International business machines corporation (20240346339). GENERATING A QUESTION ANSWERING SYSTEM FOR FLOWCHARTS simplified abstract
Contents
GENERATING A QUESTION ANSWERING SYSTEM FOR FLOWCHARTS
Organization Name
international business machines corporation
Inventor(s)
Joseph Shtok of Binyamina (IL)
LEONID Karlinsky of Acton MA (US)
Simon Magnus Tannert of Stuttgart (DE)
Jasmina Bogojeska of Adliswil (CH)
Marcelo Gabriel Feighelstein of Zychron Yaakov (IL)
GENERATING A QUESTION ANSWERING SYSTEM FOR FLOWCHARTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240346339 titled 'GENERATING A QUESTION ANSWERING SYSTEM FOR FLOWCHARTS
The abstract of this patent application describes methods, systems, and computer program products for generating semantically meaningful question-answer pairs for graph-like charts, such as flowcharts. In one example, a method of implementing a question answering (QA) system involves generating a synthetic dataset of graph-like chart images by rendering a plurality of graph-like chart images from associated graph data, generating question-answer pairs for each image, and calculating ground truth annotations for each pair and associated graph-like chart images. The QA system is further trained on the synthetic dataset to answer questions about the graph-like chart images.
- Simplified Explanation:
The patent application discusses techniques for creating question-answer pairs for graph-like charts, like flowcharts, to train a QA system.
- Key Features and Innovation:
- Generation of semantically meaningful question-answer pairs for graph-like charts - Creation of a synthetic dataset of chart images for training a QA system - Training a vision-language architecture to answer questions about the chart images
- Potential Applications:
- Enhancing question-answering systems for graph-like charts - Improving understanding and analysis of complex data represented in charts - Automating the generation of question-answer pairs for educational purposes
- Problems Solved:
- Difficulty in generating meaningful question-answer pairs for graph-like charts - Lack of efficient methods to train QA systems on chart data - Limited automation in creating educational materials based on chart images
- Benefits:
- Improved accuracy and efficiency in answering questions about graph-like charts - Enhanced educational tools for teaching complex concepts through charts - Streamlined processes for generating question-answer pairs for various applications
- Commercial Applications:
"Enhancing Question-Answering Systems for Graph-Like Charts: Market Implications"
- Prior Art:
Further research can be conducted in the field of question-answering systems for visual data and educational tools utilizing graph-like charts.
- Frequently Updated Research:
Stay updated on advancements in vision-language architectures and question-answering systems for visual data.
Questions about Question-Answering Systems for Graph-Like Charts: 1. How does this technology improve the efficiency of answering questions about complex data represented in charts? 2. What are the potential educational applications of training QA systems on graph-like chart images?
Original Abstract Submitted
aspects of the disclosure include methods, systems, and computer program products for generating semantically meaningful question-answer pairs for graph-like charts, such as flowcharts. in one example, a method of implementing a question answering (qa) system may comprise generating a synthetic dataset of graph-like chart images. the generating may comprise rendering a plurality of graph-like chart images from a plurality of associated graph data, generating a plurality of question-answer pairs for each of the graph-like chart images, and calculating a plurality of ground truth annotations for each of the plurality of question-answer pairs and associated graph-like chart images from the plurality of associated graph data. the method of implementing the qa system may further comprise training a vision-language architecture on the synthetic dataset to answer questions about the graph-like chart images.
