104 results about "Syntactic parsing" patented technology

The invention relates to the field of wisdom education, and particularly discloses a teaching strategy optimization model and grammar error early warning method based on data mining, and the method comprises the following steps: S1, obtaining original code data in a student code library in real time, and preprocessing the original code data to obtain a structured data matrix; s2, for the structured data matrix, generating a grammar parse tree through a grammar parser, positioning error nodes and extracting context features by using a node traversal algorithm, and constructing a single-error multi-dimensional feature vector; meanwhile, an error association rule base is constructed based on historical error data, a causal relationship across error types is identified, and dynamic knowledge graph data is formed. According to the technical scheme, association analysis and deep mining can be carried out on the multi-source learning data, dynamic solution suggestions for student individual errors or group generality errors are formed, and teachers are assisted to quickly adapt to dynamically changing learning requirements of the students.

The invention discloses a code change influence analysis method and device, equipment and a storage medium, and relates to the technical field of software, the method comprises the following steps: performing grammar analysis on a multi-programming language code to obtain a back-end abstract syntax tree and a front-end abstract syntax tree, and converting the back-end abstract syntax tree and the front-end abstract syntax tree into a uniform syntax tree structure through a front-end and back-end calling mapping chain; a cross-language dependency graph is constructed according to the unified syntax tree structure, the cross-language dependency graph is composed of nodes and edges, the nodes represent code entities, and the edges represent dependency relations; and when the code change of the bank business is detected, traversing the cross-language dependency graph through a graph traversal algorithm to obtain a code change influence result. Due to the fact that the back-end abstract syntax tree and the front-end abstract syntax tree of the multi-programming language codes are constructed and connected in series, the perfect cross-language dependency graph is constructed, the front-end link and the rear-end link are connected, cross-language tracking can be achieved when the codes of the banking business are changed, and the influence of code change can be accurately analyzed.

The invention discloses an equipment agent processing program conversion method and device based on cooperation of a large model and a small model. An equipment agent is constructed by analyzing control systems, kinematics structures and process constraint information of a source machine tool and a target machine tool, and line-level instructions are abstracted into system-independent unified semantic representation based on a multi-system numerical control corpus. And performing grammar analysis and semantic mapping on the source program, and generating a conversion task in combination with grammar rules, kinematics accessibility and process security constraints of a target machine tool. A small model is finely adjusted through supervised learning to realize basic generation capability, a large model is introduced as a patch evaluator, candidate results are jointly scored from different dimensions, knowledge migration is realized based on improved near-end strategy optimization, and a small model generation strategy is continuously optimized. And finally, high-quality results are screened through confidence degree sorting, cross-system G / M instruction and multi-axis track generation and verification are completed, and high-precision automatic conversion of numerical control programs is achieved.

The invention discloses an ANTLR4-based multi-manufacturer network equipment configuration analysis method and system, and the method comprises the steps: carrying out the preprocessing of a configuration file; based on a machine learning algorithm of multi-dimensional feature analysis, automatic identification of configuration file manufacturer types is realized; based on the identification result of the manufacturer type, loading an ANTLR4 grammar parser corresponding to the manufacturer type; a lexical analyzer in ANTLR4 realizes lexical analysis on the configuration file through lexical rule definition, a Token classification system and an optimized analysis algorithm; a syntactic analyzer in ANTLR4 constructs an abstract syntax tree according to a lexical analysis result and a syntactic rule defined based on a context-independent grammar; traversing the abstract syntax tree, and extracting key configuration information; and converting the specific configuration format of each manufacturer into a unified standard model. According to the method and the system, network equipment configuration files of different manufacturers can be automatically identified and analyzed, and key configuration information is extracted and converted into a unified model.

