755 results about "Data content" patented technology

The invention relates to the technical field of integration of artificial intelligence security and network security, and discloses an AI dynamic security transmission system based on an SASE framework, which realizes security access control based on AI dynamic identity verification through an SASE integration access module, acquires and predicts network performance change in real time by using a network state sensing module, and transmits the network performance change to a network server. Equipment, environment and data content are subjected to multi-dimensional analysis by means of a security risk assessment module, a quantitative risk score is generated, and a transmission protocol, parameters and encryption strength are dynamically adjusted according to a network state and the risk score by means of a dynamic transmission optimization module and a self-adaptive encryption module; the problem that safety protection and transmission efficiency are difficult to cooperate in a traditional architecture is effectively solved, low-delay and high-reliability data transmission service can be provided for AI application in a complex network environment, meanwhile, self-adaptive dynamic protection of the whole data transmission process is achieved, and data safety is comprehensively guaranteed.

The invention discloses a method and system for encrypting sensitive data based on a large model, relates to the field of data security, and solves the problem that a traditional fixed encryption strategy lacks dynamic adaptability. An encryption strategy container is generated through a data evaluation server, an evaluation module analyzes data content characteristics through a large model, a multi-dimensional sensitivity evaluation matrix and a use scene-risk level association model are established, and meanwhile the performance of an encryption module is tested; calculating a risk level according to a data sensitivity weight and a scene risk coefficient, triggering an alarm if the risk level exceeds a threshold value, otherwise, comparing a standard scene risk model to adjust encryption algorithm parameters, and generating a scene self-adaptive dynamic encryption strategy in combination with an encryption efficiency curve after performance compensation; and finally, the encryption gateway executes encryption. The method can improve the resource utilization rate through dynamic adaptive encryption, guarantees the stable efficiency through real-time performance compensation, improves the perspectiveness through intelligent prediction, reduces the safety risk and management cost through whole-process protection, and is suitable for a multi-industry sensitive data protection method.

The invention discloses a private domain data-based user portrait generation method and a private domain data-based content generation and touch method, and relates to the technical field of big data processing and pushing. Analyzing user behavior characteristics and interest preferences based on the collected data; marking static tags for the corresponding users based on the basic attributes; according to the behavior characteristics and interest preferences, constructing a primary dynamic tag; through user behavior data collected in real time, a time decay weighting algorithm is adopted to improve recent behavior weight and filter abnormal click data, a time sequence cross attention network is adopted to model a behavior feature sequence, interest preference and probability are output, and a dynamic threshold value is set to trigger dynamic label updating; and if the key behavior data of the user is collected, recalculating the dynamic tag based on the key behavior data and performing full-amount refreshing. According to the invention, a data-content-touch real-time linkage closed-loop system is constructed.

The invention relates to the technical field of resource matching, and discloses a cross-platform e-commerce resource dynamic matching search method, which comprises the following steps: carrying out real-time analysis on commodity description information from different e-commerce platforms, extracting a core attribute of a commodity and generating a unified semantic representation; when cross-platform data conflicts occur, a conflict resolution strategy is dynamically generated, and the conflict resolution strategy is executed by a local preprocessing module; acquiring data content after conflict resolution, selecting a target edge node based on the data content in combination with user geographical location information, and dynamically configuring a cache data set of the target edge node; and generating corresponding multi-dimensional matching features based on user intention information in a natural query language in combination with the commodity data in the configured cache, determining a candidate commodity set and a corresponding search result based on the multi-dimensional matching features, obtaining feedback information of the user on the search result, and updating the intention analysis model and the matching strategy based on the feedback information. According to the invention, efficient cross-platform resource matching can be realized.

The invention relates to the field of quantum storage and cloud computing fusion, and discloses a big data distributed storage method and system based on cloud computing, and the method comprises the steps: revealing a data intrinsic geometric structure through manifold embedding, and generating a manifold coordinate; secondly, constructing an Ising physical model based on the geometric structure, and solving a model ground state through quantum annealing to determine an optimal data dynamic fragmentation scheme; thirdly, homomorphic encryption is carried out on the data fragments, a Lie group optimization algorithm is used for solving on a special orthogonal group manifold, and a resource mapping matrix considering safety and efficiency is generated; and finally, instructing a fragmentation scheme, constructing a transmission tensor load fusing manifold information, data content and security mapping for each fragment, and optimizing transmission configuration. According to the method, multiple frontier technologies are fused, dynamic fragmentation of data structure sensing and safe and efficient resource mapping are achieved, and the overall performance and safety of the system are remarkably improved.

