237 results about "Regular expression" patented technology

Artificially intelligent systems and methods for financial coaching provide personalized, fiduciary-compliant financial guidance through advanced machine learning architectures with measurable performance criteria. The systems implement privacy-preserving processing pipelines that detect personally identifiable information using multi-layered pattern recognition including regular expressions for formatted data sequences, named entity recognition with confidence thresholds above 0.85, and contextual analysis algorithms. A multi-step artificial intelligence processing workflow includes automated language detection, emotional tone classification with confidence scoring, financial profile transformation using predefined templates, context-aware question rephrasing, and semantic similarity matching employing vector embeddings with financial domain vocabulary weighting applying multiplier values between 1.3-2.0. Specialized training methodologies expand datasets through mathematical transformation functions utilizing statistical standard deviations with incremental variations between 0.5-2.0. Mood-based escalation logic automatically transfers users to human advisors when emotional indicators exceed confidence thresholds above 0.8. The systems maintain response times below 5 seconds while providing regulatory compliance through curated content sources and predefined fiduciary instruction parameters.

The invention discloses an interaction control method and system for an intelligent agent and a front-end and back-end system, and the method achieves the automatic control of the intelligent agent on the front-end and back-end system through the integration of a large language model. The method comprises the following steps: an intelligent agent performs natural language intention recognition through a large language model, automatically selects a proper tool, extracts parameters required by the tool, converts the intention into a target task, generates a structured control instruction, maintains a complete session history and supports multiple rounds of dialogue interaction; the back end receives a user request, calls an intelligent agent to generate a structured instruction, transmits the structured instruction to the front end, and dynamically adjusts a subsequent instruction according to the received front end feedback; and the front end receives the instruction transmitted by the rear end, automatically identifies an instruction format through a regular expression, performs corresponding operation after parameter verification and feeds back a result. According to the method, unified control of the agent on the front-end UI and the back-end business logic is realized, complex multi-round dialogue and multi-step operation are supported, and the method has a wide application prospect.

The invention provides a non-deep traffic analysis streaming matching search analysis method, which comprises the following steps of: constructing a deep data packet detection architecture on the basis of a data platform development kit (DPDK); aiming at the non-encrypted traffic, establishing a multi-mode recognition mechanism combining a regular expression and a feature bit stream mode; aiming at the encrypted traffic, constructing an encrypted traffic feature library according to the statistical features, the protocol features and the behavior features; real-time risk detection of network traffic is realized by adopting a streaming matching search technology; and constructing an intelligent decision and response mechanism, and integrating flow analysis and identification results. According to the non-deep traffic analysis streaming matching search analysis method provided by the invention, real-time analysis, risk identification and supervision of network non-encrypted traffic and encrypted traffic are realized by taking a data platform development kit (DPDK) as a basis and combining a high-performance streaming regular expression engine and a finite-state machine principle; the method can be widely applied to scenes of network communication supervision, data security protection, malicious traffic monitoring and the like.

Systems and methods for generating an enhanced error message are provided. An example method includes: receiving one or more raw error messages. The one or more raw error messages include one or more stack traces. The method further includes matching at least one raw error message of the one or more raw error messages to one or more error rules from a plurality of error rules. The one or more error rules include regular expression patterns. The method further includes parsing the at least one raw error message, based on the one or more matched error rules from the plurality of error rules; and generating one or more enhanced error messages, based on the at least one parsed raw error messages. The one or more enhanced error messages include one or more natural language sentences. The method further includes embedding the one or more enhanced error messages into a website.

