news is realized.

One embodiment comprises a non-transitory storage medium storing program code to receive one or more sensory events from a sensory event analytics module that receives sensory data about a physical environment from one or more sensors and processes the sensory data from the one or more sensors to detect the one or more sensory events. The one or more sensors include at least an Internet Protocol (IP) video camera. The one or more sensory events include one of a face detected, a vehicle detected, and a license plate detected. The program code includes code to store the sensory events for later retrieval as stored sensory events; and evaluate one or more historical correlations among the stored sensory events by evaluating the stored sensory events for the one or more historical correlations across at least one of time and space based on at least one weight vector.

The invention belongs to the technical field of cross-modal video moment positioning, and relates to a cross-modal video sensitive event retrieval method and system based on frequency domain enhancement. The method comprises the following steps: acquiring data of a text mode and data of a video mode, and respectively encoding the data of the two modes to obtain features of the two modes; projecting the features of the two modals to a frequency domain through fast Fourier transform, and enhancing the features of the video modals in the frequency domain to obtain frequency domain enhanced video features; generating positive and negative candidate video segments for the frequency domain enhanced video features through Gaussian distribution, respectively representing candidate video segments closest to a retrieval request and candidate video segments closest to the retrieval request, and selecting the candidate video segment closest to the retrieval request as a retrieval result so as to realize cross-modal video moment positioning; and multi-scale contrast learning is carried out on the positive and negative candidate video segments, so that the generation quality of the positive and negative candidate video segments is improved, and the accuracy of cross-modal video sensitive event retrieval is improved.

The present application relates to the technical field of information engineering knowledge graph construction, and particularly relates to a supervision knowledge graph dynamic modeling method based on multi-source heterogeneous data fusion. The method constructs a dynamic evolution and cross-source consistent knowledge network by designing a four-dimensional knowledge graph modeling framework, combining entity alignment of a graph neural network, relationship extraction of remote supervision, and attribute processing of weighted fusion. For a multi-modal data missing scenario, a virtual feature compensation mechanism (historical event retrieval, multi-dimensional feature weighted fusion) is used to generate virtual features and map them to the graph, effectively filling in the data and solving the problem of incomplete knowledge coverage in complex engineering scenarios. A compliance entropy evaluation model is introduced to quantify the compliance state of the supervision knowledge graph from three dimensions of rule coverage, data consistency, and traceability integrity, breaking through the limitations of the traditional artificial compliance check in terms of lag and subjectivity.

The invention discloses a potential evapotranspiration extreme event intelligent identification method for time sequence big data, and relates to the technical field of big data mining, and the method comprises the steps: collecting meteorological data, carrying out the quality control and restoration, calculating the daily potential evapotranspiration amount, writing in a column storage table of time and space partitions, and forming a potential evapotranspiration time sequence data set; obtaining a conditional quantile baseline value and a scale parameter according to the potential evapotranspiration time sequence data set, performing streaming updating, calculating a standardized residual error through the conditional quantile baseline value and the scale parameter, and generating a standardized residual error sequence; according to the standardized residual sequence, identifying continuous high-value time periods and generating event objects, calculating extreme strength indexes and sorting the extreme strength indexes to obtain an event curve and an event list; and constructing an event signature through the event curve and the event list and establishing an inverted index, and performing intelligent identification and result archiving on the potential evapotranspiration extreme event through similar event retrieval. And a comparable, searchable and reusable effect can be achieved for potential evapotranspiration extreme events.

The invention relates to the technical field of intelligent traffic, in particular to a traffic event image-text mutual search method and system based on cross-modal retrieval, and the method comprises the steps: obtaining query data of a traffic event, and carrying out the structural processing of the query data, and obtaining a query semantic unit; performing feature coding on the query semantic unit to generate a query semantic vector; constructing a weak common semantic space, wherein a weak common semantic unit is provided with an image index channel and a text index channel; selecting an index channel according to the query data, mapping the query semantic vector to a weak common semantic space for similarity matching, and generating a traffic event initial detection result set; and carrying out refined sorting on the traffic event initial inspection results, and outputting a traffic event retrieval result set. According to the method and the device, the problems of low large-scale retrieval efficiency and insufficient retrieval precision are effectively solved, the matching deviation caused by modal difference is reduced, and the efficiency of traffic event retrieval and the business suitability are effectively improved.

The invention discloses an event retrieval method and system in a mixed scene, electronic equipment and a storage medium, and the method comprises the steps: receiving video stream information in a plurality of scenes, segmenting the video stream information, and obtaining a plurality of image sets; generating a first prompt word of the first image set according to a preset event library; the preset event library comprises description information and label information of the image set; inputting the first cue word and the first image set into a multi-modal large model to obtain a first cognitive result corresponding to the first image set, and storing the first cognitive result into the preset event library; obtaining question information of the to-be-retrieved target event; and according to the question information, performing retrieval in the preset event library to obtain a target event. According to the method and the device, the events in multiple scenes can be retrieved, and the retrieval efficiency can be improved. The method can be widely applied to the technical fields of smart cities and Internet of Things.

The invention discloses an event report generation method and device, equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence. Based on a user input event, event retrieval is carried out in the internet resources and the private knowledge base, and event related information is obtained; screening and integrating the event related information to obtain event refining data; generating a plurality of event subtopics based on the event refining data; for each event subtopic, content supplementation is carried out based on event related information, and an event context containing all the subtopics is obtained; based on the output style framework, event contexts are sorted, a complete event report is obtained, the complete event report is input into a webpage generation model, and an event report visual page is generated in combination with cue words. The method has the technical effect of improving the generation stability of the event report.

A method is generally provided for adjusting a pattern projection rate in an active perception system, comprising the steps of observing a scene with an event-based sensor array; projecting a current light pattern of a sequence of light patterns on the scene for a given interval of time; retrieving events generated by the event-based sensor array in response to the projection of the current light pattern; monitoring a property of the event retrieval progress; and dynamically controlling the projection of the light pattern based on the property.