The invention discloses a data analysis processing method and system based on multi-source data fusion, and relates to the technical field of data analysis fusion processing. Comprising the following steps: data acquisition and preprocessing: acquiring multi-source data, including user behavior data, content data and social data, related to APP pushing and cultural transmission from a plurality of data sources such as social software and an internet platform, after acquisition, preprocessing the multi-source data, generating preprocessed data, and establishing a dynamic credibility evaluation model; according to the method, the dynamic credibility evaluation model is established to distribute the weight for the data source, so that the interference of low-credibility data on the analysis result is avoided, and the information analysis of the user interest intensity, the content credibility and the cultural value based on the fused data is more accurate; therefore, a more reliable basis is provided for making an APP push strategy and a cultural transmission scheme.

The invention discloses a dynamic privacy protection closed-loop control method and system for mobile edge crowd sensing. According to the method, information related to a communication channel and data content is obtained through risk perception, and a multi-dimensional comprehensive privacy risk score is calculated; then, dynamically determining a value of a differential privacy budget epsilon according to the risk score by utilizing a reinforcement learning algorithm in a strategy decision-making stage; then, performing noise addition disturbance on crowd sensing data according to the epsilon in a privacy protection execution stage so as to realize a preset privacy protection level; then, the privacy leakage risk and the data validity of the disturbed data are evaluated in the effect verification stage, and an evaluation result is obtained; and finally, privacy control strategy parameters are adjusted according to an evaluation result in a feedback optimization stage, and feedback is applied to a risk perception and decision process of a next cycle, so that closed-loop control is formed, and a privacy protection effect is continuously optimized. According to the method, the user data privacy security can be improved, and the data availability and the energy consumption efficiency are both considered.

The invention relates to the technical field of data transmission optimization, in particular to a low-power-consumption data transmission optimization system and method for a smart watch. According to the method, the data transmission strategy is dynamically adjusted by combining the user behavior state, the data content characteristics and the system operation parameters. The system firstly senses the wearing state, interaction frequency and equipment resource information of a user, evaluates the priority of to-be-transmitted data, predicts the short-time attention probability of the user based on the behavior trend, and calculates the cognitive perception index of the data. And further comprehensively considering energy consumption, cognitive risk and resource occupation through a scheduling cost function, selecting an optimal transmission mode, and executing instant uploading, delayed caching, compression processing or communication protocol switching operation at an equipment end. According to the scheme, the data redundancy transmission frequency can be effectively reduced, the timeliness of key data is ensured, the overall energy efficiency of the system is remarkably improved, and the method is suitable for the smart watches in various dynamic use scenes.

The invention discloses an encrypted data transmission authentication system based on a security edge gateway, which belongs to the technical field of encrypted transmission, and specifically comprises an edge gateway cluster which is used for collecting traffic operation data in real time and comprises a roadside edge gateway node and a vehicle-mounted edge gateway node; the dynamic trust evaluation model is used for generating a real-time trust evaluation value according to the traffic operation data; mapping an encryption algorithm strength grade according to the trust evaluation value; the closed-loop feedback verification unit is used for performing byte-level comparison on the decrypted data content and the original data content transmitted by the transmitting end, and updating parameters of a dynamic trust evaluation model according to a comparison result; the double-track authentication unit is used for automatically switching to an emergency rapid authentication channel when an emergent traffic event occurs, and automatically switching to a standard authentication channel when the traffic event is relieved; according to the invention, intelligent dynamic balance between the security protection strength and the communication efficiency is realized.

The invention provides a heterogeneous data stream real-time automatic cleaning and correcting method based on a dynamic rule engine, and relates to the technical field of data processing, and the method comprises the steps: accessing a multi-source heterogeneous data stream; loading a predefined dynamic cleaning rule set to a rule engine; monitoring an input data stream in real time, analyzing data content in parallel through a rule engine, and triggering a cleaning action; dynamically generating a correction operation instruction according to a rule matching result; a data credibility weight factor and a correction utility attenuation coefficient are introduced, and a cleaning strategy is dynamically adjusted; and outputting the cleaned standardized data stream and recording a correction log. Through the dynamic rule engine and the intelligent algorithm, flexible adjustment and real-time processing of the heterogeneous data stream cleaning rule are realized, the efficiency and accuracy of data cleaning are improved, and the problems of insufficient rule flexibility, low processing efficiency and difficulty in ensuring data accuracy in the prior art are solved.

