6 results about "Text value" patented technology

Provided is a process including: obtaining criteria to select plain-text values in a lower-trust database; selecting, based on the criteria, a first plain-text value; in response, determining a first reference value; storing the first plain-text value in a higher-trust database in a second entry identified by the first reference value; storing the first reference value in the first entry of the lower-trust database; selecting another instance of the first plain-text value stored requested to be stored in a third entry in the lower-trust database; and in response, storing the first reference value in the third entry.

The present application relates to the technical field of artificial intelligence, in particular to a multi-path RAG context weighted enhanced retrieval driven NL2SQL generation method and device. The method comprises the following steps: receiving and preprocessing a natural language query text of user input to obtain a multi-dimensional query vector; performing multi-path context retrieval in parallel based on the multi-dimensional query vector to obtain a retrieval result set; assembling the retrieval results of the retrieval result set into system prompt words and inputting the system prompt words into a large language model to obtain SQL generation instructions returned by the large language model; and executing the SQL generation instructions. Through virtual key markers and virtual key coverage rules, when a filtering condition string contains a virtual key marker, the large language model is instructed to generate a filtering condition using a text value in an equal comparison and to switch to an identification column and identification value to generate a filtering condition in a range comparison, so that the large language model can generate a correct SQL statement in a range comparison query without understanding the underlying ID coding, thereby solving the problem of understanding the underlying ID coding of the large language model.

A system for managing a technical document for a storage device includes: a large language model (LLM) configured to receive parts selected from a first version of the technical document, which have a target characteristic, and a second version of the technical document newer than the first version of the technical document, and generate first vectors for the selected parts from the first version of the technical document and second vectors for all parts from the second version of the technical document based on semantics. A comparator compares each of the second vectors with the first vectors to find a closest first vector, and generates a similarity metric between each of the second vectors and the closest first vector. A classifier classifies each of the parts from the second version of the technical document based on the similarity metric and text values of the parts from the second version.

The invention, which relates to the technical field of computer vision and intelligent data processing, discloses an electric charge notice processing method combining OCR and multi-level verification, and the method comprises the steps: carrying out the OCR processing of an electric charge notice image, and obtaining the full text and position information; positioning and extracting initial text values of the key fields based on predefined semantic tags and position information, and combining the initial text values into structured data; verifying the data by using a multi-level rule engine; when verification fails and an error caused by OCR is identified, triggering an intelligent correction strategy based on context semantics to carry out correction; according to the method, OCR and business rule verification are deeply integrated, an intelligent closed loop of identification-verification-correction is constructed, end-to-end automatic processing from images to credible data is realized, the accuracy and processing efficiency of data extraction are effectively improved, and the method has good format adaptability.

A question processing system and methods are provided that are configured to intelligently generate structured data queries from natural language questions using a large language model (LLM). The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform operations which include receiving a natural language question for structured data including columns having discrete text values, generating, using an LLM, a first structured data query having a predicted text value, searching a data store for similar ones of the discrete text values, generating, using the LLM, a second structured data query that refines the first structured data query based on the similar discrete text values, and querying a structured database based on the first and / or second structured data query.

This application discloses a method for processing in-vehicle projection screens, an electronic device, and a vehicle, relating to the field of vehicle projection technology. The method includes: when text content exists in the projection screen frame, segmenting the projection screen frame into text regions to obtain multiple initial text regions; obtaining scores for multiple preset scoring items for each initial text region, and fusing the scores of the multiple preset scoring items to obtain a comprehensive score corresponding to each initial text region; the comprehensive score is used to represent the text value and risk priority of the corresponding initial text region; sorting the multiple initial text regions according to the comprehensive score, and selecting the first number of initial text regions with the highest comprehensive scores as the target text regions of the projection screen frame; obtaining the character recognition results of the target text regions, and determining whether there is target abnormal information in the projection screen frame based on the character recognition results of the target text regions. This application can save computing resources for in-vehicle projection.