The invention discloses an integrated circuit design Verilog code generation method and device based on a large language model, equipment and a medium, and relates to the technical field of computers, and the method comprises the steps that semantic analysis is conducted on an input language of an integrated circuit user side through the large language model, and a target constraint set is determined based on an obtained performance index set and through a regular expression; a candidate architecture scheme is generated by utilizing thinking chain technology reasoning, the candidate architecture scheme is predicted by utilizing an XGBoost regression model, and a target architecture scheme is determined based on an index prediction result and the candidate architecture scheme by utilizing a non-dominated sorting genetic algorithm; and determining an initial Verilog code based on the target architecture scheme and a preset code template library, and performing code style conversion on the initial Verilog code based on a code style feature corresponding to the integrated circuit user side to obtain a target Verilog code. And the efficiency and availability of integrated circuit design are improved.

The invention discloses a permission matching method and device, and relates to the technical field of computers. The method comprises the following steps: acquiring a to-be-matched path; performing permission rule matching on the to-be-matched path based on a pre-constructed permission rule tree; when the permission rule in the permission rule tree is matched, determining a corresponding rule control permission based on the permission rule, and obtaining a permission matching result of the to-be-matched path; and when the permission rule in the permission rule tree is not matched, determining a preset default control permission as a permission matching result of the to-be-matched path. According to the method, the accurate child nodes, the single-wildcard child nodes and the multi-wildcard child nodes are integrated through the permission rule tree of the single tree structure, common permission matching scenes such as accurate matching, single-segment wildcard matching and cross-multi-segment wildcard matching can be covered without introducing a regular expression, the integrity of the expression ability is guaranteed, the implementation complexity is reduced, and the implementation efficiency is improved. And the system stability is improved. And meanwhile, the problem of matching logic confusion caused by traditional multi-rule scattered storage is avoided.

The invention relates to a project review-oriented large language model optimization training method and system, and the method comprises the steps: collecting multi-source heterogeneous data related to project review through a distributed crawler, converting the multi-source heterogeneous data into a model recognizable format through cleaning, desensitization, labeling and structural processing, and carrying out the recognition of the model. Extracting a text core paragraph through a regular expression, and desensitizing to obtain text data; based on the text data, extracting change points of the text data as policy change contents by comparing expressions of new and old policies; obtaining a historical project review report and extracting policy change content, project parameters and review results to form a training sample set; constructing a BERT model which takes the policy change content and the project parameters as input and takes the review result as output, and performing optimization training based on the training sample set; and utilizing the BERT model after optimization training to predict a project review result.

The invention discloses a file transmission method and system for sensitive information identification and automatic blocking. The method comprises the steps that a network data packet in the file transmission process is captured, file content is analyzed, and related metadata is extracted; performing multi-level sensitive information detection on the extracted related metadata by fusing keyword matching, regular expression matching and semantic analysis methods; based on a multi-level sensitive information detection result, combining sensitive information severity, weight, file importance and information density to construct a weighted risk assessment model, calculating a risk value and dividing risk levels; when the risk level is judged to be high risk, file transmission connection is automatically interrupted, local cache data is cleared, and a complete audit log is recorded. According to the sensitive information identification method and device, through combination of various identification technologies such as keyword matching, regular expression matching and semantic analysis, the accuracy of sensitive information identification is greatly improved, sensitive information in various forms can be effectively identified, and the situations of misinformation and missing report are reduced.

The invention relates to a text review method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: receiving an examination category and a to-be-examined text input by a user terminal; calling a corresponding prompt word according to the review category, inputting the to-be-reviewed text into the large language model, and outputting each review point and a confidence coefficient corresponding to each review point; loading a corresponding regular expression library according to the review category, performing rule matching on the to-be-reviewed text, and outputting hit review points and matching positions corresponding to the review points; performing deduplication merging on the review points to obtain target review points; and sending the target review point and the confidence coefficient and / or the matching position corresponding to the target review point to the user terminal. Therefore, the semantic comprehension ability of the large language model and the rule matching ability of the regular expression library can be combined, the examination texts of different examination categories can be comprehensively and accurately examined without depending on a large amount of standard data, the adaptation range is wide, and the flexibility is high.

