162 results about "Syntactic parsing" patented technology

The invention provides a cross-database unified management and operation method and system, and relates to the technical field of databases, and the method comprises the following steps: establishing a connection by obtaining database connection information; extracting a database structure by using a dialect strategy processor and mapping the database structure into a unified description; converting the operation instruction into a standard intermediate statement; converting the intermediate statement into a target database execution statement by using a grammar analysis module and a conversion rule; and executing and monitoring in a transaction unit mode. Unified management and operation of different types of databases are realized, the consistency and reliability of database operation are improved, and the development difficulty of cross-database operation is reduced.

The invention discloses a structured remote sensing report generation system, method and device based on a syntax tree and a medium, the system comprises a user input layer, a core processing layer and an output and verification layer, the system receives user demand parameters and input data, automatically analyzes the demand parameters and standardizes the input data; generating a syntax tree structure conforming to industry specifications, and driving the large model to obtain a first draft of a report under the constraint of the syntax tree; and performing automatic verification and manual intervention correction on the first draft of the report to form a professional remote sensing report. According to the method, the multi-dimensional syntax tree architecture is constructed, and the hierarchical syntax analysis algorithm and the domain knowledge graph are combined, so that semantic association of the multi-modal remote sensing data and accurate mapping of terminologies are realized, automatic generation of a long document report meeting remote sensing geographic industry specifications is supported, the structured degree and logic continuity of text generation are improved, and the text generation efficiency is improved. The method can be widely applied to the fields of geological monitoring analysis, environment evaluation report generation and the like.

The invention relates to the technical field of computer software engineering and cross-platform development, in particular to a system for assisting in transplanting Android language to ArkTS (ArkTS) of the swan Mongolia, which comprises a code input module for acquiring Java and Kotlin double-language source codes, an analysis module for analyzing codes by using an improved grammar analysis algorithm, and a storage module for storing the codes. The translation module constructs an abstract syntax tree based on an analysis result and generates an attribute description array, and the generation module generates an ArkTS interface code according to the attribute description array; the distributed computing architecture realizes efficient task scheduling and processing, and the post-processing optimization module guarantees the code quality. Through multi-module cooperation, the probability-rule fusion algorithm, the type dynamic mapping and other technologies, code transplantation can be rapidly and accurately completed, the large project transplantation period is shortened from several weeks to several days, the manual correction cost is reduced, the code conversion accuracy and the system stability are improved, and the development of the wide-gap application ecology is powerfully promoted.

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 an aspect emotion triple extraction method for a large language model annotation data set, and relates to the technical field of natural language processing, and the method comprises the steps: carrying out the initial triple labeling of a standardized text data set, calculating a cognitive bias index based on a labeling reference set, and generating a data set with a bias label; a dynamic attenuation suppression method is adopted to generate a bias mask matrix, exponential mask enhancement is performed on samples exceeding a preset bias threshold value, and bias mask enhancement representation is obtained; inputting the bias mask enhanced representation into a differentiable grammar parser, calculating a grammar dependency matrix by using an attention mechanism, optimizing a topological structure of the grammar dependency matrix in combination with structural entropy loss, and generating a boundary judgment matrix; and extracting candidate triple embedding based on a boundary judgment matrix, calculating a contradiction coefficient by using a quantum emotion entangled state, and generating a correction triple set. According to the method, the accuracy and availability of emotion recognition results in the fields of medical evaluation and the like are enhanced.

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 provides a large language model JSON output repairing method and system based on ANTLR grammar analysis, and belongs to the technical field of model repairing. The method comprises the following steps: preprocessing an original output text of a model to obtain a to-be-repaired JSON text; constructing a fault-tolerant grammar rule, and generating a JSON grammar parser according to the fault-tolerant grammar rule; a JSON text to be repaired is input into an analyzer, grammar analysis is carried out in stages by adopting a progressive grammar matching strategy, and error node position coordinates and error types of grammar analysis anomalies are positioned by analyzing a context tracking mechanism; according to the position coordinates of the error nodes and the error types, performing context-aware repair on the text by adopting a hierarchical repair strategy to obtain a repaired JSON (JavaScript Object Notation) text; and performing multi-layer verification on the repaired JSON text by using a multi-layer verification mechanism, and outputting the repaired JSON text after the multi-layer verification is passed. According to the method, the error classification accuracy and the error positioning precision in the JSON output repairing process are improved, and then the repairing success rate of large language model JSON output is improved.

