55 results about "Chinese word" patented technology

The invention relates to the technical field of natural language processing, in particular to a foreign trade letter intelligent semantic error correction and business term optimization method and device, and the method comprises the steps: obtaining a target foreign trade letter, and constructing a target corpus; performing Chinese word segmentation and part-of-speech tagging on the target foreign trade letter; performing term optimization based on the word segmentation result and the knowledge graph; identifying the letter title by using a conditional random field model, and converting the letter title into structured data; a Bi-LSTM-CRF model is adopted to carry out risk point detection, including Bi-LSTM coding, feature engineering and Max-pooling technologies, a part-of-speech sequence is obtained through a softmax function and a Viterbi path, and sequence labeling is carried out to obtain a risk point detection result; and finally, performing Chinese error correction based on the word segmentation result after part-of-speech tagging and the knowledge graph. The recognition and correction accuracy of foreign trade terminologies is improved, and communication obstacles caused by nonstandard use of the terminologies are effectively reduced.

This application relates to the field of data processing technology and discloses a method and system for Chinese word segmentation and semantic unit parsing based on rule enhancement. The method includes: constructing a multi-level domain rule base from forced matching rules, pattern template rules, and context constraint rules to generate a set of rule triples; loading the set of rule triples into an AC automaton to linearly scan the input text to obtain a set of candidate segments and trigger word position indices; constructing a candidate directed acyclic graph, and obtaining a structured word segmentation sequence and a pruned candidate pool through dynamic programming after dynamic modulation and fusion scoring; verifying the integrity of downstream slots, and locating backup candidate edges in the pruned candidate pool using gap signals when failure occurs, and obtaining a corrected word segmentation sequence through renegotiation and scoring. This application improves the completeness of professional terminology recognition in professional vertical scenarios and the self-correction capability of cross-domain word segmentation results.

The application provides a Chinese spoken language intention recognition brain-computer interface system based on a sound-meaning integration double model, belongs to the technical field of biomedical engineering, and relates to language brain-computer interface technology. Taking sound-meaning integration as the core, the stereotactic intracranial electroencephalogram (sEEG) technology is adopted to collect neural signals of the brain articulatory motor coding area and the semantic concept organization coding area. The system comprises a voice initiation decoder, a speech decoder, a semantic decoder and a Chinese word speech-semantic fusion synthesizer, the target decoder is constructed by extracting high gamma band features of key brain areas of the frontal lobe (left inferior frontal gyrus, premotor cortex, etc.), the temporal lobe (anterior temporal lobe, dorsolateral temporal lobe, etc.). At the same time, a visual and auditory induction training paradigm is matched, three tasks of listening to sound to group words, looking at words to group words and word association are set, and the subjects are supported to generate words independently. The system effectively solves the homonym and near homonym word ambiguity problem in Chinese spoken language recognition, and provides a precise interactive tool for ALS and other speech disorder patients.

A storage format of Chinese language (“Readable Hanyu Expression” or “RHE”) and the related processing methods and systems. Unlike current Chinese processing methods which directly code Chinese characters into fonts for display, RHE takes an indirect approach by storing Chinese language in the RHE storage format that can be mapped to several display forms including simplified and traditional Chinese characters, Hanyu Pinyin, etc. In the RHE storage format, each Chinese word is stored as an RHE storage element having the format (Syllable+Tone)n+Mark, where n is the number of syllables (Chinese characters) in the word, Syllable represents the pronunciation (without the tone) of the character, Tone represents the tone of the pronunciation, and Mark is a value that differentiates different words having the same pronunciations and tones. Various mapping tables are used to map RHE storage elements to standard Chinese character codes (such as Unicode) and Pinyin expressions.