The invention relates to an enterprise data analysis method and device, and relates to the technical field of data governance, and the method comprises the steps: carrying out the Text2SQL task fine tuning of a large language model through a low-rank adaptation technology, constructing a structured knowledge base containing an enterprise data dictionary, a field calling relation and a national standard, converting the unstructured industry specification into a structured data standard knowledge base, and realizing knowledge vectorization storage by using an M3E-base vector model; sampling representative samples based on to-be-sorted data fields and retrieving related rules, integrating the representative samples into thinking chain cues, inputting the thinking chain cues into a fine tuning model to generate a labeling classification result, and outputting a data sorting result after multi-model evaluation and verification; generating a regular expression through a retrieval data standard to screen non-standard data, sampling to generate an SQL conversion code, iteratively cleaning until the standard is reached, and outputting standardized data; and finally, executing index optimization and anomaly detection based on the fine tuning model, and receiving natural language query to generate an SQL and a visual report.

The invention discloses an error log analysis method and system based on a large language model. The method comprises the steps of obtaining a first error log text; based on the first error log text and a system cue word, an analysis cue word is constructed, and the system cue word is used for indicating an operation and maintenance expert role of the large language model, a task needing to be executed and a preset structured output format rule; inputting the analysis cue word into a large language model; output content generated by the large language model is received, the output content comprises a first error information analysis result conforming to the preset structured output format rule, and the first error information analysis result comprises an error type analyzed from the first error log text and root cause description. Therefore, a mechanical matching mode of a regular expression is abandoned, the semantic understanding capability of a large language model is combined with cue word engineering, the error log is intelligently analyzed based on deep semantic understanding, and the accuracy and integrity of key error information extraction of the error log are improved.

This invention provides an automatic report generation method based on business rules and regular expression matching, belonging to the field of data processing and report generation technology. The method includes: S1. Report requirement parsing; S2. Business rule definition; S3. Regular expression matching rule configuration; S4. Raw data acquisition; S5. Raw data preprocessing; S6. Business rule execution; S7. Regular expression matching validation and field extraction; S8. Report template generation; S9. Report data filling and generation; S10. Report validation and feedback optimization. This invention achieves accurate, automated, and flexible report generation through multi-stage collaboration and multi-algorithm integration.

A computer-implemented method for identifying a product citation in a document, the method comprising searching, in the document, for an entity identifier corresponding to an entity and, if an instance of the entity identifier is detected in the document, determining a portion of the document around the instance of the entity identifier as a target text, wherein the entity is associated with a product catalogue, the product catalogue comprising a plurality of product identifiers; applying a first regular expression to the target text, wherein the first regular expression is configured to match one or more of the plurality of product identifiers; and if a product identifier from the plurality of product identifiers is determined to be cited in the target text, adding an entry to a citation database linking the document and the product identifier.

The application discloses a data bloodline collection method and device based on a Gbase stored procedure, and the method comprises the following steps: removing fixed keywords of a stored procedure definition process body; capturing a stored procedure variable through a regular expression and converting the stored procedure variable into a Key-Value form; replacing a variable name with a variable value according to the Key; processing a loop structure and a branch structure, and processing a self-defined label; and performing syntax compatibility and replacing or removing SQL statements according to some keywords. The application processes some general keywords of the stored procedure, removes redundant information irrelevant to the data bloodline, processes some syntaxes specific to the Gbase in a compatible manner, so that the syntaxes can be parsed by open-source SQL tools, and the application is adapted to the stored procedure of the Gbase, so that the application can help some manufacturers using the Gbase stored procedure to process data in an automatic form to the data bloodline, and the application is convenient for data warehouse construction.

The application discloses a security reinforcement method and device based on a programming language library, and aims to solve the technical problem that site administrators currently usually manually reinforce the security of sites, and the sites are prone to missing replacement and missing modification. The method comprises the following steps: obtaining a programming language script matched with a regular expression from a target folder storing a script file according to the regular expression; renaming a script name corresponding to the programming language script according to a preset script dictionary, so as to obtain a specified script name after renaming; determining a hyper text markup language document referencing the programming language script, and modifying the name of the programming language script referenced in the hyper text markup language document according to the specified script name.

