319 results about "Filtering rules" patented technology

The invention discloses a data filtering and noise reduction method based on laser point cloud. According to the method, the multi-scale features are intelligently screened through the random forest algorithm, and the system can automatically generate the optimal filtering rule according to the local geometric characteristics of the point cloud without depending on manual parameter presetting. In a complex urban scene, a fine structure of a high-rise vertical face can be accurately reserved through curvature features, and sparse noise of a vegetation area is rapidly eliminated through a density threshold value. The data-driven adaptive mechanism not only reduces the manual intervention cost, but also greatly improves the scene generalization ability of the filtering strategy, so that the filtering strategy can still keep stable output in a dynamic environment. The dynamic interference is accurately positioned by combining the consistency verification of the motion trails of the multi-frame point clouds and utilizing the time sequence correlation analysis, so that the data reliability in a complex dynamic scene is remarkably improved, and a solid foundation is provided for high-precision three-dimensional reconstruction and real-time perception.

The invention provides a medical AI question and answer method based on retrieval enhancement, which comprises the following steps: acquiring a medical professional knowledge base, and constructing an entity recognition model and a medical knowledge graph; the method comprises the following steps: splitting a medical professional knowledge base, and creating a vector index and a full-text retrieval reverse index; intention classification is carried out, and initial processing is completed; performing multi-path mixed retrieval on the medical professional knowledge base to obtain a user question related text block; a filtering rule is preset, and the user question related text blocks are filtered; answering the user question according to a preset second prompt word, and answering the user question according to a preset third prompt word when the user question exceeds the range of the medical professional knowledge base or the multi-path mixed retrieval has no result. According to the method, related context information can be accurately searched, reliable reference information is provided for a generative large model to answer professional questions, the interactive experience of a medical question answering system is improved, and the accuracy and specialty of answer generation of the system are remarkably improved.

The invention discloses a source code change analysis method, system and equipment. The method comprises the following steps: acquiring a project source code and identifiers corresponding to the project source code in at least two versions; comparing differences of project source codes between different versions based on the identifiers, and determining code change content; filtering the code change content according to a preset filtering rule, and determining a change method name; performing code analysis on a method calling relation in the project source code, and determining a method calling link diagram; identifying the method calling link diagram by referring to a change method name, and determining a change influence link diagram; analyzing according to the entry of the change influence link diagram, and determining the range of the entry and a corresponding calling link; according to the method and the device, case design is performed according to the range of the code change influence entry and the corresponding calling link, and the evaluation of the test coverage is completed, so that the efficiency of test work is improved, the possibility of human errors is reduced, the test result is more accurate and reliable, and the evaluation of the test coverage is realized.

The invention discloses a multi-path suppression positioning method and system for a banded sparse single Beidou CORS network, and relates to the technical field of satellite navigation positioning. According to the multi-path suppression positioning method for the banded sparse single Beidou CORS network, initial pseudo-range time sequence data are acquired, the time sequence data and regional state data are received, the pseudo-range data are corrected and analyzed, then, filtering processing is performed by using a preset filtering rule, a virtual base station is established, data fusion is performed, and the multi-path suppression positioning method for the banded sparse single Beidou CORS network is obtained. According to the method, the pseudo-range time sequence data of each satellite is dynamically corrected, and particularly, through comprehensive analysis of the reflecting surface information, the environment data and the signal arrival time difference, the accurate position information of the receiver is obtained. Errors caused by reflecting surface and environment changes can be recognized and corrected in real time, and the stability and precision of a positioning system in a complex environment are remarkably improved.

Methods, apparatuses, systems, and machine-readable media are disclosed for improving packet filtering efficiency by reducing processing time and / or by reducing memory usage. Any of various types of data structures, such as flat hash maps and / or ruletrees, may be used by a packet filtering appliance to search for cybersecurity policy packet filtering rules that should be applied to in-transit packets. The packet filtering appliance may search the index data structures for matches of search objects, in the form of values that the packet filtering appliance extracts from in-transit packets, to threat indicator matching criteria of the policy rules. Each of the index data structures may map rule identifiers (rule IDs) of policy rules to keys that are based on (or that comprise) the matching criteria of those rules.

