218 results about "Logical expression" patented technology

The invention discloses an electronic medical record automatic quality control system and method based on a large language model, and the method comprises the steps: extracting medical record data from a medical information system, and carrying out the data preprocessing; and performing deep semantic analysis on the medical text by utilizing a large language model, and extracting key diagnosis and operation information. And performing semantic representation on the medical terms by fine tuning the pre-training language model and combining with a multi-layer attention mechanism. And constructing an ICD coding knowledge graph, and calculating the semantic similarity between the diagnosis terms and the ICD coding terms in the electronic medical record by using an embedded vector technology to realize automatic matching. And according to a predefined quality control rule, automatically checking the electronic medical record through the logic expression, and generating a quality control report and an improvement suggestion. And finally, visually displaying quality control and coding results, and outputting a quality control report. The electronic medical record quality control efficiency and accuracy are improved, and standardization and automation of quality control work are achieved.

Provided herein is a process that converts unprotected data into protected data based on permissions defined using logical operators. As such, user permissions can be managed with a simple string of data. In one example, the method may include receiving a request for data from a user device, identifying a permission object corresponding to the user device, retrieving a string comprising a logical expression with a logical operator and one or more values from the permission object, wherein the logical expression defines access permissions of the user device with respect to a database, executing a database query on the database based on the request to generate results, and filtering the results from the database query based on the logical expression to generate filtered results and outputting the filtered results to the user device.

The invention provides a software demand defect detection method based on a large language model and a satisfiability problem solver, and the method comprises the steps: constructing a domain knowledge base, guiding the large language model to extract key elements in a demand text through combining with a cue word project, and recognizing imperfect and ambiguous defects; and meanwhile, the demand is converted into a logic expression, and logic inconsistency is detected by using an SAT solver. According to the method, incremental updating of the knowledge base is supported, efficient retrieval and comparison are achieved through vectorization and Hash coding technologies, experiments show that the method is remarkably superior to a traditional technology in demand detection in the fields of finance and the like, defects can be accurately positioned, correction suggestions can be provided, and the efficiency and accuracy of demand analysis are effectively improved.

The invention discloses an examination method and system based on a BIM model, and relates to the technical field of data processing, and the method comprises the steps: collecting a historical standard text, analyzing the standard text, and constructing a constraint condition logic expression of a standardized attribute value; according to the constraint condition logic expression, through a configuration file and a method name, constructing corresponding data information for the attribute of each component in the BIM model, constructing a preset rule for each component, generating configuration data, and storing the configuration data in a BIM model review rule base; receiving a to-be-examined BIM model, reading attributes of components of the to-be-examined BIM model, and performing model examination according to the preset rule to obtain an examination result; an examination result is output, and visual result output is carried out on unmatched components; the problems of low BIM model examination efficiency and low accuracy in the prior art are solved.

The invention discloses a tool calling semantic analysis method and system for a low-resource data environment, and relates to the technical field of semantic analysis, and the method comprises the following steps: constructing a logic expression of each tool based on a context-independent grammar, and generating initial training data in combination with a cue word project and a large language model; performing iterative training on a pre-configured semantic analysis model according to the obtained training data in combination with a self-training method to obtain an optimized semantic analysis model; and performing similarity calculation on the tool candidate data and the training data through a recall model to obtain vector scores of the tool candidate data and the training data, and screening out tools which do not conform to user semantics to obtain a final semantic analysis model. According to the method, the initial analysis data set based on the context-independent grammar is constructed, and the analysis capability of the model is enhanced in combination with the self-training strategy, so that the performance of the model in a low-resource environment is improved, and the semantic analysis capability is effectively expanded.

