4 results about "Description type" patented technology

The invention relates to the technical field of engineering drawing information extraction, in particular to a description type drawing information extraction method and device, equipment and a medium, and the method comprises the steps: extracting a text serial number based on a rule, verifying a serial number result by adopting a large model, and judging a statement division position when the serial number does not exist; combining one or more adjacent single-line texts into a semantic complete description statement; grouping the serial number of each description statement based on a credibility rule, constructing a description statement tree hierarchical structure, and structurally positioning and splicing each node content based on a keyword of preset information to obtain information-related phrase content; and extracting preset information items by adopting a rule with credibility and a large model respectively, and when the results of the rule and the large model are contradictory, carrying out selection or reutilization of the large model for judgment according to the credibility to obtain a final information result. Therefore, the problems that in the prior art, the credibility degree of the result is difficult to determine, and the situation that the large model answers mistakenly cannot be judged and dealt with are solved.

This invention discloses a method for dynamic language syntax extension and type description based on Prefer blocks. The method includes: performing lexical and syntactic analysis on the dynamic language source code containing Prefer blocks to construct an abstract syntax tree (AST) containing Prefer nodes; parsing the Prefer nodes in the AST to extract type constraint information declared in the Prefer blocks; associating the type constraint information with the corresponding function and variable nodes in the AST to obtain an associated syntax tree; and performing type checking and code generation on the dynamic language source code based on the associated syntax tree to obtain a bytecode file. By setting non-intrusive Prefer blocks and describing type constraints using syntax classes, type information is introduced into the dynamic language without modifying the core syntax or intruding on business logic code, thus solving the problems of tight coupling, poor extensibility, and strong intrusion between the type description mechanism and the core syntax.

The invention provides a dialogue type commodity recommendation method and system based on a large model and electronic equipment, and the method comprises the steps: obtaining interaction information associated with a target user, extracting an attribute value corresponding to a hierarchical attribute definition table through a large language model, and filling the attribute value into a structured preference portrait; the definition table contains constraint class and description class fields, and the extracted attribute values comprise constraint attribute values defining a screening range and description preference attribute values representing aesthetic appreciation and demands of a user; splicing the attribute value with the context information, and generating a user demand abstract by using a large language model; and calculating the semantic vector similarity between the abstract and the commodity selling point abstract, carrying out logic filtering on a calculation result based on a constraint attribute value to obtain a recommended commodity set, and generating reply information containing recommended commodity information. The recommendation method has the advantages of high precision and strong real-time performance.

The invention provides a text classification method, a text classification model training method and device and electronic equipment. The method comprises the steps of obtaining a to-be-classified text; extracting text elements of various description types related to the text classification task from the text; adding description type marks of description types corresponding to the text elements in positions corresponding to the text elements in the text to obtain a text sequence; obtaining an embedded vector sequence of the text sequence; encoding the embedded vector sequence to obtain a text vector representing the text and a plurality of text element vectors representing the text elements of the plurality of description types respectively; performing fusion processing on the text vector and the plurality of text element vectors to obtain a text fusion vector; and mapping the text fusion vector into a classification result of a text type related to the text classification task. Through the method and the device, the text classification accuracy can be improved.