The invention discloses a multi-language data analysis-oriented extensible system, method, equipment and medium, and relates to the technical field of multi-language analysis, the multi-language data analysis-oriented extensible system comprises a grammar analysis module used for analyzing a query language and generating a language-specific syntax tree structure after analysis; the grammar adaptation module is used for converting a language-specific grammar tree structure into an abstract grammar tree AST in a uniform format; the abstract syntax tree processing module injects a permission control strategy, a field desensitization rule and an alarm exception expression into the AST; the business processing module is used for executing business-related rule check and label injection; the query plan generation module is used for constructing a logic query path and a corresponding distributed execution scheme; and the task scheduling module issues the distributed execution scheme to the corresponding execution node. According to the method, by constructing a unified multi-language grammar analysis framework and a standardized abstract syntax tree AST representation mechanism, compatibility and fusion of multiple query languages such as SQL, SPL and natural language are achieved.

The invention relates to the technical field of software engineering and information processing, in particular to a semantic verification method and device based on a large model.The method comprises the steps that a source code file and a corresponding software requirement and design document are obtained, code semantic representation is generated based on grammar analysis and static program analysis, and a semantic verification result is obtained; based on text analysis and business flow chart structure identification, generating a design demand semantic representation; respectively inputting the code semantic representation and the design demand semantic representation into a pre-training language large model to generate a code implementation logic description and a design demand logic description; and performing semantic consistency verification on the two types of logic descriptions to obtain a semantic inconsistency result, determining a code position in the source code file based on the semantic inconsistency result, and outputting a scanning report. According to the invention, the automation degree and the rechecking performance of consistency checking of requirements can be improved, and the leak detection and reworking cost can be reduced.

The invention provides a structured query statement generation method and device, equipment, a medium and a program product, and can be applied to the field of artificial intelligence and the field of financial science and technology. The method comprises the steps that in response to a natural language statement input by a user, the natural language statement is analyzed through a natural language processing model, and semantic elements are obtained; performing syntax analysis on the semantic elements to generate an abstract syntax tree; based on the abstract syntax tree, database structure metadata coding is conducted on the natural language statement through a deep learning model, and a first structured query statement is generated; and performing security verification on the first structured query statement to generate a second structured query statement.

The invention discloses a real-time analysis and view editing method and system based on streaming data, and the method comprises the steps: receiving streaming data which comes from a large language model and is organized in an editing protocol format, carrying out the real-time lexical analysis of the streaming data, and decomposing the streaming data into a semantic unit sequence through a semantic pattern recognition technology; performing grammar analysis on the semantic unit sequence, and converting the semantic unit into a structured editing instruction for modifying an existing rendering tree node according to an instruction pattern recognition mechanism and a target object analysis mechanism; converting the structured editing instruction into an atomic instruction sequence executable by a rendering tree editing interface; and modifying the rendering tree in real time according to the atomic instruction sequence and triggering update rendering of the view. According to the method, the content generated by the AI is analyzed in real time by adopting a streaming output mechanism, so that a user can observe the generation process of the view in real time, local redrawing of the view is realized by using an editing protocol, and the view editing efficiency is greatly improved.

The invention relates to a label extraction model training method and device, a vehicle label extraction method and device and electronic equipment, and the method comprises the steps: inputting a current sample vehicle image into a preset multi-modal model, and obtaining a sample description text; performing grammar analysis processing on the sample description text to obtain at least one segmented word, the part-of-speech of the at least one segmented word and the dependency relationship between the at least one segmented word; performing noun merging based on the at least one segmented word, the part of speech of the at least one segmented word and the dependency relationship among the at least one segmented word to obtain a sample description tag; based on a preset filtering word, filtering the sample description label to obtain a real description label; and training a to-be-trained label extraction model based on the current sample vehicle image and the real description label to obtain a label extraction model. According to the embodiment of the invention, the method can meet the multi-dimensional demands of vehicle recognition, is adaptive to a multi-label scene, greatly improves the readability of a vehicle recognition result, and reduces the decision errors.