The invention discloses a small and medium-sized enterprise information management method and system based on a multi-layer architecture, and belongs to the technical field of information management, and the method comprises the steps: constructing a decoupling architecture of a user interface layer, a business logic layer and a data storage layer; analyzing the evaluation standard through a dynamic rule engine of a business logic layer, and generating a configurable rule unit comprising a logic expression and a dynamic weight parameter; an offline priority strategy is adopted at the mobile terminal, and a vector clock identifier containing a client ID and a logic clock sequence is added to a data record; executing dynamic weighted evaluation calculation to generate a total evaluation score; and performing industry reference threshold verification on the numeric field. The technical bottleneck of tight coupling of multiple layers of modules in a traditional single framework is broken through by constructing a decoupling framework of the user interface layer, the service logic layer and the data storage layer and an asynchronous message bus communication mechanism, so that cross-layer codes do not need to be synchronously modified when the system adds or adjusts the evaluation dimension, and the system reliability is improved. And the framework flexibility and the expansion efficiency are obviously improved.

The invention relates to a public multi-mode cloud network resource software security enhancement method based on neural symbol fusion reasoning, which comprises the following steps: an intermediate representation generation stage: generating and optimizing an intermediate representation of a program through a fine-tuned large language model, and establishing semantic mapping from a source code to a structured logic representation; in the symbol language conversion stage, the intermediate representation generated by the large language model is converted into a domain-specific language fact set which can be recognized in the symbol logic reasoning stage, and formal and logic expression of program semantics is achieved; and a symbol logic reasoning stage: matching the fact set with the rule base through a symbol logic reasoning engine, performing detection and verification according to the safety rule, generating a structured report, and feeding back a result for optimization. The method is suitable for security enhancement of various core software systems in a public cloud network multi-modal network environment, high-precision security analysis is carried out on cross-modal and cross-subsystem fragmented codes in a compiling-free environment, and verifiable technical support is provided for public cloud network security control.

The invention discloses a branch coverage rate calculation method and device based on BOOL logic, and relates to the technical field of software testing. The method is suitable for the test case taking the BOOL logic expression as basic test data, the branch path diagram is generated according to the BOOL logic expression, the coverage rate condition of the test case set on the BOOL logic branches is calculated according to the covered path condition in the case execution process, covered and uncovered BOOL branch reports are output according to the test execution condition, and the test efficiency is improved. The test case executed by the black box is transparent, and meanwhile, a test case set can be completed according to uncovered branch guidance in an output report.

Techniques for a natural language interface for searching and retrieval of digitally-stored information are disclosed. In one embodiment, a computerized method is disclosed comprising receiving, at a computing device, natural language input from a user; generating, by the computing device, a prompt using the natural language input; submitting, by the computing device, the prompt to a large language model (LLM); receiving, by the computing device, from the LLM, a response to the submitted prompt, the response comprising a logical expression of the natural language input generated by the LLM using the prompt; generating, by the computing device, for a data source, a query using the logical expression; retrieving, by the computing device, a query result set from the data source using the query; and generating, by the computing device, a response to the natural language input using the query result set.

The invention discloses a large language model knowledge verification and improvement method and device and a medium. The method comprises the steps that task description, specific problems and example data input by a user are received; in combination with a preset heuristic cue word and structured processing, generating a logic expression, and removing redundant contradiction rules to form a logic knowledge base; inputting specific questions into the large language model to generate preliminary answers, and performing symbolization conversion on the preliminary answers to extract entities, relationships and attributes so as to obtain symbolized propositions; matching the symbolized proposition with the logic knowledge base, if a conflict is matched, generating a candidate correction scheme through deductive reasoning, determining an optimal scheme according to a predefined correction cost function, feeding back the optimal scheme to the large language model, and regenerating an answer; and iterating the related steps until the answer passes verification, and outputting a final answer, a confidence score and an interpretability report. Through the deductive constraint and bidirectional feedback mechanism, the LLM output reliability is improved, the knowledge base cost is reduced, and dynamic updating and interpretability of knowledge are realized.