The present application provides a model segmentation method, a device and a storage medium. Segmentation parameters in different segmentation dimensions can be generated for a target model, and the generated segmentation parameters are filtered according to preset filtering rules, such that the remaining segmentation parameters in the segmentation dimensions are significantly reduced, and thus the number of segmentation strategies generated by means of combining the remaining segmentation parameters can also be significantly reduced. Candidate segmentation strategies that meet verification conditions are searched for among the segmentation strategies obtained by means of combination. After multi-level filtering operations, low-quality segmentation strategies can be rationally discarded, thereby making the number of retained candidate segmentation strategies more streamlined. The performance of the target model under each candidate segmentation strategy is evaluated, such that an appropriate target segmentation strategy can be finally determined to serve as the basis for distributed deployment of the target model.

The invention belongs to the technical field of natural language processing and knowledge engineering, and discloses a method, a system, equipment and a medium for automatically constructing a multi-field scientific knowledge base, and the method comprises the following steps: based on an input identifier list or a field search word, retrieving a full text of a literature, analyzing and converting the full text into a structured text; combining a pre-configured large language model with a field cue word, extracting key information in the structured text, and outputting structured data; the automatic script filters irrelevant, repeated or incomplete structured data according to a pre-configured filtering rule; performing standardization processing on the filtered structured data so as to realize the consistency and comparability of the data; and inserting the standardized structured data into an interactive knowledge base or database, establishing data association, and verifying association logic. The method supports cross-field rapid adaptation, solves the problems of low efficiency and high error rate of a traditional method, and can be widely applied to the fields of biomedicine, material science, synthetic biology and the like.

The invention belongs to the field of data processing, and discloses a real-time data processing system and method for the Internet of Things. Comprising a long-tail device, data of a long-tail device end is transmitted to an edge layer through a communication protocol, an edge gateway in the edge layer is used for receiving the data, the edge layer further comprises a data filter, and the data filter discards useless data based on a filtering rule and retains value data; performing normal data and potential anomaly marking on the data based on a filtering rule, and finally outputting high-value data through an anomaly confirmation mechanism; the event detector performs anomaly detection on the value data through a model rule, if the data is abnormal, the data is divided into a high-priority queue, otherwise, the data is a low-priority queue, the high-priority data is transmitted to the cloud for application preferentially, and the low-priority data is subjected to settlement processing; and the cloud is used for receiving the high-priority data and triggering an alarm notification, thereby realizing high-efficiency and high-quality processing of real-time data oriented to the Internet of Things.

The invention relates to a method for actively collecting a micro-service error log, which comprises the following steps: collecting a micro-service log according to pre-configured task information, the pre-configured task information comprising a micro-service name and a log path, and the micro-service log comprising log content, a link tracking ID and log context information; filtering the micro-service log according to the filtering rule to obtain a key error log, wherein the key error log is used for representing generated important error information; filling the abnormal type, the log context and the link tracking ID analyzed based on the key error log into a structure template to generate a structured log file; and sending the structured log file to the target receiving end according to the configuration information. According to the method, a rear-end collection mode is adopted, the micro-service logs are automatically collected, developers do not need to manually log in a server or query log files, and time and energy are saved.

The invention relates to the technical field of operating systems, and discloses a file operation tracking method and device, computer equipment and a storage medium, and the method comprises the following steps: creating a first tracking point and a second tracking point for each file operation function; in response to the fact that the file operation function is called, triggering a corresponding first tracking point; based on the first tracking point, collecting a file path and calling information of the file operation function; storing the file path under the condition that the file path conforms to a preset filtering rule; and in response to return of the file operation function, triggering the second tracking point, obtaining a return value of the file operation function, and sending the return value, the file path and the calling information to a user layer. According to the method, the tracking points are set, the whole life cycle of the file operation function is comprehensively monitored, the complete context information, including the file path and the calling information, of the file operation is obtained, the unnecessary data volume is reduced through the preset filtering rule, efficient and accurate tracking of the file operation is achieved, and the stability and the safety of the system are improved.