The invention discloses an agent intention understanding method based on multi-modal information fusion, relates to the technical field of natural language processing, and solves the technical problem that multi-agent intention understanding cannot be realized in a dynamic environment. Voice, text and visual features are mapped to the same hidden space through maximum mean value difference minimization, distribution difference between modes is eliminated, joint features in the hidden space can capture cross-mode complementary information at the same time, and the richness and anti-noise capability of feature expression are enhanced. CRF (Conditional Random Field) is combined with a special dictionary in the scheduling field to carry out candidate set expansion on fuzzy keywords, and specific semantic variants in the field are captured. The optimal grammar of the scheduling instruction is analyzed and decomposed into a feature vector causal relationship pair, and components of an intention and logic dependence of the intention are clarified. A dynamic knowledge graph is constructed based on the causal relationship, probability dependence among parameters is quantized by using a Bayesian network, the causal relationship strength is dynamically adjusted, and environmental changes are adapted.

The invention provides a source database storage process migration method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the grammar analysis of an original storage process in a source database, and generating a corresponding abstract syntax tree; based on a preset rewriting rule set, performing semantic equivalent transformation on the flow control syntax structure in the abstract syntax tree to generate a transformed abstract syntax tree; and generating a target script in a target execution environment from the converted abstract syntax tree, executing the target script in a script running engine, dynamically generating a standard SQL statement corresponding to the business logic defined by the original storage process, and submitting the standard SQL statement to one or more target data platforms for execution. And the business logic of the original storage process is reproduced. By introducing the target script as the intermediate execution layer, the flexibility of the migration scheme is greatly improved, so that the migration scheme is suitable for various big data platforms without the native storage process capability.

The invention relates to an NL2SQL semantic parsing method and device, and the method comprises the steps: inputting a natural language query statement into a business data model, and obtaining a context vector; fusing the context vector with the natural language query statement to obtain a joint semantic vector; decoding the joint semantic vector and the structured feature based on a constraint decoding strategy to obtain an initial SQL statement, and verifying the initial SQL statement through a grammar parser to obtain a target SQL statement; the context vector of the natural language query statement can be more comprehensively captured through the business data model, and the optimal joint semantic modeling is realized through the context vector and the natural language query statement, so that the problems of information bias and redundancy caused by fixed weight or simple splicing are effectively solved; the context features, the structured features of the database and the constraint decoding strategy are dynamically fused, so that complex service logic and anaphora and omission phenomena in the long dialogue context can be better understood.

The invention discloses a language learning evaluation method based on a deep learning algorithm, and relates to the technical field of language processing, and the method comprises the steps: receiving a voice signal and original text content, constructing a noisy voice sample through an adversarial disturbance generator, inputting a pre-trained voice recognition model, and outputting a voice recognition text and an anti-noise confidence score; constructing a context semantic graph in the semantic analysis path, generating an edge attention weight, calculating a semantic coherence index, and matching a predefined grammar rule base in the activated grammar analysis path to generate a grammar error tag; and dynamically generating feedback content based on the multi-dimensional evaluation matrix, and updating a preset corresponding threshold value and a rule base weight according to the adoption of the user on the feedback content. According to the method, collaborative quantitative analysis of pronunciation, semantics and grammar problems is realized by constructing a multi-dimensional evaluation matrix of an anti-noise confidence score, a semantic coherence index and a grammar error tag.

The invention relates to the technical field of SQL (Structured Query Language) grammar conversion, and provides a general SQL grammar conversion method, device and equipment and a medium, the method comprises the following steps: performing lexical analysis on a source end SQL statement to obtain a lexical unit set; based on the type features and semantic attributes of the lexical unit set, determining parser combiners, and constructing a specific parser by infinitely combining the parser combiners; the specific resolver is used for conducting grammar analysis on the lexical unit set, a general abstract syntax tree is constructed through a mapping assembly, and nodes of the general abstract syntax tree correspond to the specific resolver one to one; and traversing the general abstract syntax tree, and generating a target end SQL statement according to an SQL syntax rule of a target end database. Through the technical scheme, any complex source end SQL can be accurately converted into the target end SQL.