The invention discloses an expressive control dynamic display system and method for a semiconductor design form, and the system comprises an expression configuration module which is used for receiving a logic expression inputted by a user, and prompting available variables in the form in real time; the variable dependency analysis module is used for identifying dynamic variable reference in the logic expression; the change monitoring and scheduling module is used for monitoring a form data change event, acquiring an affected control set when variable value change is detected, and merging and optimizing expression calculation requests; the expression analysis service module is used for performing grammar check and dangerous operation filtering on the logic expression, processing an expression calculation request and returning an analysis result; and the state updating execution module is used for comparing the difference between the analysis result and the current control state according to the analysis result, and judging whether the current control needs to be updated or not according to the difference. According to the method, the problem of performance waste caused by global monitoring data change is effectively solved.

The embodiment of the invention discloses an intelligent number asking method and system based on dynamic feedback, a storage medium and electronic equipment. The method comprises the steps that a subject domain and a semantic model are constructed, a data view is established, data mapping is configured, and a natural language problem and a standardized index are analyzed; generating an SQL (Structured Query Language) logical expression based on the Few-shot example and the large model, and carrying out semantic correction on the SQL logical expression; sQL query is executed, dynamic feedback storage is carried out based on an execution result, and SQL generation parameters are updated by utilizing a self-adaptive learning mechanism. According to the method, through semantic modeling and data mapping, precise alignment of a natural language and a database structure is achieved; few-shot examples and large model generation are combined with semantic correction rules, so that the accuracy and stability of SQL generation are improved; and a continuously optimized intelligent number-asking closed loop is constructed by executing a feedback and adaptive learning mechanism, so that the self-learning and evolution capabilities of the system are improved.

The invention provides a neural network hardware implementation method and system based on an incomplete specified function, and the method comprises the steps: carrying out the quantification of the input data and weight of a neural network, and obtaining a position index of a non-zero weight; traversing the training set, and obtaining a plurality of data sets related to the non-zero weight according to the position index of the non-zero weight based on an incomplete specified function; performing logic minimization on the basis of the plurality of data sets, generating a Boolean logic expression based on an incomplete specified function, and determining a flash memory logic array scale and internal port connection lines according to a cube of the Boolean logic expression and logic variables in the Boolean logic expression; the flash memory logic array is constructed according to the scale of the flash memory logic array and the internal port connecting line, and a peripheral circuit of the flash memory logic array is constructed, and the peripheral circuit is mainly used for processing output data of the flash memory logic array. According to the invention, power consumption and time delay in a neural network hardware implementation process are reduced.

Described are methods, systems, and media for regulatory exploration comprising: receiving a regulatory exploration request comprising a scenario comprising a desired outcome and a plurality of partial inputs to describe the scenario and identify fact constraints; receiving an executable regulatory logic flow chart, wherein each element of the flow chart is associated with a regulatory text; applying algorithm to determine all paths in the regulatory logic flow chart; filtering the paths based on the desired outcome; transforming each remaining path into a logical expression comprising attributes; generating a query space comprising conditions on the input facts associated with each attribute; generating a fact space comprising input facts associated with each attribute; generating a possibility space by joining the input facts in the fact space under the conditions in the query space; converting the possibility space to a plurality of database queries; and running the queries to generate an output.

The invention discloses an Armv8-a assembly code-oriented formal verification method, which comprises the following steps of: analyzing an Armv8-a processor architecture and an instruction set system, extracting module components to be modeled, including an abnormal level, an execution state, a data value, a register block, a memory, an instruction set and an assembly code, and modeling each module component; determining a non-formalized requirement of the corresponding assembly instruction according to the function and the security specification of each assembly instruction in the assembly code, and then generating a formalized logic expression of each assembly instruction in combination with the defined model, so as to obtain a formalized specification; and finally, carrying out formalized verification by adopting a theorem prover. According to the method, modeling is carried out on each module component of a physical machine, then a formalized logic expression of each assembly instruction in an assembly code is generated based on a constructed model, and formalized verification of the Armv8-a assembly code is completed by using a theorem prover.