The invention discloses a virtual microblog comment generation framework based on a large language model agent. The virtual microblog comment generation framework comprises a user feature modeling module, a behavior modeling module, an information recommendation and random topic module and a user personality evolution module. An intelligent agent is constructed by defining a five-element characteristic system of gender, education degree and the like, and comment generation is controlled by utilizing a prompt template in combination with emotional, standing and irony elements; on the basis of a recommendation system technology and random topic setting, microblog information flow and real-time discussion are simulated; influences of information on users are reflected by means of a personalized evolution mechanism. All the modules operate cooperatively, and large-scale and high-quality Chinese public opinion data can be generated autonomously in real time. The method has the beneficial effects that the data bottleneck is broken through; the data scarcity problem is solved; the data content is updated; improving the model performance: enhancing the generalization ability of the model, and providing diversified training data; a real social scene is simulated; multi-dimensional user simulation is carried out, and a platform function mechanism is simulated; and multi-field research is assisted, and public opinion analysis tasks and service sociology research are supported.

The invention relates to the field of computers, and provides a report generation method and device, equipment and a storage medium. The method comprises the following steps: analyzing a target report template uploaded by using an object, and obtaining each piece of to-be-extracted data and the position of the to-be-extracted data; in response to a data extraction configuration operation triggered by the use object, configuring a data source for each piece of data to be extracted; and respectively extracting target data contents of the to-be-extracted data from the corresponding data sources, and filling the corresponding positions of the target report template with the target data contents to generate a service report. The automatic and intelligent report filling mode is adopted, so that the human input is remarkably reduced, the manual writing time is greatly saved, the high-quality, standardized and normalized business report can be quickly generated under the condition of extremely little manual intervention, and the professional report generation efficiency is greatly improved. The innovative mode effectively solves the problem of excessive manpower resource consumption in the traditional report writing process, and reduces the operation cost of enterprises.

The invention discloses a data transaction security assessment method and system, and relates to the technical field of data security and intelligent assessment. The method comprises the steps of performing feature analysis on a data field, determining a sensitivity weight and generating a sensitivity vector; the fields are graded according to the sensitivity vectors, and dynamic adjustment is carried out in combination with transaction related information to obtain a grading result; calculating a data content risk, a field association risk, and a transaction environment risk based on the sensitivity feature set; determining a weight according to a transaction scene, and weighting various risks to obtain a comprehensive score; and judging the risk level according to the comprehensive score and a threshold value dynamically determined based on historical data. According to the invention, through hierarchical sensitivity modeling and dynamic risk calculation, fine-grained security assessment of different types and sensitivity data is realized, and the risk result can be adaptively adjusted along with changes of data contents, transmission paths and transaction environments, so that the accuracy, real-time performance and scene adaptability of assessment are improved, and the risk assessment efficiency is improved. The defects of a static evaluation method in the prior art are overcome.

The invention discloses an on-chain and off-chain collaborative interaction system based on a block chain, and the system comprises a data structure module which is used for designing a composite data structure containing metadata, data content, a hash value and a timestamp, and employs a Merkle tree to manage data; the distributed storage and transmission module is used for storing data under the chain by adopting a distributed file system, storing key data on the chain by using a block chain, and designing a secure transmission protocol; by means of the Merkle tree and Hash verification, data integrity can be quickly and accurately verified, tampering can be perceived, a distributed storage and transmission technology and a two-way synchronization strategy can be designed, on-chain and off-chain efficient collaboration is achieved, data processing efficiency and reliability are improved, data security privacy is guaranteed by means of block chain characteristics and encryption, digital signature and other technologies, and the method is suitable for large-scale popularization and application. Distributed storage and a P2P network facilitate node and capability expansion to adapt to data growth, an intelligent contract is introduced, online and offline data collaborative automatic management is achieved, risks are reduced, and efficiency is improved.