The invention provides a retrieval method and device based on graph structure retrieval enhancement, electronic equipment and a storage medium, and the method comprises the steps: obtaining original data, screening the original data based on a preset screening rule to obtain a plurality of candidate phrases, calculating the similarity between the plurality of candidate phrases and a preset central semantic vector of each layer, the multiple candidate phrases are layered according to the similarity, feature vectors are constructed, levels and feature vectors corresponding to the multiple candidate phrases are obtained, graph entities are obtained based on the candidate phrases, context fragments of the graph entities in original data are extracted, and relation types between the graph entities are obtained based on the context fragments; according to the relationship type between the graph entities and the hierarchy of the graph entities, a multi-hierarchy knowledge graph is obtained, and retrieval is performed based on the multi-hierarchy knowledge graph and the corresponding associated information block, so that the technical problems of result redundancy and logic fracture of a retrieval enhancement generation method are solved through the method.

The embodiment of the invention provides a model segmentation method and device and a storage medium. According to the embodiment of the invention, the segmentation parameters under different segmentation dimensions can be generated for the target model, and the generated segmentation parameters are filtered according to the preset filtering rule, so that the residual segmentation parameters under each segmentation dimension are obviously reduced, and the number of segmentation strategies generated by mutual combination is also obviously reduced. In addition, candidate segmentation strategies conforming to verification conditions are searched from the combined segmentation strategies. Therefore, through multi-level filtering operation, low-quality segmentation strategies can be abandoned reasonably, so that the number of the reserved candidate segmentation strategies is more simplified. Performance evaluation is carried out on the target model under each candidate segmentation strategy, and an appropriate target segmentation strategy can be finally determined. Therefore, the appropriate target segmentation strategy can be efficiently determined for the target model, the appropriate target segmentation strategy is used as a basis for distributed deployment of the target model, manual experience does not need to be relied on any more, and therefore the model segmentation effect can be effectively improved.

The invention discloses an unpowered device binding and positioning method and system based on the passive Internet of Things, and the method comprises the steps: receiving device identification information broadcasted by a plurality of passive tags through a positioning gateway installed on a tractor, and enabling the passive tags to be fixed to a dragged unpowered device; processing the equipment identification information based on a preset electromagnetic signal filtering rule, and generating a bound equipment list; generating a marshalling sequence list according to the signal intensity data of each passive tag in the binding equipment list; acquiring real-time position data of the tractor, wherein the real-time position data comprises latitude and longitude and azimuth angles; according to the marshalling sequence list, pre-stored equipment physical length data and the real-time position data, absolute position coordinates of all the unpowered equipment are solved through a space relation model. The technical problems of poor safety, high cost and insufficient marshalling positioning precision caused by dependence on battery power supply in the prior art are solved.

The invention relates to a message processing method and device, an electronic device and a storage medium. The method comprises the following steps: in response to a to-be-processed source message, acquiring analysis rule configuration information corresponding to the source message through a rule real-time monitor so as to analyze and convert the source message into a first intermediate message of a memory object structure; obtaining a message filtering rule corresponding to each message theme from the rule offline file through a rule real-time monitor so as to filter the first intermediate message to obtain a second intermediate message matched with each message theme; obtaining generation rule configuration information configured under each message theme and a target theme subscribed by a target receiving end; and performing message format conversion processing on the second intermediate message matched with the corresponding message theme by using the generation rule configuration information to obtain a target message, and forwarding the target message matched with the target theme to a target receiving end. On the premise of not invading logic of a generator end and a consumer end, messages can be filtered and forwarded universally and flexibly.