The invention provides an agent control instruction generation method and device, equipment, a medium and a product. The intelligent agent control instruction generation method comprises the following steps: splitting an obtained natural language according to a set rule to obtain splitting units; generating a function corresponding to each splitting unit based on the splitting units and a trained function model; constructing a capability logic expression corresponding to the obtained natural language based on the function corresponding to each splitting unit; and generating an agent control instruction based on the capability logic expression. By analyzing the natural language, the corresponding split unit is converted into the corresponding function, the natural language data is standardized through the function, then the agent control instruction is constructed based on the function, and semantic analysis is decoupled from the internal logic of the agent, so that the intelligent agent control instruction is obtained. Therefore, the instruction generation method can be flexibly and repeatedly used and is convenient to migrate.

A logical expression acquisition unit (502) acquires a logical expression that represents a condition under which searchable encryption is permitted, by a logical structure with a plurality of attribute values and a logical operator. An encrypted tag generation unit (504) sets a secret sharing value which reflects the logical structure, to each of the plurality of attribute values, and generates an encrypted tag to be used for the searchable encryption, using a plurality of secret sharing values set to the plurality of attribute values.

A distributed system provides access by a principal to a resource associated with sensitive data. Micro-services in communication with an authorization engine each include a resource provider that receives a resource action request from the principal to access the resource, determines a context for the request, and transmits the context to the authorization engine in an authorization request. The authorization engine receives the authorization request, resolves the authorization request context against a plurality of pre-defined resource conditions, and responds to the resource provider with an authorization response of allow, deny, or allow-with-conditions. The context for the request includes metadata regarding attributes of the principal, and each of the resource conditions includes a logical expression operating upon the attributes.

The invention relates to the technical field of software testing, and discloses an LLM and SMT solver-based test case generation method, which is characterized in that a search type test is taken as a core drive, when coverage stagnation occurs, an execution path is subjected to semantic analysis by means of an LLM, a logic expression for describing a target path condition is generated, and in consideration of the limitation of the LLM in logical reasoning, a test case is generated; the system further introduces an SMT solver to perform verification and reasoning on a logic expression output by the LLM, finally feasible test input is generated, and the test efficiency and the coverage rate are improved. According to the method, the efficiency and precision of path coverage are improved, good adaptability and universality are achieved, the method is suitable for various languages and complex program structures, and the intelligent level and engineering practical value of automatic testing are effectively improved. The problem of insufficient accuracy of a large language model in complex path constraint reasoning is effectively relieved.

The embodiment of the invention discloses an atomic rule logic expression visualization method and device. The specific implementation mode of the method comprises the steps that a grammar rule file is created according to a pre-defined standard data structure of a logic diagram, and grammar for analyzing an atomic rule logic expression is defined in the grammar rule file; generating a lexical analysis interface and a grammar analysis interface according to the grammar rule file; according to the target logic relation expression, based on the lexical analysis interface and the grammar analysis interface, creating an analyzer of the atomic rule logic expression; and analyzing the target logic relation expression through an analyzer to obtain standard data of the logic diagram. According to the implementation mode, the complex atomic rule expression can be converted into the logic diagram.

The invention relates to a 5G security demand extraction and assertion generation technology based on LLM and RAG, and the technology comprises the following steps: 1, a standard document preprocessing module, splitting a 3GPP standard document according to a security process hierarchy, mapping the 3GPP standard document to a corresponding label, and solving a knowledge fragmentation problem; the RAG knowledge base construction module analyzes document slices by using an RAGF low tool, divides the document slices into text blocks, stores the text blocks into a database through vectorization of an embedded model, and realizes efficient retrieval by adopting hierarchical indexing; 3, an LLM semantic understanding and assertion generation module, which is used for converting a natural language demand into a logic expression based on a DeepSeek model in combination with a cue word framework, a knowledge base and a signaling alphabet; and the assertion post-processing module is used for performing grammar check, standard conformity verification, simplification and logic conflict detection on the LTL assertion. According to the technology, automatic extraction of security requirements and assertion generation are realized, efficiency and accuracy are improved, security requirements in multiple aspects are covered, and a reliable scheme is provided for 5G terminal protocol security testing.