A dialogue-based artificial intelligence system for interaction management in digital commerce, consisting of: a housing that encloses an arrangement of interconnected printed circuit boards; a conversation processing unit arranged on a first circuit board, comprising a syntactic parsing processor for generating hierarchical parse structures from user input texts, a semantic embedding processor for generating high-dimensional semantic vectors from the parsed structures, and a dialogue state calculation circuit for managing a multi-level conversation memory using clocked recurrent memory buffers; a retrieval augmentation unit arranged on a second circuit board, comprising a vector indexing processor for storing and retrieving domain-specific embedding vectors, a similarity calculation processor for calculating cosine-based semantic distances between the semantic vectors and vectors stored in a knowledge store, and a document reconstruction structure for merging retrieved text segments into a unified context representation; a generative response unit arranged on a third circuit board, comprising a transformer execution processor for executing a quantized transformer architecture for natural language generation, a context fusion circuit for merging the unified context representation with the semantic vectors to generate response conditioning data, and a hallucination suppression circuit for comparing the generated text with retrieved text segments and attenuating content divergence beyond a predetermined semantic threshold; a domain integrity check unit that is communicatively connected to the generative response unit, wherein the domain integrity check unit includes a regulatory restriction store that stores domain-driven rules, and a conformance assessment processor configured to check generated responses for conformance with the domain-driven rules, blocking non-conforming segments or replacing them using verified text content from the retrieval extension unit; a knowledge storage array comprising at least one static domain repository for storing commercial specifications, regulatory guidelines, product descriptions, and domain documents, a dynamic interaction buffer for storing anonymized conversation state data, and a vector storage partition for storing embedding vectors that can be retrieved by the vector indexing processor; and a multi-interaction device consisting of a touchscreen panel, an array microphone, a speaker structure and a contactless communication interface, each configured to receive multimodal user inputs or generate multimodal system outputs.

A system and method for translating sign language utterances into a target language, including: receiving motion capture data; producing phonemes / sign fragments from the received motion capture data; producing a plurality of sign sequences from the phonemes / sign fragments; parsing these sign sequences to produce grammatically parsed sign utterances; translating the grammatically parsed sign utterances into grammatical representations in the target language; and generating output utterances in the target language based upon the grammatical representations.

The invention provides a hybrid computing task classification method and device, equipment and a medium, and the method comprises the steps: carrying out the grammar analysis of an input hybrid computing code, generating a tree structure reflecting a code structure, and extracting subtask units and unit information in the hybrid computing code based on the tree structure; extracting feature words of the unit information according to the unit information; obtaining a subtask type of a predefined hybrid computing task and a corresponding keyword; and respectively mapping the keywords and the feature words into semantic vectors, and calculating semantic similarity to determine the subtask type of the subtask unit. The tree structure is obtained through the abstract syntax tree algorithm, so that the hybrid computing code is analyzed, the function definition and the dependency relationship thereof are accurately extracted, and subjectivity and errors possibly brought by manual intervention are avoided.

The invention belongs to the technical field of industrial dynamic formula execution, and discloses an analysis-free high-availability and high-performance formula execution method. The method comprises the following steps: S1, formula extraction and function body construction: receiving a calculation formula input by a user, and taking the calculation formula as a function body core calculation logic; s2, function packaging: adding a function head and a return value statement for a function body, and constructing a complete function definition character string; wherein the function head comprises a function name and a parameter list; and S3, function persistence and dynamic import execution: writing a function character string into an independent Python module file, and calling and executing through a dynamic import mechanism. According to the method, function packaging is adopted, the repeated lexical analysis and grammar analysis process which must be carried out when a traditional event () method is executed each time is eliminated, and the problems that a formula is forcibly required to only comprise functions of input parameters, calculation expressions and return values, and the bottleneck of industrial real-time application and the fragility of a whole framework are solved.

This invention discloses an automated rule engine execution system and method for communication events, belonging to the field of communication technology. The system includes: collecting multi-source heterogeneous communication events; obtaining standard communication event objects through a dedicated rule meta-model for each communication event; loading a rule set; generating an abstract syntax tree through syntax parsing and pre-compilation; constructing a rule dependency graph and performing intersection and mutual exclusion detection to form a scheduling strategy containing priority, mutual exclusion whitelists, and execution order; locating a subset of candidate rules based on system context; determining the target rule through condition matching; encapsulating automated operations into atomic action units; and executing them concurrently or sequentially according to orchestration logic; simultaneously generating a unique execution trace ID to record the entire link log; monitoring anomalies in real time; triggering a circuit breaker if the anomaly rate exceeds the limit or execution times out; taking down abnormal rules and demoting their execution; evaluating the rule effectiveness and providing optimization suggestions after the session ends; this invention improves the efficiency of communication event processing and the stability of rule execution, ensuring reliable system operation.