A traffic filtering method includes a network edge node that provides a cloud service that receives target traffic; obtains a filtering rule, where the filtering rule is for filtering, based on a filtering action, target traffic that meets a filtering condition; invokes a rule engine to parse and execute the filtering rule, where the rule engine is deployed in the network edge node or in a network edge processing system connected to the network edge node; and obtains filtered target traffic based on an execution result, where the filtered target traffic is traffic that meets a filtering requirement corresponding to the filtering rule. The target traffic filtered according to the filtering rule includes at least one of traffic sent by a network side to a user terminal and traffic sent by the user terminal to the network side.

This disclosure relates to data association, attribution, annotation, and interpretation systems and related methods of efficiently organizing heterogeneous data at a massive scale. Incoming data is received and extracted for identifying information (“information”). Multiple dimensionality reducing functions are applied to the information, and based on the function results, the information are grouped into sets of similar information. Filtering rules are applied to the sets to exclude non-matching information in the sets. The sets are then merged into groups of information based on whether the sets contain at least one common information. A common link may be associated with information in a group. If the incoming data includes the identifying information associated with to the common link, the incoming data is assigned the common link. In some embodiments, incoming data are not altered but assigned into domains.

According to the intelligent terminal equipment intelligent adaptation method and device, intelligent terminal automatic discovery is carried out based on scene-based adaptive ARP scanning and multi-fingerprint UPnP filtering, access equipment is obtained, automatic and precise discovery of intelligent terminal equipment is achieved, and the intelligent terminal equipment can be automatically and accurately found by standardizing the scanning frequency and the filtering rule. The equipment discovery efficiency and accuracy are improved, the access equipment is subjected to prefabricated API library matching and AI reverse analysis to obtain interface information of the access equipment, automatic analysis of a standard interface and a private interface is realized based on a multi-dimensional analysis technology of an AI large language model, and the equipment discovery efficiency and accuracy are improved by utilizing the AI large language model and combining a built-in multi-language programming template. According to the method, the adaptive code matched with the interface information is automatically compiled, the adaptive code is automatically generated based on the AI technology, the compatibility of multi-protocol and multi-interface type equipment is supported, and finally the core problems of low efficiency, poor compatibility, difficult maintenance and high threshold in the existing intelligent terminal adaptation process are solved.

Disclosed are a multicast service filter rule transformation method and apparatus. A multicast service filter rule transformation method according to an embodiment includes receiving a unicast filter table, transforming the received unicast filter table into a plurality of multicast service filter tables by dividing rule entries of the unicast filter table, and generating a multicast egress port that matches each filter rule in the multicast service filter tables.

The invention relates to a data packet filtering method and device. The method comprises the following steps: extracting dimension information of a data packet, wherein the dimension information comprises at least one of a source IP address, a destination IP address, a source port, a destination port and a protocol type; sending the data packet to a corresponding virtual system; the virtual system matches the dimension information of the data packet with a pre-configured strategy template; when the matching is successful, filtering the data packet according to a filtering rule corresponding to the strategy template; and when the matching is unsuccessful, filtering the data packet through a strategy tree. According to the data packet filtering method and device, the packet filtering strategy analysis and matching efficiency can be improved, and the network attack protection efficiency of packet filtering is improved.

The invention discloses a network high-speed traffic acquisition method, system and device based on a clouded environment, and relates to the technical field of network communication. According to the invention, a clouded environment is created; a two-stage clouded environment capacity expansion and contraction strategy is constructed by using an optimized FCN network high-speed flow prediction model and a real-time load index, and pre-allocation and accurate adjustment of resources are realized; the optimal solution of the model learning rate is dynamically searched by introducing an optimization algorithm, the session continuity is guaranteed by adopting a consistent Hash algorithm, and the load balance degree and the processing throughput are improved in combination with a three-level dynamic filtering rule and a lightweight DPI (Deep Packet Inspection) technology; due to an annular buffer management strategy and a Kafka message queue synchronization mechanism, the key data loss rate and the data synchronization delay are reduced, and the requirements of real-time analysis and long-term storage in a high-speed network scene are met; according to the method, the problem of insufficient resource elasticity of a clouded environment is effectively solved, the resource supply response speed is improved, and the cost and the prediction error rate are reduced.