The invention provides a Chinese spoken language intention recognition brain-computer interface system based on pronunciation-meaning integration double models, belongs to the technical field of biomedical engineering, and relates to a language brain-computer interface technology. Sound-sense integration is taken as a core, and a stereotactic intracranial electroencephalogram (sEEG) technology is adopted to acquire neural signals of a brain phonetic motion coding region and a semantic concept organization coding region. The system comprises a sound production starting decoder, a voice decoder, a semantic decoder and a Chinese word voice-semantic fusion synthesizer, and a target decoder is constructed by extracting high gamma wave band characteristics of key brain regions of frontal lobe (left subfrontal gyrus, anterior cortex of motion and the like) and temporal lobe (anterior temporal lobe, dorsal lateral temporal lobe and the like). Meanwhile, an audio-visual induction training normal form is matched, three tasks of listening word combination, character reading word combination and vocabulary association are set, and subjects are supported to autonomously generate vocabularies. The system effectively solves the problem of ambiguity of homophonous and near-phonetic words in spoken Chinese recognition, and provides an accurate interaction tool for speech disorder patients such as ALS and the like.

The invention discloses a dialect song generation method and device and a dialect song display method and device, and relates to the technical field of computers. The method comprises the steps of obtaining a first Chinese song and Chinese lyrics of the first Chinese song; dialect lyrics of the first Chinese song are generated through a language model according to the Chinese lyrics of the first Chinese song, and the dialect lyrics of the first Chinese song are used for describing semantics of the Chinese lyrics of the first Chinese song in a dialect language expression mode; a first dialect song corresponding to the first Chinese song is generated according to the first Chinese song, the dialect lyrics of the first Chinese song and the dialect pronunciation mapping relation through a song generation model, and the first dialect song is used for singing the first Chinese song through dialects. The dialect pronunciation mapping relation is established by adopting a pronunciation mode of at least one language to mark dialect pronunciation of the Chinese vocabulary. According to the method, a more accurate dialect pronunciation mapping relation is constructed, and the accuracy of dialect pronunciation in the first dialect song is improved.

This invention relates to a big data topic analysis method based on an embedding model. First, the Sentence-BERT model is used to perform sentence embedding representation on preprocessed Chinese text data. Then, the UMAP projection dimensionality reduction algorithm is used to reduce the dimensionality of the embedded vectors. Next, the HDBSCAN clustering algorithm is used to cluster the dimensionality-reduced vectors. Based on the assignment of each Chinese text in the target Chinese dataset to a corresponding topic class, the Chinese words with the highest c-TF-IDF scores are selected to represent each topic class. Finally, the DSG model is used to perform word embedding representation on the topic words, calculating the similarity between different topic words and between different topic classes, thereby detecting the volatility of newly emerging topic classes. The entire scheme design has higher topic consistency and topic diversity, and can detect new hot topics in a timely and accurate manner, providing early warnings.

The application provides a data mode matching method and system for an interface, and belongs to the technical field of mode matching, and comprises the following steps: obtaining preprocessed data modes by preprocessing initial data modes of any two interfaces to be matched; obtaining language attributes of parameter names and parameter descriptions in the preprocessed data modes; if it is determined that the language attributes contain English words, calculating name similarity of the parameter names to obtain a name similarity result; if it is determined that the language attributes contain Chinese words, calculating semantic similarity of the parameter descriptions to obtain a semantic similarity result; and fusing the name similarity result and the semantic similarity result to output a data mode matching result of the any two interfaces to be matched. The application realizes automatic mode matching between heterogeneous mode interfaces provided by different systems, solves the problem that data mode matching between interfaces needs to be manually performed when heterogeneous data is integrated, and thus improves interoperability between systems.