The invention relates to the technical field of industrial measurement and control, in particular to a multi-source data fusion system operation monitoring system which comprises a jump behavior recognition module, a confidence coefficient screening module, a behavior consistency extraction module, a power recovery anomaly detection module and an operation state monitoring output module. According to the method, the sudden change trend in the current and voltage signals of the operation equipment is extracted, the response dislocation condition between the signals is combined, the behavior change of the equipment can be accurately described, potential abnormal fragments are identified, the signal fragments are screened by means of the multi-dimensional confidence factor, and low-reliability data content is removed; the method comprises the following steps: establishing a characteristic time section with representativeness through time interlacing characteristics between triggering behaviors and behavior type consistency judgment, and realizing accurate marking of abnormal behaviors in a power recovery process of equipment by combining trend delay and fluctuation amplitude change of a power signal in a voltage rising process.

The invention discloses an industrial data standard detection method based on a large model technology, and the method comprises the steps: 1, carrying out the definition of data standards, including a data content standard, a data format standard, a metadata standard, a data quality standard, a data exchange standard, a data security and privacy standard, and an industry and field specific standard; 2, performing large model knowledge enhancement, including general data standard integration, static standard rule scheme injection, dynamic semantic analysis detection scheme injection, data blood relationship detection scheme injection and composite detection mechanism fusion injection; and step 3, performing data standard detection, including data standard formatting and data standard automatic detection. According to the method disclosed by the invention, remarkable effect improvement is realized in the aspects of coverage rate detection, real-time performance, compliance interpretation capability, domain knowledge deep embedding, system management intelligence and the like, and a new generation of basic technical facilities is provided for industrial internet data management.

The invention relates to the field of customs document text feature recognition, in particular to a deep learning-based customs document text feature recognition method, which comprises the following steps of: preprocessing a real-time customs document text to obtain customs document text features; establishing a customs document text classification analysis model based on deep learning according to the customs document text features; and performing feedback adjustment processing by using the customs document text classification analysis model to obtain a customs document text feature recognition result, and establishing a dynamic threshold judgment system by considering multi-dimensional features such as data types, data capacity, text content, timestamps and historical data at the same time, so that the abnormal document recognition accuracy is improved, and the user experience is improved. Meanwhile, a cross validation mechanism of the data content classification model and the data content analysis model reduces the omission ratio of high-risk receipts in the test, and effectively solves the problem of cold start of training data.

The invention discloses a zero-configuration knowledge graph construction method, equipment and a medium, belongs to the technical field of knowledge graphs, and aims to solve the technical problem of how to overcome the hard coding defect in traditional knowledge graph construction, realize a more flexible construction mode with lower difficulty in use, further realize data source entity association and semantic fusion and improve the knowledge graph construction efficiency. According to the technical scheme, field name semantic analysis and data content analysis are conducted through a dynamic semantic analysis algorithm, and intelligent database deep analysis is achieved; the same entities in the multiple tables are automatically recognized and merged through a cross-table entity intelligent merging algorithm, and multi-table collaborative intelligent search is achieved; constructing an intelligent knowledge graph: automatically selecting an optimal construction strategy through a multi-strategy relation construction engine according to keyword role features, and independently constructing a local knowledge graph for each data table; and optimizing and intelligently exporting the knowledge graph.

The invention discloses a smart city data capitalization-oriented data right confirmation management method and system, and belongs to the technical field of data resource management. The method comprises the following steps: receiving data assets uploaded by a user and carrying out multi-modal preprocessing on data contents to generate a data fingerprint with a unique identifier; counting the proportion of the unconfirmed right data fragments; judging an infringement risk level of the data assets in combination with a risk early warning model; if the unconfirmed right proportion exceeds the dynamically calculated threshold value range or the infringement risk level reaches a preset threshold value, executing an audit interception operation and returning a right confirmation abnormity prompt to the user, and requesting to supplement ownership proof; and embedding a multi-modal fusion watermark into the data assets passing the auditing, and generating a cross-domain verifiable right confirmation voucher. According to the method, the data features are extracted through multi-modal preprocessing to generate the unique data fingerprint, the ownership registration state of the data fingerprint is inquired in combination with the block chain technology, the ownership-confirmed and unconfirmed data fragments are accurately identified, and the problem that the data ownership is difficult to accurately and efficiently identify is solved.