The invention discloses an energy power policy file knowledge base retrieval method based on large model fine tuning, which comprises the following steps: step 1, labeling original text data by using an RDF semantic data model, and importing the original text data into a Freebase database; step 2, constructing a fine tuning data set for performing fine tuning on the LLaMa2-7b model; step 3, performing RDF data annotation on a natural language question to be retrieved, and inputting the RDF data annotation into the fine-tuned LLaMa2-7b model to generate a candidate logic expression C; the method comprises the following steps of (1) obtaining a candidate logic expression list C, (2) updating the candidate logic expression list C into C '', (3) inputting the candidate logic expression list C'' into an SPARQL statement generation function, generating an SPARQL query statement, and retrieving an answer to a natural language question from a Freebase database, thereby realizing the unification and standardization of data formats and improving the retrieval accuracy.

The invention relates to the technical field of data analysis, and discloses an event context generation method and device, computer equipment and a storage medium, and aims to analyze theme description information, recommend synonyms and generate a keyword list through a large language model, simplify the operation difficulty of clients and improve the data comprehensiveness. According to the method, the news data are collected through the logic expression corresponding to the keyword list, the time feature text in the news data is standardized, the target short sentence only containing the standard time is obtained, the standard time corresponding to various texts is deduced through the context reasoning ability of the large language model, and the data recall rate and accuracy are improved. The target short sentences are grouped and clustered by using a large language model vector, so that the merging capability of similar events is improved. And selecting the core short sentences of each cluster to generate event sequence data, processing the event sequence data in combination with a logic expression, and filtering uncorrelated events. And finally, generating event venation with high readability by utilizing text output and summarization capability of the large language model.

The invention provides a complex scene visual recognition rapid construction method based on natural language description, and relates to the technical field of computer vision and natural language processing, and the method comprises the steps: obtaining natural language description information inputted by a user; performing language analysis and element extraction on the natural language description information to obtain a scene semantic table; decoupling the scene semantic table into M atomic conditions, and obtaining an atomic instruction set; performing visual feature extraction on the to-be-recognized image by using a visual encoder to generate an image feature vector; converting the atomic instruction set into an atomic instruction vector set, and outputting an atomic instruction verification set; generating a relation verification matrix; and executing global logic expression verification operation based on the atomic instruction verification set and the relationship verification matrix, and outputting comprehensive confidence. The technical problems that in the prior art, semantic understanding depth is insufficient, complex scene understanding is limited, and self-adaptive capacity is insufficient are solved.

The invention discloses a chemical industry park environmental pollution risk intelligent assessment method and system, and relates to the technical field of environmental risk management, and the method comprises the steps: extracting an association rule of a risk event based on a real-time data stream, coding the association rule into a symbolic logic expression, constructing a mixed neural symbol architecture, and carrying out the construction of a hybrid neural symbol architecture; optimizing the symbolic logic expression and the mixed neural symbolic architecture parameters through joint training, and outputting a preliminary risk level assessment result; according to the real-time data stream, extracting a'risk event-cause-consequence 'triple, generating a risk knowledge graph, and performing graph reasoning in combination with a preliminary risk level assessment result to obtain a risk event causal chain and a diffusion path; according to the method, efficient integration and dynamic optimization of the multi-source heterogeneous data are achieved by constructing the mixed neural symbol architecture, and the problem that space-time relevance is weakened due to data splitting type processing in an existing method is solved.