A user specifies a natural language command to a device. Software on the device generates contextual metadata about the user interface of the device, such as data about all visible elements of the user interface, and sends the contextual metadata along with the natural language command to a natural language understanding engine. The natural language understanding engine parses the natural language query using a stored grammar (e.g., a grammar provided by a maker of the device) and as a result of the parsing identifies information about the command (e.g., the user interface elements referenced by the command) and provides that information to the device. The device uses that provided information to respond to the command.

The invention discloses an ancient modern text machine translation method based on deep learning, and belongs to the technical field of natural language processing. The invention provides a multi-task collaborative optimization framework aiming at the problems of domain knowledge deficiency, frequent word activation, corpus scarcity and the like of an existing neural network model in ancient language translation. Precise domain knowledge injection is realized by constructing a closed ancient language parallel corpus retrieval library and combining historical term alignment and logic chain reasoning; a probability weighted part-of-speech embedding mechanism is adopted, and grammar feature distribution of virtual word ambiguity and word type activity is dynamically fused, so that the grammar analysis robustness is improved; and semantic generation, retrieval alignment and part-of-speech constraint tasks are jointly optimized through a fixed weight strategy. According to the method, the semantic accuracy and the logic continuity of ancient language translation are improved, and extended application of complex ancient language styles is supported. Experimental results verify that the performance of the method is improved in terms of BLEU and ROUGE-L indexes, and efficient technical support is provided for ancient book digitization and cross-time explanation.

The invention discloses a real-time analysis and view rendering method and system based on streaming data, and the method comprises the steps: receiving the streaming data from a large language model, the streaming data being streaming data segments organized in an intercommunication protocol format, and comprising a view segment and a logic segment; performing incremental lexical analysis on the streaming data fragments by adopting a state keeping mechanism to generate a lexical unit sequence; performing real-time grammar analysis on the lexical unit sequence, and converting the lexical units into a structured instruction set through a nested structure analysis mechanism and an attribute pattern recognition engine; converting the structured instruction set into an atomic operation instruction sequence executable by a rendering tree editing interface; and updating the rendering tree in real time according to the atomic operation instruction sequence and generating a rendering view. A user can immediately see the page prototype after the first view segment arrives and dynamically perfect the interface along with successive arrival of the subsequent segments, so that the average waiting time is compressed from the minute level to the second level or even the millisecond level, and the user experience is remarkably improved.

The invention relates to the technical field of databases, and discloses a database grammar compatibility implementation method, which comprises the following steps of: pre-creating a keyword data structure header file of each database, and storing a mapping relationship between a keyword and a keyword Token mark into the keyword data structure header file; creating a grammar analysis file of each database in advance, and introducing the keyword data structure header file into the grammar analysis file; generating a grammar data structure and a keyword data structure according to the keyword data structure header file and the grammar analysis file; compiling the grammar analysis file to generate a code interface; and calling a code interface according to a service demand, and executing the SQL statement through the code interface, the grammar data structure and the keyword data structure to generate an execution result. According to the method, the independent keyword mapping relation and the grammar analysis file are defined for each type of database grammar, the analysis code is generated, and the corresponding grammar analyzer is selected through the configuration item, so that the support for multiple types of database grammar is realized.

The invention relates to the field of computing, and more particularly to methods for automated text processing. A method for classifying a text parse includes inputting into a classification model a text parse containing a main entity and, associated with said main entity, an associated end entity. A text processing method consists in performing the following steps of: identifying a text including three segments, and subsequently identifying said segments; selecting one of the segments for subsequent marking, and marking in this first segment only one part to be parsed; parsing marked parts by semantic-syntactic parsing; extracting from the semantically-syntactically parsed part of the first segment a main entity of said first segment and an associated entity related to the main entity of the first segment, wherein one associated entity is an associated end entity, and extracting from each semantically-syntactically parsed part of a selected second segment and / or a selected third segment one assertion; associating said assertion with the main entity of the first segment. The invention provides for more precise automated generation of a text corpus.