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 is suitable for the technical field of data query, and provides an index query method and device, electronic equipment and a storage medium, and the index query method comprises the following steps: obtaining a first type of query language statement input by a user; performing grammar analysis on the first type of query language statement based on a predefined grammar rule to generate a corresponding analysis tree; traversing the analytic tree, identifying a query target in the first type of query language statement, and constructing a query semantic object based on the query target, the query target including one or more of an index and a physical table; and according to the query semantic object, generating a second type of query language statement corresponding to the first type of query language statement for an underlying data system to perform index query. According to the scheme, by introducing the query semantic object and supporting mixed recognition and processing of the index and the physical table, the problems that in an existing query mode, flexibility is insufficient, dynamic parameters cannot be expressed, and multi-source joint query cannot be supported are solved.

The invention relates to a heterogeneous database data migration method, which relates to the technical field of data migration, and comprises the following steps: automatically judging the type of a source database by analyzing meta-information in a source database acquisition packet, and then performing lexical and grammatical analysis on an SQL (Structured Query Language) of the source database to form a syntax tree object of the source database; object migration and conversion are carried out on the source database syntax tree object and the target database syntax tree object, and mapping of the syntax tree objects is completed; the target syntax tree object is converted into the target database object script through rule conversion and rewriting conditions, and automatic data migration is achieved.

The invention discloses a method and system for reversely generating a design book through codes driven by a large language model, and relates to the field of software engineering. According to the method, code engineering is analyzed through a grammar analysis technology and a big language model, the incidence relation of visible explicit and implicit codes is mined, and a knowledge graph is formed. And function points are mined from a project by applying heuristic search in combination with a vector clustering technology. And relying on the knowledge graph, a summary design book and a detailed design book are reversely generated for code engineering by utilizing a large language model, so that the technical difficulty of maintenance and migration of a software system is reduced in an auxiliary manner.

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 discloses a Function Declaration-oriented code intelligent comparison and incremental updating method and system, and belongs to the technical field of data analys.The method specifically comprises the steps that grammar analysis is conducted on code files of different versions, an abstract syntax tree is constructed, the abstract syntax tree is traversed to extract a function declaration set, and the function declaration set is stored in a database; comparing the function declaration set by adopting an anti-collision hash algorithm, marking the changed function declarations, and carrying out difference analysis; on the basis of the difference analysis result, the system automatically formulates and executes an incremental updating strategy, the unchanged codes are reserved to the maximum extent, and the code upgrading efficiency and reliability are improved.

The invention discloses an ANTLR-based SysMLv2.0 text model synchronization method, which comprises the following steps of: S1, constructing a syntactic analysis framework of a SysMLv2.0 language on the basis of the ANTLR, and generating a Leyer and a Parser for analysis; s2, analyzing the original SysMLv2.0 text, and generating an abstract syntax tree AST containing structure, behavior and constraint elements; s3, constructing a semantic model structure based on AST mapping; s4, respectively constructing an original semantic model and a target semantic model, and unifying an identifier, a namespace and a reference path format; s5, comparing semantic model structure differences to generate a difference list; s6, performing insertion, deletion or replacement operation on the original model text according to the difference type, and performing incremental synchronization; s7, deserializing the synchronized semantic model to generate a standard SysMLv2.0 modeling text; and S8, outputting the text file for loading and visual operation of the modeling tool. According to the method, a unified analysis and synchronization system is constructed, and accurate comparison and incremental updating of the SysMLv2.0 text model are realized.