The present application relates to the technical field of electronic digital data processing, and discloses a four-level index pinyin bucket word library generation method, acquires a Chinese word library text, extracts the first Chinese character and the first pinyin of each line of words as a classification key, and generates a triple; the triple is classified into a corresponding pinyin bucket according to the pinyin, the words in the bucket are sorted in descending order of word frequency, an independent Chinese character block is generated for each unique Chinese character, and the words are solidified according to the word length by using a first character multiplexing mechanism; a four-level static index of an initial letter statistical area and a pinyin index area and a Chinese character word index area and a word storage area is sequentially constructed, each index area uses fixed-length entries and absolute offset addressing; a metadata area containing a file length double-semantic field is constructed, a high-frequency-first deterministic truncation is performed on the word library according to a preset threshold, each data area is spliced and a data integrity check value is appended, and an embedded binary word library is generated. The problems of high storage redundancy and uncontrollable memory are solved, and the purposes of deterministic analysis, resource adaptation and high security are achieved.

The application discloses a machine translation software defect detection method based on combined semantics, comprising the following steps: S1, obtaining different Chinese translation sentences of the same English source sentence from different translation software; S2, using a word alignment model to correspond English words in the source sentence with segmented Chinese words in the Chinese translation sentences; S3, using a sentence compression model and a syntactic structure analysis method to obtain a main part and each additional part of the English source sentence respectively and form a sub-sentence set; S4, aligning each part of the English source sentence obtained in the step S3 with the corresponding translation part to obtain aligned translation of the main part and the additional part of the source sentence; and S5, detecting errors, including semantic similarity calculation and synonym checking.

The application belongs to the field of natural language processing in the nuclear power industry, and particularly relates to a professional word segmentation method applied to nuclear power industry corpus, which comprises nuclear power professional vocabulary construction, nuclear power stop word vocabulary construction, nuclear power synonym vocabulary construction, nuclear power same pronoun vocabulary construction, nuclear power field new word recognition, nuclear power field entity automatic recognition, nuclear power field synonym automatic recognition, nuclear power corpus Chinese accurate word segmentation and the like operations. The application has the beneficial effect of completely solving the problem of inaccurate Chinese word segmentation of nuclear power industry corpus, laying a solid foundation for the application of subsequent big data and artificial intelligence in the field of nuclear power natural language processing, and reducing the investment of other practitioners in the field of nuclear power in natural language processing.

The present invention provides a data processing method and system capable of improving efficiency of Chinese vocabulary learning. The method comprises: a data storage unit storing a vocabulary database related to Chinese language learning; segmenting each word into two or more sub-words; binding each sub-word to a balloon graphic, and assigning a color to the balloon; displaying four or more balloons on a client display screen, wherein one sub-word is displayed on each balloon, and the position of the balloon in the screen changes randomly; detecting an instruction for dragging one balloon in the client display screen so that the one balloon at least partially overlaps another balloon; upon detection of said instruction, indicating that phrase matching is performed on the sub-words bound to the selected balloons; and traversing the data storage unit, if there is a corresponding phrase in the data storage unit, indicating that the matching is successful, removing the balloons from the client display screen, and displaying the phrase in a set area of the client display screen, otherwise, retaining the balloons on the client display screen until all balloons in the client display screen are removed.

This invention relates to the field of natural language processing technology and discloses a multilingual word vector weighted alignment method based on orthogonal Protodyakonov analysis. The method includes the following steps: S1: Randomly initialize an orthogonal matrix R, and randomly rotate the Chinese word vectors, i.e., X < -XR; substitute the weight matrix A, calculate the weighted orthogonal transformation matrix W according to the provided weighted Protodyakonov analysis, and obtain the weighted aligned Chinese word vector XW2. The Chinese word vectors are downloaded through a given word vector link to obtain Chinese and English word vectors X and Y. A given alignment dictionary L is used to weight sentiment words, with the goal of weighted alignment from X to Y. The method provided by this invention can perform weighted alignment according to the needs of downstream tasks, further improving the performance of downstream tasks, realizing a shared word vector space, and providing a mathematical proof of the weighted orthogonal Protodyakonov analysis.