The application discloses a device intelligent agent processing program conversion method and device based on large model and small model cooperation. A device intelligent agent is constructed by analyzing the control system, kinematic structure and process constraint information of the source machine tool and the target machine tool, and the line-level instructions are abstracted into system-independent unified semantic representation based on a multi-system numerical control corpus. The source program is parsed and mapped, and the conversion task is generated in combination with the syntax rules, kinematic accessibility and process safety constraints of the target machine tool. The small model is fine-tuned through supervised learning to realize the basic generation capability, the large model is introduced as a patch evaluator, the candidate results are jointly scored from different dimensions, and the knowledge transfer is realized based on the improved proximal policy optimization to continuously optimize the small model generation strategy. Finally, high-quality results are selected through confidence ranking, cross-system G / M instructions and multi-axis trajectory generation and verification are completed, and high-precision automatic conversion of numerical control programs is realized.

This invention discloses an intensity-aware emotion classification method based on a hierarchical knowledge-enhanced graph neural network. Its key features include: preprocessing the Chinese text to be classified by word segmentation, syntactic parsing, and dependency tree construction; extracting word-level contextual semantic vectors and global sentence representations using a pre-trained language model; identifying sentiment words and degree words in the text, calculating the dynamic sentiment intensity of lemmas, and adaptively expanding the sentiment lexicon; extracting a sentiment knowledge subgraph and aggregating knowledge embeddings, followed by seed-driven pruning to obtain a sparse dependency subgraph; fusing semantic and knowledge features to generate initial node representations, and learning these representations using a hierarchical intensity-aware graph neural network; finally, generating graph-level features through dual-path pooling, fusing global semantics, and outputting the emotion classification result through a multi-task framework. This invention solves the problem of ambiguous emotion classification caused by insufficient modeling of the combined intensity of "degree words + sentiment words" in existing technologies.

The application discloses a data processing method and device, and relates to the technical field of computers. A specific implementation manner of the method comprises the following steps: receiving a definition operation of a syntax rule and a syntax label of an index calculation expression; using the syntax rule to perform lexical analysis and syntax analysis on the index calculation expression, and obtaining a syntax analysis tree; creating an accessor to traverse the syntax analysis tree, and replacing the syntax label in a node in the syntax analysis tree with implementation logic code of the corresponding syntax rule by analyzing the node; determining an index identifier in the index calculation expression, obtaining index data corresponding to the index identifier, processing the index data in sequence according to the position of the node where the implementation logic code is located in the syntax analysis tree, obtaining processing result data, and returning the processing result data. In the implementation manner, for an index definer who can give a data expression, the index definer can efficiently define and efficiently execute a new index without writing redundant codes, and the learning cost and operation cost are relatively low.

The application provides an English text context self-adaption method for cross-cultural communication, comprising: performing word segmentation and grammar analysis on the English text to obtain a preliminary language feature vector; performing similarity matching on the preliminary language feature vector and a cultural knowledge base to determine a cultural attribution label of the preliminary language feature vector; if the cultural attribution label corresponds to multiple cultural meanings, obtaining surrounding sentence information through English text context to obtain an extended context segment; performing emotion analysis on the extended context segment in combination with the cultural attribution label to obtain an emotion tendency label, and filling in missing cultural details after fusion processing of the emotion tendency label and the preliminary language feature vector to obtain an enhanced context framework, completing cross-cultural context representation, realizing dynamic analysis of cultural meanings and accurate labeling of emotion tendencies, significantly improving the accuracy and depth of language understanding in cross-cultural communication, and being suitable for intelligent translation and cultural adaptive interaction in a multilingual environment.

A computer-implemented method of generating a hardware description for configuring a digital electronic circuit 2000 to parse input data comprising a sequence of input tokens against a grammar that de