The invention discloses a logic knowledge construction method and device based on a large language model and logic programming, electronic equipment and a storage medium, and belongs to the field of artificial intelligence knowledge engineering. According to the method, automatic conversion from multi-source heterogeneous knowledge to machine reasonable logic knowledge is realized through combination of semantic understanding capability of a large language model and standardized processing of logic programming. The method specifically comprises the steps of obtaining unstructured / semi-structured original knowledge data, performing entity relationship recognition and predicate logic detection by utilizing a large language model to generate a preliminary logic expression, performing grammar normalization processing to form standard logic facts and rules, and constructing a consistent logic knowledge base through a conflict detection and resolution mechanism. According to the method, a mixed conversion framework of natural language and formalized logic is innovatively provided, and the maintainability and expandability of the knowledge base are remarkably improved by introducing timestamp metadata, a rule dependence graph and an incremental updating mechanism. The technology provides structured logic support for subsequent large model reasoning, and can be widely applied to intelligent questions and answers, decision support and other scenes requiring precise logic reasoning.

A method for constructing a fault knowledge graph. The method comprises: after a sentence to be processed is acquired according to fault discrimination text, determining protocol signaling and an atomic flow of said sentence from an atomic flow chart according to a signaling character string of said sentence; after an atomic flow clause is generated according to the atomic flow and said sentence, determining a logic expression corresponding to the atomic flow clause; generating a logic expression of said sentence according to the logic expression of the atomic flow clause; then generating a logic expression of the fault discrimination text according to the logic expression of said sentence; and adding the logic expression of the fault discrimination text to a fault knowledge graph. By means of the method, corresponding protocol signaling and a corresponding atomic flow can be searched for in an atomic flow chart according to a signaling character string of fault discrimination text, such that the accuracy of identifying the signaling can be improved, and the success rate of converting the fault discrimination text into a logic expression is improved. Further provided in the present application is a computing apparatus capable of implementing the method.

The invention discloses a call recording quality inspection method and system based on a logic expression, and relates to the field of call quality inspection, and the method comprises the steps: receiving a logic expression and a call recording text inputted by a user; logic operators in the logic expression are extracted, and operation logic of the logic operators is determined; when it is detected that the customized operator exists in the logic expression, obtaining a detection logic setting of the customized operator in a customized logic database, and determining a customized logic of the customized operator based on the detection logic setting; determining a detection logic tree corresponding to the call recording text; traversing all leaf nodes of the detection logic tree, and determining a node calculation result of the call recording text at the leaf nodes; determining an output result of the detection logic tree at the root node; and according to the logic expression, the call recording text and the output result, generating a recording quality inspection report. By implementing the method, a complex language mode can be identified and processed more accurately, and errors in call recording quality inspection can be avoided to a greater extent.

The invention discloses a special equipment fee checking rule engine implementation method based on java, and relates to the technical field of charging automation. Comprising the steps of 1, defining a calculation rule: defining and storing the calculation rule of the special equipment inspection fee, 2, analyzing the calculation rule: converting the stored calculation rule into an executable code or logic instruction by using a rule analyzer in a Java programming language, and 3, inputting and preprocessing data: inputting and preprocessing the data through a user input or system automatic acquisition mode; and 4, rule matching and execution: inputting the pre-processed related data into a rule engine, matching and calculating the related data by the rule engine according to a preset rule and a logic expression, determining a corresponding inspection cost, and performing rule matching and execution on the inspection cost. Step 5, outputting and feeding back a result: outputting the calculated inspection cost to a user, generating a corresponding cost report or notification according to needs, providing a feedback mechanism, and allowing the user to recheck the result or propose objection, and step 6, updating and maintaining the rule.

The invention discloses a summary generation method and a related device, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-source information of a target conference, obtaining a summary generation prompt instruction according to the multi-source information, the summary generation prompt instruction is used for instructing a summary generation large model to generate a summary according to the content of the multi-source information, and generating a structured conference summary by referring to the hierarchical structure in the conference presentation, and inputting a summary generation prompt instruction into a pre-trained summary generation large model to obtain the conference summary of the target conference. According to the method, the hierarchical structure of the conference summary can be reconstructed based on the hierarchical structure of the conference presentation, so that the content of the multi-source information can be presented as a more logical expression in the conference summary, and the readability of the conference summary is improved.