Techniques are disclosed relating to extracting data from a document, using a large language model (LLM), to populate fields in a data structure. A computer system may receive a request to populate multiple fields of a data structure with data extracted from text of a document. The computer system parses the text using an LLM (as well as regular expressions or other parsing techniques in some embodiments). The parsing includes issuing, to the LLM, a sequence of queries targeting individual ones of the multiple fields. The computer system applies a validation algorithm to results received from the LLM in response to the sequence of queries. The validation algorithm confirms the presence of results in the text of the document and populates the data structured with the validated results. In various embodiments, the computer system performs an optical character recognition (OCR) on the document to determine the text for parsing.

Embodiments of the present application provide a data classification method and device, electronic equipment, storage medium and program product. Relate to the field of information processing. In the present application, a first classification result is obtained according to text data of to-be-classified data, and a second classification result is obtained according to resource directory data of to-be-classified data, and then the first classification result and the second classification result are combined to determine the subclass to which the to-be-classified data belongs. In the present application, regular expressions are not relied on, and not only structured data can be classified, but also unstructured data can be classified. In the present application, the subclass description text data is obtained according to the subclass description text in the classification hierarchical judgment specification table corresponding to the to-be-classified data. Based on the resource directory data of the to-be-classified data and the subclass description text data, the second classification result of the to-be-classified data is obtained, which can scan all subclasses included in the hierarchical classification judgment specification table to accurately determine the second classification result of the to-be-classified data.

The application provides a BERT-based log anomaly monitoring method and system, and relates to the technical field of log data monitoring, comprising: preprocessing log sequences by replacing dynamic variable parameters with regular expressions; extracting semantic vectors using BERT and mapping them to Qwen model vector space; training and fine-tuning the Qwen model to classify log anomalies. This method combines the semantic extraction capability of BERT and the powerful representation capability of the Qwen model, and has the advantages of efficient dynamic variable processing, deep semantic extraction, precise vector space alignment, strong anomaly detection capability, etc. Experiments show that the application is superior to the prior art in terms of precision, recall rate and resource efficiency, significantly improving the accuracy and adaptability of log anomaly detection.

The invention discloses an intelligent potential simulation precision optimization method based on material attribute mutation interpolation. The intelligent potential simulation precision optimization method comprises the steps that TCAD software is used for generating a technical alternating current file containing unstructured doping concentration and potential data; extracting grid point coordinates, grid point coordinates on the material attribute mutation boundary, and doping concentration values and potential values of corresponding grid points from the technical exchange file through a regular expression; determining a polygon range of each material based on the extracted material lattice point information; interpolating the potential data and the doping concentration data of the polygonal range of each material attribute, and generating a doping concentration matrix and a potential matrix according to an actual proportion; and taking the interpolated matrix as a training data set of an X-Net model, training an intelligent potential simulation model, and realizing prediction from doping concentration, bias and material distribution to potential.

The application discloses a kind of main grid side operation mode single identification method and related device, method includes: based on preset semantic rule to the current operation mode single of main grid side carries out first preprocessing operation, obtains multiple semantic single sentence;According to first regular expression, action recognition is carried out to semantic single sentence, obtains action mode list;Second preprocessing operation is carried out to action mode list, obtains simplified action mode list;Word division operation is carried out to the sentence in simplified action mode list, obtains multiple segmentation words;Based on segmentation words and preset main grid side information, according to second regular expression, equipment identification is carried out, obtains equipment ID;Based on preset power grid topological relation, according to action mode list and equipment ID determine target action information.The application solves the technical problem that prior art lacks the text recognition scheme for mode single.

