9 results about "Process semantics" patented technology

The invention provides a Web workflow system and method based on JSON data analysis, and relates to the technical field of workflow design. A standardized JSON process definition file is generated by adopting a visual process designer, process semantic verification and BPMN conversion are realized through a three-level analysis architecture, and efficient management of the whole process of process modeling, execution and auditing is realized in combination with a plug-in task executor, a thread security context manager and a process monitoring module, so that the process modeling, execution and auditing efficiency is improved. The method has the advantages of fast analysis, strong expansion, easy collaboration, traceability and the like.

Device for the intelligent encapsulation of legacy data information systems with the integration of artificial intelligence, comprising: a collection unit for legacy interfaces, configured to intercept communication data from existing platforms; a semantic interpretation unit designed to analyze and map data structures and process semantics; a contextual abstraction layer designed to convert interpreted information into standardized, interoperable formats; a policy-driven management module that ensures secure access, Data transformation and regulatory compliance are ensured; and a learning and inference unit for adaptive optimization of data mappings and operational logic.

The invention relates to the technical field of natural language processing, and discloses an AI-driven cross-language big data semantic extraction and translation method and system.The method comprises the steps that a semantic complexity online prediction model is constructed, a multi-level cache structure is achieved, a semantic importance scoring algorithm is applied, and a resource allocation strategy is optimized in combination with reinforcement learning; a hierarchical time window model is adopted for incremental semantic analysis, and cross-language real-time semantic extraction and translation are achieved. Through the semantic complexity online prediction model and the reinforcement learning optimization resource allocation strategy, the system can accurately predict the data processing difficulty and adjust resource allocation in advance, and the resource utilization rate is improved; in combination with a multi-level cache structure and incremental semantic analysis, the system can quickly retrieve and reuse the processed semantic information and is suitable for application scenes with high requirements on real-time performance; the resource utilization efficiency is effectively improved, the processing delay is remarkably reduced, and the peak value processing capacity is enhanced.

This invention relates to the field of industrial control network detection technology, and more particularly to an industrial control network intrusion detection method based on a large language model. This invention constructs a joint analysis engine of process semantics and physical constraints based on a large language model, performing time-series prediction of the compliance of operational intentions and their physical consequences, thereby identifying the threat level of abnormal intentions. Combining operational instruction data and physical process state data, it identifies abnormal operational behaviors caused by identity impersonation, internal unauthorized access, or operating condition conflicts, and performs process context mismatch risk analysis on operational instructions. Based on the results of abnormal intention threat level identification and process context mismatch risk analysis, it predicts the intrusion threat level of the industrial control network, thereby executing an adaptive response control scheme. This method can detect complex attacks that are formally legitimate but semantically dangerous, effectively identifying abnormal operations caused by identity impersonation, internal unauthorized access, and operating condition conflicts, thus improving the overall security resilience of the industrial control system.

The invention relates to the technical field of intelligent document review, in particular to an intelligent document review method and system based on large model fusion causal reasoning, and the method comprises the steps: collecting documents, extracting formats and null lines, recognizing roles and actions, retrieving nouns after verbs, processing semantic repetition, outputting a table, checking causal connections, comparing action sequences, screening and joining, ranking verbs, and pulling through actions. And outputting causal fragments, checking consistency, separating objects, calibrating behaviors, outputting chain fracture, splitting adverbs, sorting relationships, and outputting conflict paths and review paths. According to the method and the device, by extracting the paragraph formats, roles and actions of the documents, the meticulousness of review is improved. And analyzing a causal conjunction and an action relationship, and identifying a causal relationship and a semantic conflict. The method comprises the steps of calibrating an action sequence, identifying missing parts, sorting multiple actions and role changes, optimizing an examination path, reducing manual intervention and improving efficiency.

Provided in the embodiments of the present disclosure are a method and apparatus for generating code, and an electronic device and a program product. The method comprises: acquiring a user-defined orchestration process drawn by a user on a canvas of a graphical user interface, and on the basis of the orchestration process, generating process orchestration code and process node code in a target language, wherein the process orchestration code represents process semantics, and a process node represents a task in the orchestration process. The method further comprises: on the basis of the process orchestration code and the process node code, generating an executable file package in the target language. In the embodiments of the present disclosure, by means of such a method for converting the orchestration process drawn by the user into the process orchestration code and process node code in the target language and further generating the executable file package in the target language, the code in the target language can be automatically generated from the user-defined orchestration process, such that the barrier to entry for user programming is reduced, and the flexibility of the user orchestration process is improved.

The present application relates to the technical field of industrial control network detection, and more particularly to an industrial control network intrusion detection method based on a large language model, which constructs a process semantics and physical constraint joint analysis engine based on a large language model, performs time sequence prediction on the compliance of an operation intention and a physical consequence, thereby identifying an abnormal intention threat degree; in combination with operation instruction data and physical process state data, identifies abnormal operation behaviors caused by identity impersonation, internal overreach or working condition conflicts, and performs process context mismatch risk analysis on operation instructions; based on the abnormal intention threat degree identification result and the process context mismatch risk analysis result, predicts the intrusion threat degree of the industrial control network; thereby executing an adaptive response control scheme, can detect complex attacks that are formally legal but dangerous in process semantics, effectively identifies abnormal operations caused by identity impersonation, internal overreach and working condition conflicts, and improves the overall security resilience of the industrial control system.

The invention discloses a science and technology enterprise domain knowledge filtering method. Belongs to the field of natural language processing. Comprising the following steps: implementing data cleaning and duplicate removal for a document set of a science and technology enterprise; document content is segmented sentence by sentence, adaptive semantic block aggregation is carried out based on semantic similarity of adjacent statements, and processed semantic blocks are vectorized and then stored in a knowledge base; performing user original query depth optimization by using a large language model, and retrieving the most relevant Top-k blocks after the original query depth optimization; and carrying out classification by using the pre-trained DeBERTa-v3 as a domain filter to judge whether the blocks belong to the field of science and technology enterprises. The model is trained on positive samples (internal file blocks of science and technology enterprises) and negative samples (general knowledge, knowledge in other fields and the like); carrying out redundancy elimination on the basis of the output of the domain filter, and calculating the similarity of the block texts filtered by the domain filter to carry out redundancy filtering; and adding cue words, limiting an answer generated by the large language model to be related to the interior of the science and technology enterprise, and generating an answer according to the finally reserved blocks.

The invention discloses a collaborative filtering recommendation system and method based on natural language processing semantic similarity, belongs to the field of information recommendation, relates to a natural semantic processing technology, integrates semantic information in the field of natural language processing into semantic similarity measurement, comprehensively and deeply understands and finds the semantic information from the practical significance, and improves the recommendation efficiency. The problems of recommendation algorithm cold start and data sparsity are solved; the similarity of the article in the natural language processing field is calculated to obtain more comprehensive semantic information, and the semantic information is not influenced by a user scoring matrix and feature attributes of the user or the article; indirect and direct semantics, explicit semantics and latent semantics are measured, and the defect of a single angle can be made up. According to the method, the similarity between the articles is calculated by utilizing the semantic similarity in the field of natural language processing, and the similarity is fused into the similarity calculation of the collaborative filtering recommendation algorithm, so that the defect that the collaborative recommendation algorithm does not consider the semantic knowledge of the recommended articles is overcome, and the accuracy and recall rate are higher.