The invention provides a data packet real-time filtering method and device for a vehicle-mounted host firewall, and relates to the technical field of vehicle-mounted host firewall application, and the method comprises the steps: receiving a preset rule set sent by an upper computer; monitoring the current vehicle state in real time, determining a first filtering rule of the current network traffic data packet from a preset rule set based on the first vehicle state of the current vehicle, and analyzing and filtering each protocol layer data of the current network traffic data packet; if the current vehicle is switched from the first vehicle state to a second vehicle state, determining an application layer data filtering rule and / or a transmission layer data filtering rule corresponding to the second vehicle state from a preset rule set, and updating the first filtering rule to generate a second filtering rule, and analyzing and filtering each protocol layer data of the current network flow data packet based on the second filtering rule. The technical problem that a vehicle-mounted host firewall in the prior art cannot enable the filtered data packet to accurately meet the requirements of a complex vehicle application scene is solved.

A content distribution and optimization system that receives a plurality of event traffic bursts, generated by a first client computing device, in a first pod from a partition of a messaging bus. Messaging bus is partitioned based on a device identifier (ID) of the first client computing device and comprises a plurality of application launch timestamps. A filtering rule is configured for the device ID of the first client computing device for checking a rate limit of each event traffic burst. First set of event traffic bursts is blocked based on number of events exceeding a threshold value of rate limit of an event traffic burst generated by the first client computing device until a new fixed window is assigned. Event traffic communicated to a metrics aggregation controller is limited to pre-defined rate for the first client computing device. Enrichment of remaining second set of event traffic bursts is performed.

A source content processor receives content from a crawler and calls a text mining engine. The text mining engine mines the content and provides metadata about the content. The source content processor applies a source content filtering rule to the content utilizing the metadata from the text mining engine. The source content filtering rule is previously built based on at least one of a named entity, a category, or a sentiment. The source content processor determines whether to persist the content according to a result from applying the source content filtering rule to the content and either stores the content in a data store or deletes the contents from the data ingestion pipeline such that the content is not persisted anywhere. Embodiments disclosed herein can significantly reduce the amount of irrelevant content through the data ingestion pipeline, prior to data persistence.

The present disclosure provides a method, device and electronic device for generating advertisement filtering rules, which relate to the fields of artificial intelligence technology, and in particular to the fields of big data and browser technology. The method comprises: obtaining at least one image corresponding to each of a plurality of web pages; determining the location information of the advertisement in each web page according to at least one image corresponding to each web page; triggering an operation instruction for the advertisement according to the location information, and obtaining the information of the element node corresponding to the advertisement based on the operation instruction; generating advertisement filtering rules according to the number of appearances of the advertisement in a plurality of web pages and the information of the element node corresponding to the advertisement. The method improves the efficiency and accuracy of generating advertisement filtering rules.

The invention relates to the technical field of signal processing, and provides a multi-frequency bio-electricity signal anti-interference method and device, equipment and a storage medium. The multi-frequency bio-electricity signal anti-interference method comprises the steps that multi-frequency-band bio-electricity signals of multiple channels are synchronously collected; based on a time-frequency analysis rule, performing frequency domain decomposition on the multi-band bio-electricity signal of each channel, and extracting an interference frequency component; according to the identified interference frequency component, denoising the main frequency band signal of each channel by using a collaborative adaptive filtering rule, and dynamically adjusting a filtering parameter based on a reference characteristic of a non-interference signal in an auxiliary frequency band; and performing multi-scale fusion on the features of the filtered main frequency band signal and the features reserved in the auxiliary frequency band, and performing recovery through a weighted reconstruction rule to obtain a target bio-electricity signal. The invention aims to improve the reliability and stability of the multi-frequency bio-electricity signal.