The invention belongs to the technical field of information security, particularly relates to data circulation of a block chain, zero-knowledge proof and confidentiality protection, and particularly provides an efficient instrument control data circulation method based on the block chain, which is used for overcoming the problem of mutual restriction of data correctness and confidentiality in an instrument control data circulation process. According to the method, the regular expression is adopted, so that the data content can be processed, and the defect that an existing data circulation technology is insufficient in data content support is overcome; a challenge mechanism is adopted, so that the whole data set can be prevented from being proved, and the calculation overhead is remarkably reduced; the recursive proof system is adopted to efficiently generate the proof of the challenge data set, the proof is concise, and efficient verification can be carried out on the block chain, so that it is ensured that the proof generation and verification efficiency is further optimized. Based on the core technologies, the efficient data circulation method with correctness and confidentiality guarantee is realized.

The invention discloses a DLT log matching method and equipment. The method comprises the following steps: receiving an expected message character string comprising at least one predefined semantic identifier, wherein the predefined semantic identifier is used for representing a dynamic content type in a DLT log; relying on a mapping rule base formed by the predefined semantic identifiers and regular expression fragments, obtaining regular expression fragments corresponding to the predefined semantic identifiers; performing regular escape processing on a static text part in the expected message character string, and splicing the static text part subjected to escape and the regular expression fragment according to an original sequence in the expected message character string so as to construct a regular matching mode; and finally, matching the message field of the actual DLT log by using the regular matching mode to obtain a corresponding matching result.

The invention relates to the field of log analysis, and provides a log sensitive information extraction method and system based on a large language model. According to the method, a processing architecture of'rule preliminary screening-model fine judgment 'is adopted, and log texts are preliminarily screened by using predefined regular expression rules; and submitting the preliminarily screened candidate segments to a large language model for context semantic analysis, thereby accurately distinguishing non-sensitive information with similar formats and sensitive information without a fixed mode. Besides, through a feedback optimization mechanism, continuous learning can be carried out from an actual judgment, and a rule base can be automatically adjusted and supplemented, so that the long-term maintenance cost and the dependence on experts in the manual field are reduced, evolution from a static rule set to a self-adaptive and intelligent sensitive information extraction system is realized, and the method is suitable for popularization and application. And the effect and reliability of log security management and control are comprehensively improved.

The invention relates to the technical field of computer data processing and information system operation and maintenance, in particular to a universal field matching method and system in an operation and maintenance scene and electronic equipment, and the method comprises the following steps: acquiring multi-source basic data and historical field matching data; constructing an initial field regular standard and an initial priority model based on historical field matching data, and extracting multi-source basic data to obtain four types of core features and effective features; and optimizing the initial field regularization standard and the initial priority model based on the effective features to obtain a regular expression matching rule, a structured association key rule and a fuzzy matching threshold rule, and executing a matching task on the rules to obtain a real-time matching result and exception handling feedback. And the rule is optimized based on the real-time matching result and the exception processing feedback to obtain a field matching standard, and the field matching efficiency under different operation and maintenance scenes is improved.

The application discloses a consumer complaint response method and system based on AI assistance and language understanding, which splits the complaint response process into two core sub-problems of multi-modal consumer complaint data processing and feature fusion and demand attribution and response generation. In multi-modal consumer complaint data processing and feature fusion, first, regular expressions are used to denoise text, spectral subtraction is used to denoise voice, and Gaussian filtering and adaptive histogram equalization are used to denoise images; then, modal features are extracted, text is used as the core of cross-modal fusion, and entity and relationship are extracted to construct a multi-modal semantic knowledge graph. In demand attribution and response generation, Graph Transformer is used in combination with the graph and domain prior knowledge to output primary and secondary demands; a static complaint graph is constructed, an attribution path is mined through BFS and is verified through multi-modal verification; and an "emotion-demand-attribution-prevention" structure is used to optimize text and adjust the format by using LLM, and an individualized complaint response is output.