1. The name of the design product: graphical user interface for judging translation content of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content of graphical user interface. 4. The picture or photo that best shows the design points: design 2 front view. 5. Design 2 is designated as the basic design. 6. The use of graphical user interface: for judging translation content. The human-computer interaction and change state of graphical user interface: click one Chinese word such as "avalanche" in design 1 front view to enter design 1 interface change state diagram 1; click the English word corresponding to "avalanche" such as "avalanche" in design 1 interface change state diagram 1 to enter design 1 interface change state diagram 2; keep for a preset time such as 1 second to enter design 1 interface change state diagram 3; click one Chinese word such as "apple" in design 1 interface change state diagram 3 to enter design 1 interface change state diagram 4; click the English word corresponding to "apple" such as "apple" in design 1 interface change state diagram 4 to enter design 1 interface change state diagram 5; keep for a preset time such as 1 second to enter design 1 interface change state diagram 6; wait until only the last Chinese word and the last English word are left to enter design 1 interface change state diagram 7; click the Chinese word "beef" in design 1 interface change state diagram 7 to enter design 1 interface change state diagram 8; click the English word "beef" corresponding to "beef" in design 1 interface change state diagram 8 to enter design 1 interface change state diagram 9; keep for a preset time such as 1 second to enter design 1 interface change state diagram 10. Click one Chinese word in the main view of design 2, such as "avalanche", to enter design 2 interface change state diagram 1; click an English word in design 2 interface change state diagram 1 that does not correspond to "avalanche", such as "apple", to enter design 2 interface change state diagram 2; keep for a preset time, such as 1 second, to enter design 2 interface change state diagram 3; click one Chinese word in design 2 interface change state diagram 3, such as "apple", to enter design 2 interface change state diagram 4; click an English word in design 2 interface change state diagram 4 that does not correspond to "apple", such as "mother", to enter design 2 interface change state diagram 5; keep for a preset time, such as 1 second, to enter design 2 interface change state diagram 6; click one Chinese word in design 2 interface change state diagram 6, such as "pencil", to enter design 2 interface change state diagram 7; click an English word in design 2 interface change state diagram 7 that does not correspond to "pencil", such as "mother", to enter design 2 interface change state diagram 8; keep for a preset time, such as 1 second, to enter design 2 interface change state diagram 9; click one Chinese word in design 2 interface change state diagram 9, such as "pencil", to enter design 2 interface change state diagram 10; click an English word "beef" in design 2 interface change state diagram 10 that does not correspond to "pencil" to enter design 2 interface change state diagram 11; keep for a preset time, such as 1 second, to enter design 2 interface change state diagram 12.

The application relates to the field of speech recognition and discloses a vehicle industry term speech recognition method and device and a storage medium. The method comprises the following steps: constructing a Chinese word-phone pronunciation dictionary and a vehicle professional term BPE-phone pronunciation dictionary; training an initialized basic speech recognition model by using Chinese speech data; and migrating the parameter weight from the basic speech recognition model, and training a target speech recognition model by using the Chinese speech data on the migrated model. According to the embodiment of the application, a speech recognition system with good effect can be efficiently trained under the condition that only a small amount of high-quality vehicle professional term speech data set and a large amount of unlabeled vehicle professional term speech data are needed. The finally obtained speech recognition system does not use a pre-training model with excessive parameter quantity, ensures the speed of speech recognition, and reduces the requirement on hardware in actual application.

The application belongs to the technical field of computers, and particularly relates to a kind of automobile accessory name word segmentation method and system.The method comprises: creating a list of accessory names, creating a containment relationship graph, and using the containment relationship graph.The list of accessory names is created by manual annotation, the created list of accessory names is sorted by accessory name length, and a processed accessory name list with an initial state of empty is created;for each accessory name in the sorted list of accessory names, the following operations are performed: finding a containment relationship, generating a directed acyclic graph, setting a weight, finding the optimal path in all paths according to a dynamic programming algorithm, and updating the containment relationship graph.The application uses a containment relationship graph to save the word segmentation results in a graph structure, not only completes Chinese word segmentation, but also saves the knowledge of the automobile accessory field contained in the word segmentation results, provides an important source of knowledge for creating a knowledge graph in the field of automobile accessories, and can improve the accuracy and efficiency of Chinese word segmentation.

