8 results about "Formatted text" patented technology

A system for adaptive text rendering includes an editor, a context analyzer, an adaptive text generator, and a feedback and learning engine. The editor renders a text box on a digital canvas and receives user input via the text box. The context analyzer extracts contextual information from digital content associated with the digital canvas. The adaptive text generator uses the user input, text box dimensions, and contextual information to direct an artificial intelligence (AI) model to generate text. It then formats the generated text to fit within the text box based on one or more fit criteria. The feedback and learning engine captures and evaluates user feedback related to the formatted text and generates tuning adjustments to refine the adaptive text generator or the AI model.

The application discloses a ship structure strength calculation formula fine-grained knowledge extraction method, which faces a ship structure strength calculation scene and comprises the following steps: generating a specified format text file by analyzing a ship structure strength calculation guide PDF; constructing a ship structure strength calculation formula fine-grained extraction large model; obtaining text-level full-quantity triple by adopting a general ontology model guided text-level full-quantity triple extraction method and a semantic-based triple edge relationship supplementing and correcting method; perfecting the ontology model by adopting an ontology model generation and attribute expansion method based on rule filtering and hierarchical clustering; formulating attribute value text description by adopting a triple snowflake type expansion method based on attribute semantic depth mining; and specifying attribute value reference description by adopting a triple supplementing method based on reference association expansion, so as to obtain formula-level full-quantity triple, thereby constructing a calculation formula graph and realizing the structured management of the calculation formula.

This application relates to a method, apparatus, and storage medium for displaying text to be displayed. The method includes: upon acquiring the text to be displayed, acquiring the global offset of the target text within the text to be displayed that requires formatting adjustment; determining the global character range of each slice in the slicing results of the text to be displayed; determining, based on the comparison result between the global character range and the global offset, a target slice containing the character to be adjusted, and determining the local offset of the character to be adjusted within its respective target slice; and during the streaming display of the target slice of the text to be displayed, adjusting the format of the character to be adjusted corresponding to the local offset within the target slice before displaying it. This application solves the technical problem that formatted text cannot be displayed when displaying long text output by LLM.

The application provides a large model-based vertical field data construction method, and belongs to the technical fields of data processing and artificial intelligence, and comprises the following steps: converting a vertical field source document into an intermediate format text and dividing the intermediate format text into multiple text blocks; inputting the text blocks into a pre-trained generative language model, guiding the pre-trained generative language model to generate a plurality of candidate questions according to the contents of the text blocks according to a pre-designed prompt word, and performing preliminary screening and fine screening on each candidate question to obtain a question set; predefining a mode of a knowledge graph according to the field characteristics of the vertical field, processing all the text blocks based on an information extraction model, and constructing a field knowledge graph; and performing local context retrieval based on the text blocks of the source of each final question in the question set, performing global knowledge retrieval based on the field knowledge graph, and generating a final answer and a final thinking chain. The application is suitable for different vertical fields, and can effectively improve the quality of data and ensure the accuracy of question generation.

This invention provides a method for automatically formatting text boxes in architectural drawings, comprising: Step 1, acquiring all text boxes to be automatically formatted and their coordinate information; Step 2, calculating the total area of ​​the overlapping region of all text boxes based on the coordinate information of the text boxes; Step 3, when the total area of ​​the overlapping region of all text boxes is not 0, determining the text box with the largest overlapping area with other text boxes; Step 4, moving the text box up, down, left, and right by a preset distance, selecting the movement action that minimizes the overlapping area with other text boxes after the movement, and executing the movement action; Step 5, repeating steps 2 to 4 until a predetermined number of repetitions is reached.

The application discloses a multi-format text analysis method and system based on a large language model, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring a multi-format text, wherein the multi-format text comprises a first information element in a text format and a second information element in a picture format; analyzing the first information element in the multi-format text to obtain a text analysis result; inputting the second information element in the multi-format text into a first large language model to obtain a picture analysis result output by the first large language model; and inputting the text analysis result and the picture analysis result into a second large language model to obtain an analysis result of the multi-format text output by the second large language model, wherein the second large language model is used for adjusting the output format of the analysis result. The method realizes the analysis of the multi-format text through the large language model, does not require manual intervention, and improves the analysis efficiency for the multi-format text.

The application discloses a script-style record generation method and system based on cross-modal semantic reasoning, comprising the following steps: S1, synchronously collecting and preprocessing audio stream, video stream and auxiliary text data in an interrogation scene, and outputting audio stream A'(t), video frame sequence V'(x, y, t) and formatted text T(n); S2, extracting audio stream A'(t) and video frame sequence V'(x, y, t) features in parallel, and outputting text sequence Text_Seq and visual feature sequence; S3, performing semantic conversion on the visual feature sequence to generate visual description sequence Vis_Seq described in natural language; and S4, performing time sequence alignment and semantic fusion on the text sequence Text_Seq and the visual description sequence Vis_Seq to generate a comprehensive record sequence T_comprehensive. The application generates script-style records with narrative logic and easy-to-understand, breaks the stereotyped mode of template generation, can clearly show the strategy adjustment of interrogation, the emotional change of the parties and the key turning point of the case, and makes the records more in line with the reading and cognitive habits of human beings.