Device dependent rendering of PDF content including multiple articles and a table of contents

    公开(公告)号:US12175183B2

    公开(公告)日:2024-12-24

    申请号:US18374565

    申请日:2023-09-28

    Applicant: ISSUU, INC.

    Abstract: The technology disclosed relates to systems and methods for device-dependent display of an article from a PDF file that has multiple articles and a table of contents to the articles. The system can use a library to render the article from the PDF file. The rendering can include bounding boxes positioned at on-page coordinates that can include one or more images and multiple text blocks of glyphs. The system can detect at least one table in the PDF file that includes pages numbers and multiple columns. The system includes logic to partition a contiguous sequence of text representing the table into text blocks of entries and columns. The system includes logic to merge multiple text blocks that align horizontally with a single page number into a single text block. Table of contents is displayed in a device-dependent format including the entries from the merged text blocks.

    VIRTUALIZATION, VISUALIZATION AND AUTONOMOUS DESIGN & DEVELOPMENT OF OBJECTS

    公开(公告)号:US20240420433A1

    公开(公告)日:2024-12-19

    申请号:US18814616

    申请日:2024-08-26

    Applicant: AZ, LLC

    Inventor: Sana Rezgui

    Abstract: An integrated platform is provided that enables the various steps of development operations from design to sales, the virtualization, the visualization and the interpretation of a device so it may be fully created (designed), viewed, manipulated, packaged, simulated, tested, published and marketed right from within the platform. The resulting virtual device (VD) may be a multi-layered, -dimensional, -angular, -disciplinary, -documentarian, -service, manipulated and used in multiple ways. The provided VD may include visual representations of the VD via a traditional display device in a non-immersive environment and/or within an immersive environment via new virtual-reality (VR) devices. For instance, a user may create, manipulate, in real-time, layered multi-dimensional views of a VD in a virtual-reality, augmented-reality (AR), augmented virtual-reality (AVR), and/or mixed-reality (MR) environments.

    CONCEPT-LEVEL TEXT EDITING ON PRODUCTIVITY APPLICATIONS

    公开(公告)号:US20240256773A1

    公开(公告)日:2024-08-01

    申请号:US18129750

    申请日:2023-03-31

    CPC classification number: G06F40/274 G06F40/137

    Abstract: In accordance with examples of the present disclosure, a productivity application provides a concept-level text editing tool that assists users to create a document by generating suggestions of new contents (e.g., an outline or text) of the document while also improving the quality of existing contents of the document. More particularly, the present disclosure teaches the ability to generate an outline by providing step-by-step suggestions of a next outline item, generate text suggestions based on selected outline items, generate new outline item suggestions from selected text, and generate a list of natural language suggestions for an existing outline and/or existing text in the document. It should be appreciated that any implementation or modification to the document or the outline based on the suggestions is vetted by the user.

    METHODS AND SYSTEMS FOR PREDICTING DIFFICULTY OF LONG FORM TECHNICAL QUESTIONS USING WEAK SUPERVISION

    公开(公告)号:US20240111964A1

    公开(公告)日:2024-04-04

    申请号:US18454136

    申请日:2023-08-23

    CPC classification number: G06F40/40 G06F16/35 G06F40/137 G06F40/186

    Abstract: Technical interviewing is important for organizations for assessing a candidate to make hiring decision. For effective technical interviewing, predicting difficulty of long form technical questions is crucial. The present disclosure provides systems and methods for predicting difficulty of long form technical questions using weak supervision from textbooks. Further, zero shot pre-trained large language models and unsupervised template-based technique are used for generating questions. Furthermore, a difficulty score is assigned to the generated questions based on context difficulty and task difficulty. The context difficulty for the generated questions is computed using hierarchical structure of the textbooks, and the task difficulty is computed by determining a similarity between the generated questions and Bloom's taxonomy levels. In the present disclosure, few supervised question difficulty prediction models are trained by means of weak supervision using the generated questions and corresponding difficulty scores and further evaluated for prediction performance using a gold-standard question difficulty dataset.

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