Method and system for document structure based unsupervised long-form technical question generation
US12430517B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 16, 2023 |
| Grant date | Sep 30, 2025 |
| Priority date | — |
| Expiry date | Apr 5, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure a method for document structure based unsupervised long-form technical question generation. Initially, the system receives a textbook document. Further, a PDF metadata is extracted from the textbook document using a Natural Language Processing (NLP) technique. Further, a plurality of structures from the textbook document based on the PDF metadata using an NLP based filtering technique. Further, a plurality of index based question templates and Table of Contents (TOC) based question templates are obtained from a plurality of predefined question templates using the plurality of structures. Further, the generated plurality of long-form technical questions are generated using the obtained index and TOC based question templates. The plurality of long-form technical questions are further evaluated by the system using plurality of metrics. Further, the generated plurality of long-form technical questions are used to finetune a supervised question generation model for generating optimal questions from document structure.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.