The application discloses a Chinese word segmentation method, device and storage medium, and belongs to the technical field of natural language processing. The Chinese word segmentation method comprises the following steps: S1, a second language translation sentence of a to-be-detected sentence is acquired; S2, a Chinese Bert pre-training language model is used to code the to-be-detected sentence, so as to acquire vector representation of semantic information of the whole sentence and a sentence vector representation sequence; S3, a second language Bert pre-training language model is used to code the translation sentence, so as to acquire vector representation of semantic information of the whole sentence; S4, semantic features of the to-be-detected sentence and the translation sentence are fused, so as to acquire a predicted category of each word of the to-be-detected sentence; and S5, the to-be-detected sentence is segmented according to the predicted category, so as to acquire a word segmentation result. The method improves the accuracy of word segmentation, and has a good word segmentation effect on foreign words in particular.

The application relates to a text sensitive word library extraction method, device and equipment based on a neural network model. The method comprises the following steps: constructing a sensitive word library extraction model; the sensitive word library extraction model comprises a self-defined rule algorithm, a character-by-character segmentation algorithm, a Chinese word segmentation algorithm and an N-gram algorithm; the sensitive word library extraction model is pre-trained according to a training data set; the pre-trained sensitive word library extraction model is used for word segmentation extraction and word library quantitative analysis on the text to be extracted; the full-amount word library is subjected to field structure design; the pre-trained sensitive word library extraction model is iteratively trained according to the designed word library; after the sensitive word extraction is carried out by using the trained sensitive word library extraction model, data analysis is carried out according to a word segmentation frequency filtering rule, a word segmentation character quantity filtering rule and a word segmentation type filtering rule, and a sensitive word library is obtained. The method can improve the sensitive word extraction accuracy and efficiency.

The invention belongs to the cross technical field of geographic information science and natural language processing, and particularly discloses an open geological space relation extraction method and system based on a dependency graph, and the method comprises the steps: obtaining a sentence text set according to geological text data, screening sentences at least comprising two space entities from the sentence text set to form a subject-object pair, and obtaining a screened sentence text set; constructing an entity relationship triple, obtaining segmented words, part-of-speech and syntactic analysis, and forming a geological space relationship data set; training an extraction model by using the training and evaluation sample set, wherein the model comprises a context semantic coding module, a dependency graph attention network module and a two-stage triple extraction module; and testing by using the trained extraction model, performing a two-stage prediction process on an input test data set, firstly measuring a relationship and then predicting an entity, and generating a structured triple. The method can overcome Chinese word segmentation errors, effectively captures long-distance dependence, and is suitable for open relation extraction in the geological field.

The invention discloses an intraspinal anesthetic needle puncture virtuality and reality combined teaching system, which relates to the technical field of medical teaching evaluation, and comprises the following steps of: 1, compiling an index definition library, a Chinese word matrix and a report template into a rule net version through unit and dimensional reasoning and equation and interval checking, and carrying out property test; 2, aligning and normalizing the multi-source sequence and the event according to a conversion chain, and packaging into a fact package containing a source, a formula and a unit; 3, generating a rendering plan based on the fact package, preposing word use and display precision, and pre-scoring; 4, constrained generation and reverse checking are carried out, minimum correction is carried out under the condition that a fact numerical value is not changed, and a consistency text and a final consistency score are output; 5, signing and issuing a gating and embedding a pedigree and a signature; in case of data, threshold or template change, calculating a change influence domain, re-rendering the influenced sentences, and outputting differences and auditing; consistency, traceability and verifiability of facts and characters are realized.