The invention discloses a combined electric appliance supply chain multi-dimensional early warning method and system based on a knowledge graph, and relates to the field of supply chain management, and the method comprises a collection module which is used for collecting the data content of each link of a combined electric appliance supply chain; the construction module is used for receiving the data content acquired by the acquisition module, identifying key entities in the supply chain based on an NER algorithm, determining an association relationship between the key entities through a relationship extraction technology of dependency syntactic analysis and remote supervision, and synchronously extracting attributes of the key entities in combination with an SVM algorithm so as to construct a supply chain knowledge graph model; according to the method, the knowledge graph is constructed, scattered data in the combined electric appliance supply chain are integrated on a unified platform, a comprehensive and transparent supply chain view is provided, and a manager can check the state of each link of the supply chain in real time and find potential problems in time, so that the transparency of the supply chain is effectively improved.

The invention relates to the technical field of smart water meters, in particular to a smart water meter cluster meter reading method and system.The method comprises the steps that to-be-processed data is received, and the to-be-processed data is subjected to type division according to data content to obtain a data classification set; performing data classification extraction on the data classification set in sequence to obtain corresponding processing types, and obtaining a storage address based on the processing types, the storage address corresponding to the data classification set; and storing the data in the data classification set according to the storage address, performing grade division on the data classification set to obtain corresponding processing grades, and generating a processing scheduling scheme according to the processing grades. A processing scheduling scheme of the to-be-processed data is realized, and the data management efficiency of the smart water meter is improved.

Performing charge / showback operations in a large-scale data system by scanning multiple data sources to identify data objects for processing as a unitary group with respect to common characteristics that have an impact on finances within the system. Metadata of the identified data objects are stored in a dynamic dataset that defines a single data access unit for the referenced data objects. The system processes a user query regarding cost allocations, cost forecasts, and resource usage of respective groups within an organization. The query initiates a charge-back or show-back operation that allocates costs associated with each respective usage of resources by a department or cost center, and accesses the referenced data objects through the dataset as a single unit based on data content rather than data location in a file directory of the system.

The invention discloses a main network power transmission line path generation system based on a geographic information system, which comprises a database processing module, the database processing module comprises a data import processor, a data preprocessor and a database, the database import processor is connected with the outside and imports external data into database content, and the database content is stored in the database processing module; the data preprocessor calls the data content of the database and performs primary processing according to the data category or attribute; and the path calculation module calls the data content from the database, and calculates and generates the shortest path under the cost constraint condition according to a set path generation algorithm. According to the method, dual cost calculation of unit attribute cost and moving cost is introduced, a power transmission line path planning model fusing static unit attributes and dynamic moving resistance is established, and on the premise of ensuring ecological compliance and engineering safety, inherent cost of quantified terrain and passage resistance between adjacent grid units are fused, so that the power transmission line path planning precision is improved. And the optimal calculation of the full-path comprehensive cost is realized.

The invention discloses a logic structured data modeling-oriented germination type pre-training method and system, and belongs to the technical field of information. The method comprises the following steps: performing data logic analysis on original data to obtain a structured representation of the original data; performing data germination based on the structured representation to obtain logic structured data x, and obtaining a plurality of data sample pairs {xi-a, xi-b} according to a growth path of the logic structured data x in the data germination process; and completing training of a target model for {xi-a, xi-b} based on the data sample to obtain a germination type pre-training model. According to the method, a logic structure possibly contained in each piece of data is fully mined, and a proper germination mode is applied under the condition that different contexts are given to accurately generate target data contents, so that downstream tasks can be processed more effectively.

The invention provides a security optimization encryption method, system and device for data in a facility agriculture scene and a medium, and belongs to the technical field of agricultural informatization security, and the method comprises the steps: carrying out the dynamic division of security levels of data collected in a facility agriculture environment according to the data source device type, data content sensitivity and real-time requirements; distributing an encryption algorithm for the collected data according to a mapping relation between the security level and the encryption algorithm; secret keys are generated and managed based on an identity encryption mechanism, and then secret key fragmentation storage is carried out in combination with a trusted execution environment; when encryption is needed, whether the current trusted execution environment is safe or not is judged, and when the current trusted execution environment is safe, secret keys of the fragments are recombined, the multi-source heterogeneous data are encrypted through the distributed encryption algorithm, and encrypted data are generated; and carrying out secure transmission on an adaptive communication protocol after packaging the encrypted data. According to the method, the data security level is dynamically divided, the encryption algorithm is flexibly selected, the resource consumption is reduced, and the real-time performance and security are improved.