Provided are a data filtering method and apparatus for a generative artificial intelligence model, a device, and a medium. The method comprises: determining a time point for filtering data of a generative artificial intelligence model; when the time point is reached, constructing a first knowledge graph on the basis of the data; querying the first knowledge graph in a second knowledge graph, wherein the second knowledge graph comprises a third knowledge graph constructed on the basis of valid data and a fourth knowledge graph constructed on the basis of invalid data; and filtering the data on the basis of the query result and a filtering rule, wherein the filtering rule is related to the third knowledge graph and / or the fourth knowledge graph. On the basis of knowledge graphs, data of a generative artificial intelligence model can be accurately filtered. In addition, the data is filtered in pre-training and model fine-tuning stages, preventing in advance the model from generating invalid data. The data is filtered in a model output stage, improving the security of the data.

The invention discloses a short message data intelligent management system and method based on big data, and relates to the technical field of short message data management.The management method comprises the following steps that after user authorization, the filtering process of each short message received by communication equipment is recorded, and a corresponding filtering record is generated; performing feature extraction on the set filtering rule, and performing category division on the short messages corresponding to the filtering records; based on the presentation condition of each feature in the filtering record, establishing an exception assessment rule to assess the filtering condition; capturing each short message browsing behavior of the user, summarizing each feature of short messages browsed by the user, and correcting the filtering rule; and on the basis of the corrected filtering rule, extracting corresponding characteristics of the received real-time short message, carrying out abnormity evaluation on the real-time short message, and judging whether the real-time short message is pushed to the user or not.

The invention discloses a set top box automatic testing method and system based on big data, and mainly relates to the technical field of set top box automatic testing. Comprising the steps that log collection is conducted through a built-in lightweight agent of an equipment system, and log data information is extracted; performing data cleaning on the extracted data information through a filtering rule to form a data set; performing K-means clustering on the data set subjected to data cleaning to extract a behavior pattern, and constructing a defect prediction model; the extracted log data information is divided into a training set and a verification set, and a defect prediction model is used for training; and generating a core test case and a boundary test case. The method has the beneficial effects that the test strategy can be dynamically optimized while the test case better fits the real use scene of the user.

The embodiment of the invention provides an unknown cross-site script security detection method and device generated based on a test script, and intelligent construction of the test script is realized through innovatively constructing a script generation mechanism driven by a Markov chain and through atomic element sequence analysis and a random walk strategy. And designing a DOM tree difference-based filtering analysis mechanism, and establishing a filtering rule identification strategy in combination with multi-dimensional mark extraction and node positioning. And a matrix iterative optimization mechanism is introduced, and self-adaptive optimization of the test script is realized through dynamic updating and convergence calculation of a state transition matrix. According to the method, the defects of the traditional technology in the aspects of script generation, filtering analysis, optimization adjustment and the like are effectively overcome, and the unknown cross-site script detection effect is remarkably improved.

The invention discloses a data processing method and device, electronic equipment and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring vehicle data, and loading a data filtering rule in a database to a cache; under the condition that it is determined that the data filtering rules in the database are updated, a weight coefficient corresponding to each updated data filtering rule is determined based on a preset configuration file, and the preset configuration file comprises a plurality of data filtering rules and the weight coefficient corresponding to each data filtering rule; determining a target weight coefficient based on the weight coefficient corresponding to each updated data filtering rule; and updating a data filtering rule in the cache based on the target weight coefficient, and carrying out data filtering operation on the vehicle data according to the data filtering rule in the cache. Therefore, the reading and writing times of the database can be remarkably reduced, the consistency of the cache data and the database data can be effectively kept, data processing delay and message blocking are avoided to a certain extent, and the stability of a service system is improved.