The application discloses a domain-specific language design method, device, equipment and storage medium. The method comprises the following steps: determining a syntax rule corresponding to a target domain according to a business logic of the target domain; writing the syntax rule according to a regular expression to obtain a target syntax described based on the regular expression; and generating a program package under a target running environment based on the target syntax, so as to develop the business logic by using the program package. The syntax rule is written by using the regular syntax, is not limited by a predefined syntax, and can be customized according to any business domain. Meanwhile, the running program under any environment can be output by specifying the target running environment, so that the generated program package can run in any specified environment, and the flexibility of the domain-specific language design is improved.

The invention provides a customs code preprocessing method and system based on a structured tax number tree, and the method comprises the steps: analyzing a customs tax rule document through employing a natural language processing technology, and extracting the hierarchical structure of tax numbers, the commodity description corresponding to each tax number, and a commodity classification condition; establishing a tax number structure tree containing a father-child relationship, a brother relationship and an exclusion relationship; extracting feature words of multiple dimensions from the commodity description by adopting a TF-IDF algorithm to form a many-to-many mapping table; identifying an exclusion condition in the commodity classification conditions through a regular expression, converting the exclusion condition into an IF-THEN rule, binding the IF-THEN rule with a corresponding tax number in the tax number structure tree, and performing rule logic consistency verification; obtaining feature words of each tax number based on a many-to-many mapping table, calculating a semantic distance of each tax number, constructing a semantic vector space, and clustering similar tax numbers; and correcting the clustering result by using the exclusion item rule base, and outputting the tax number semantic association network and the clustering result for customs coding classification. According to the invention, automatic processing and intelligent maintenance of tax rule information can be realized.

This invention discloses a code security scanning method, comprising: project file filtering: filtering project files in a source code repository according to a preset filtering strategy to generate a set of files to be scanned; scan scheduling: scheduling a first scanning tool and / or a second scanning tool to perform code security scanning on the set of files to be scanned according to the scan mode selected by the user, and obtaining a set of scan alert results, wherein the first scanning tool is a static scanning tool based on regular expressions or abstract syntax trees, and the second scanning tool is a deep scanning tool based on graph analysis; result standardization: deduplicating the scan alert result set to obtain a standardized scan alert dataset; report generation: generating a standardized scan report based on the standardized scan alert dataset. By scheduling the corresponding scanning tool to perform code security scanning on the files to be scanned according to the scan mode selected by the user, multiple scanning modes are provided to improve scanning accuracy.

This application relates to an FPGA-based full-offload regular expression matching system and method. The system includes a regular expression rule compilation unit and an FPGA full-matching unit. The regular expression rule compilation unit receives a set of regular expression rules, extracts fixed feature substrings from each rule, compiles a uniformly formatted isomorphic NFA, and constructs a mapping table between substrings and corresponding NFAs. The FPGA full-matching unit includes a parallel high-speed string matching engine array, a string-NFA mapping table module, a full regular expression data storage, a reconfigurable general-purpose NFA engine module, and a matching result output module. It performs full-offload regular expression matching on input network traffic: scanning the traffic through the engine array, filtering traffic containing fixed feature substrings to be verified and outputting substring identifiers, querying the NFA identifiers through the mapping table module, and loading the NFA for matching by the reconfigurable engine module. This method ensures low latency and high throughput performance for regular expression matching in high-speed network environments.

The application discloses a system and method for calculating dynamic relations of entities, comprising an entity recognition module, a calculation module and a writing and pushing module, wherein the entity recognition module comprises a recognition processing unit, an extraction unit and a standardization and screening unit; the processing unit is used for processing personal names and institutional names; the extraction unit is used for splicing the title and the body of news and inputting into a model; the standardization and screening unit is used for standardizing the input personal names and institutional names by using a regular expression; according to the existing entity recognition technology, the news subject is recognized from the complicated news body by using a combination of a pre-training model and a traditional model, the change trend of the recognized entity relations with the news heat is analyzed, the real-time dynamic relations between the entities are established, and the system can be applied to future search word library expansion.