The invention discloses a nuclear energy field-oriented C + + code conversion method and system, and belongs to the technical field of nuclear energy. The nuclear energy field-oriented C + + code conversion method comprises the following steps: step 1, grammar analysis and optimization; generating an abstract syntax tree AST from the ST source program, and performing redundant node optimization on the abstract syntax tree; step 2, constructing a meta-model; constructing a meta-model by using an Eclipse modeling framework (EMF); step 3, performing static inspection and security verification; step 4, code generation and optimization; converting the analyzed and detected traversal model instance into an efficient C + + code through an Acceleo template engine; according to the C + + code conversion method and system oriented to the nuclear energy field, the technical problems that in a nuclear energy control system, the real-time performance of codes is insufficient, the safety risk is high, and the cross-platform portability is poor are solved.

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.

According to the audio signal optimization method and device, the storage medium and the computer equipment provided by the invention, in an audio signal optimization process, the syntax tree is generated by reading the audio configuration file and performing grammar analysis on the audio configuration file to perform structure verification, so that the module dependency graph of the audio configuration file can be quickly constructed. And the accuracy and effectiveness of the configuration file are ensured. Creating each module instance based on the module dependency graph, and constructing an executable optimal processing link; the optimal processing link is dynamically generated, and the combination and sequence of the module instances can be quickly adjusted according to different audio application scenes and requirements, so that quick deployment and flexible adjustment are realized. And finally, the audio signal is processed according to the optimal processing link to obtain an optimized target audio signal, so that the audio processing efficiency and adaptability are improved. Therefore, according to the scheme, the link is dynamically constructed and optimized, so that the problem of low processing efficiency in the face of diversified and personalized requirements is effectively solved.

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.

The invention relates to the technical field of PLC programming language testing in the field of industrial automation control, in particular to an IEC 61131-3-based PLC programming software language function full coverage testing method, which comprises the following steps: establishing a structured test table based on functions of five PLC programming languages; based on the content of the structured test table, a plurality of different function points to be tested are determined, and a test program complete set is determined based on the function points to be tested; the test program complete set is iteratively updated according to a test standard; importing the test program complete set into to-be-tested PLC programming software, and testing grammar analysis, compiling results and runtime behaviors to obtain test data; generating a technical list based on the test data; according to the invention, the test comprehensiveness of the PLC programming language can be improved.

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.

The invention discloses a transformer area differentiated resource integrated communication method based on an intelligent fusion terminal, and the method comprises the following steps: S1, building a three-dimensional resource description model which comprises an equipment type, a communication protocol and data features, and carrying out the unified modeling of a photovoltaic inverter, an energy storage device and an intelligent electric meter; s2, dynamically calculating a communication priority weight according to the real-time state of the equipment and the operation requirement of the power grid; S3, selecting an optimal communication channel through a hybrid decision model; and S4, realizing protocol non-sensitive interaction by adopting an AST driving architecture which comprises a grammar analysis layer and a semantic conversion layer. According to the method, deep coupling of a communication technology and power system control is achieved, and normal form transformation from passive adaptation to active optimization is achieved through breakthrough of the three technologies. Firstly, the multi-dimensional cooperative communication capability is improved, a dynamic priority mechanism is introduced, a three-dimensional weight model is constructed based on an equipment type, a power grid state and a service demand, and accurate distribution of communication resources is realized.

The invention discloses a machine translation method and system based on large model fusion task disassembly and cognitive planning. The method comprises the following steps: 1) decomposing a translation task into a plurality of stages, including syntactic analysis, semantic alignment, term precise mapping, context coherence optimization and culture adaptation; a cue word used in the semantic alignment stage prompts a model to accurately recognize semantic connotation of a source language sentence, and finds a most matched semantic expression in a target language; and 2) in each stage, guiding the large model to execute a corresponding translation task by using a specific cue word so as to ensure the translation quality. According to the method, through a multi-stage cognitive translation instruction framework, a context-aware multi-round dialogue engine and an interpretable translation decision tracing mechanism, the quality and efficiency of machine translation are remarkably improved, good adaptive capacity and interpretability are achieved, and the method is suitable for translation requirements of various complex texts.