The invention discloses an air environment monitoring data identification system and method, and belongs to the technical field of environment monitoring, and the method specifically comprises the steps: obtaining air pollution prevention whole process data, and carrying out the Hash processing to generate a data fingerprint; storing the data fragments to a distributed network, and generating a unique content identifier; constructing a Merkel-Partrexia tree in combination with the data fingerprints, the content identifiers and the key metadata to calculate root hash, and performing uplink evidence storage; the consistency of distributed data under the chain is verified based on the on-chain root hash, and the data integrity is ensured through a sampling verification strategy; and the requester applies for an access permission through the smart contract, obtains the data content identifier and the storage node information after permission verification, and accesses a record to be chained for evidence storage. According to the invention, through a cooperative verification mechanism of the Merkel-Parene tree and the block chain, the traceability and tamper resistance of the full life cycle of the data are realized, and the data security and sharing efficiency are improved.

The invention belongs to the technical field of databases, and particularly relates to an LLM-Text2SQL-oriented database table relation exploration method. According to the method, a multi-stage cooperative processing strategy is adopted, database metadata and data content features are integrated, and semantic enhancement and structured completion are performed on original information through a large language model. And on the basis, a potential association candidate set is screened in combination with an algorithm based on feature similarity, multi-dimensional verification and judgment of an association relationship are performed by fusing a predefined rule and a large language model reasoning mechanism, and finally an entity relationship graph supporting interactive editing and iterative optimization is generated. According to the method, end-to-end automatic processing from a heterogeneous database with constraint missing and data integrity impaired to a standardized ER graph is realized, and a solid foundation is laid for remarkably improving the success rate of natural language SQL generation based on a large language model.

A link tracking method and apparatus for an agent, a medium, a device and a program product, relating to the technical field of computers, the method comprising: acquiring link tracking data of the agent in a full life cycle, the link tracking data comprising data content generated in a process from the agent receiving a request to the agent outputting a response result corresponding to the request; and then storing the link tracking data based on the original identifier corresponding to the link tracking data, in response to the query request, determining target link tracking data corresponding to the original identifier carried by the query request from the stored link tracking data, and displaying the target link tracking data, according to the method, intelligent agent debugging, workflow debugging, intelligent agent online use and link tracking in an intelligent agent evaluation stage can be covered, so that full-life-cycle link tracking of the intelligent agent is supported, link information of the intelligent agent in each key link can be comprehensively recorded in detail, and support is provided for optimization of the intelligent agent.

The invention discloses a communication method for realizing a BMS protocol through Bluetooth, and the method comprises the following steps: S1, a connection establishment stage: 1) after a local device establishes a Bluetooth connection with a slave device, the local device constructs a request instruction for reading a version number according to a predefined BMS communication protocol; and 2) periodically issuing the request instruction to the slave equipment in a first preset period through the Bluetooth feature with the notification attribute. According to the method, the communication reliability is improved, the problems of instability and data packet loss of a Bluetooth channel are effectively solved through instruction issuing based on timing polling and a multi-level overtime disconnection mechanism, and it is ensured that instructions and data are reachable in a complex wireless environment; and on the basis of a BMS protocol framework, end-to-end CRC16 verification from'equipment address' to'data content 'is introduced in a data analysis link, damaged or tampered data frames in a transmission process can be accurately identified and discarded, and system processing errors or missing data are fundamentally avoided.

The embodiment of the invention provides an electroencephalogram experiment data processing method and device and electroencephalogram equipment, and relates to the technical field of electroencephalogram equipment. According to the specific implementation scheme, in the process of continuously displaying multiple experimental stimulation contents, electroencephalogram experimental data of an experimented object are collected; acquiring experimental stimulation content to obtain acquired content; determining a content switching time point in the collected content, and generating content identification data based on the content switching time point, the content switching time point representing a time point between two adjacent experimental stimulation contents corresponding to the collected content; and fusing the content identification data with the electroencephalogram experiment data to obtain fused electroencephalogram experiment data. In the scheme, the electroencephalogram equipment can automatically generate the content identification data, and the dependency on the equipment is reduced. Compared with wireless connection, the accuracy of the content identification data can be improved. Besides, stimulation in a specified environment such as a natural environment can be directly collected for experiment without display equipment, so that the application range of the scheme is expanded.