This invention provides a method for detecting sensitive Chinese words in few-sample scenarios, relating to the fields of natural language processing and network security technology. The method involves classifying and amplifying Chinese text data in few-sample scenarios to obtain a labeled sensitive word dataset; constructing a branch-transformer mutual information calibration network using feature extraction and context encoder, a branch-transformer mutual information module, a semantic calibration regularization module, and a prediction module; training the branch-transformer mutual information calibration network using the sensitive word dataset; and analyzing the Chinese text data using the trained branch-transformer mutual information calibration network to obtain the Chinese sensitive word detection results. This invention solves the problems of low accuracy and weak generalization ability in the detection of Chinese sensitive words and variants under few-sample conditions in existing technologies.

This invention discloses a hierarchical text anonymization method, system, and storage medium based on syntax trees. The method constructs a syntax tree T based on the semantic relevance between sensitive words in the text to be matched; it performs Chinese word segmentation on the text in the dictionary based on string matching; it then performs sensitive word matching on the segmented word groups using the characteristics of the syntax tree. When node A is matched, A is added to a Map for storage, and the keywords represented by A's child nodes are matched preferentially; finally, the matched sensitive words are anonymized hierarchically. This invention uses a string matching-based word segmentation method to process the text, optimizing the attempted matching positions of the text to be matched; secondly, it uses a syntax tree approach to prioritize matching keywords with strong semantic relevance to already matched keywords, reducing the number of matching attempts and backtracking in group matching, effectively improving the matching efficiency of group matching. The hierarchical anonymization method of this invention can distinguish the sensitivity and confidentiality levels of sensitive words, providing targeted protection while avoiding wasted computational power.

The application discloses a topic classification method based on a hyperbolic graph convolutional network and hierarchical clustering, and belongs to the technical field of text topic classification in natural language processing. The method comprises the following steps: preprocessing microblog text data, including data cleaning, Chinese word segmentation and removal of stop words; and calculating a feature vector by using a TF-IDF method. The preprocessed text data is mapped to a hyperbolic space, information is converted between Euclidean space and hyperbolic space by using exponential mapping and logarithmic mapping, and the hierarchical structure characteristics of the hyperbolic space are retained. The hyperbolic distance between nodes is calculated, and a hierarchical clustering algorithm is combined to capture the relationship in the hierarchical structure data. Similar or related nodes can obtain a higher weight in the information aggregation process of the hyperbolic graph convolutional network, the hierarchical structure of the text data is mined, the hierarchical structure relationship of the microblog text data is captured by training the hyperbolic graph convolutional neural network, and high-quality topic classification is realized by using the trained hyperbolic graph convolutional neural network.

The invention discloses a Braille learning system combining a self-built Chinese word library and word segmentation processing and a working method thereof, the Braille learning system realizes a function of converting Chinese characters into Braille through the self-built Chinese word library and a word segmentation system, and integrates a display module and a voice module to improve operation convenience and use experience. The braille learning system comprises a main control module, a storage module, a communication module, a display module, a braille module, a voice module and an auxiliary module. The core process comprises the steps of reading a text file through a storage module, performing Chinese character word segmentation processing on a text by utilizing a self-established Chinese character lexicon and a word segmentation algorithm, converting Chinese characters after word segmentation into Pinyin, and mapping the Pinyin into Braille according to a Braille conversion rule. Wherein the display module can visually display an operation interface and text content, so that a user can conveniently carry out interactive operation; the voice module can synchronously convert text content into voice to be output, and double reading support of Braille and voice is achieved.

The application discloses a radar-oriented entity relationship joint extraction method, first, Chinese word segmentation and vectorization processing are performed on radar text corpus, then the number of entities in the radar text corpus and the start / stop position of a single entity are acquired based on the word vector, and the entity vector of each entity is calculated; then, the relationship vector between any two entities and the relationship vector based on the attention weight are calculated, the two relationship vectors are spliced and input into a full connection neural network, and finally, the entity relationship is extracted through the full connection neural network, so that the entity relationship about the radar feature is quickly extracted from the radar field sample corpus.

The invention discloses a report quality inspection method and system combining a large model and deep learning, and the method comprises the steps: carrying out the preprocessing of an original report text, including text cleaning, Chinese word segmentation and stop word filtering; performing clause classification prediction on the preprocessed text based on a BERT model, and outputting predicted clauses; comparing the predicted terms with the original report terms; if the predicted terms are consistent with the original report terms, outputting a verification result True; if not, performing deep semantic verification through a large language model, and outputting a final verification result; and standardizing and outputting a verification result. According to the method, the large model and the BERT are combined to check and judge the consistency of the result records and terms in the report, and the deep semantic analysis of the large model and the fast reasoning and judgment advantages of the BERT are combined, so that the accuracy and reasoning efficiency of the overall check and judgment of the algorithm are improved.

This application discloses a method, apparatus, electronic device, and storage medium for translating Chinese terms. The method includes: vector encoding the Chinese term to be translated to obtain historical data query vectors and professional term query vectors; determining a historical data query index based on the historical data query vectors and historical translated data vector indexes, and determining a professional term query index based on the professional term query vectors and professional term vector indexes; determining historical translated data examples based on the historical data query indexes and a historical translated data database, and determining professional term examples based on the professional term query indexes and a professional term database; concatenating the historical translated data examples, professional term examples, and the Chinese term to be translated into a prompt template to obtain a target prompt project; inputting the target prompt project into a target large model for translation, and outputting the term translation result. This application can improve the accuracy and professionalism of term translation and can be widely applied in the field of computer technology.

This invention discloses a power grid transfer verification method based on digital twins, relating to the field of power grid dispatching technology. The method includes the following steps: First, a dual-track isolation architecture of associated and asynchronous coexisting modes is constructed. Data sections are captured and extracted from the associated mode. Then, unstructured dispatching operation text is processed through Chinese word segmentation, stop word removal, normalized object standardization, and action vector extraction to generate a structured underlying operation script matrix. Subsequently, in the asynchronous coexisting mode, single-step dispatching operations are executed line by line according to the script matrix, and topology analysis, electromechanical transients, and dynamic power flow cross-verification are performed after each micro-state switching action. When overload or hidden risks are identified, safety blocking, full-network load rebalancing, rewriting of the original dispatching command control script, and re-verification are executed. This invention can improve the accuracy and closed-loop handling of transfer verification and enhance the consistency of on-site execution without interfering with the monitoring of the physical power grid operation.

The invention relates to the technical field of artificial intelligence and micro-application interaction, in particular to a micro-application interaction method and system based on a single agent, and the method comprises the following steps: the agent receives a user name and a password of a user, opens an interaction interface after completing identity verification, and receives Chinese words input by the user; performing accurate matching of micro-application names on the Chinese word segmentation through a layered forward longest exhaustive search method, if the matching fails, performing fuzzy matching, and determining a target micro-application according to a matching result; providing an action configuration table on demand according to the micro-application name configuration table for a user to select an action name or prompt to input a name, and generating interaction request information; the agent calls the permission knowledge base, and verifies the target micro-application and the operation permission of the corresponding action through permission codes in combination with the user name or the name matching record; after the permission verification is passed, a request is sent to the micro application to trigger function execution, and an execution result is fed back to the user through the intelligent agent.

The application discloses a Chinese joint event extraction method based on dependency analysis, first introduces dependency analysis to construct a syntactic structure and strengthens the depth interaction of information; secondly, three types of edge representations are designed to calculate graph convolution features in order to bridge the inconsistency of words; finally, the cascade error propagation problem of the traditional pipeline method is relieved through joint learning of the event trigger word classification task and the event argument classification task, and the effect of extracting event triggers and arguments from documents is improved. The Chinese joint event extraction model based on dependency analysis integrates syntactic structure information while encoding semantics, enhances the information flow between words, and designs different types of edge representations for the construction of an undirected graph according to the characteristics of Chinese word segmentation. The application enriches semantic feature representation by integrating the syntactic structure knowledge contained in the Chinese text, and effectively improves the effect of sentence-level event extraction by using the joint learning method.