Summary of Fish-bone Diagram Of Research Issue: Gain a Bird’s-eye View on a Specific Research Topic, by Jinghong Li et al.
Fish-bone diagram of research issue: Gain a bird’s-eye view on a specific research topic
by JingHong Li, Huy Phan, Wen Gu, Koichi Ota, Shinobu Hasegawa
First submitted to arxiv on: 30 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to support novice researchers in understanding academic papers and grasping the fundamentals of a new research field. The authors develop a knowledge graph called the “fish-bone diagram” that provides a broad, generalized overview of the research topic by constructing causal relationships based on issue ontology from academic papers. This tool aims to bridge the gap between researchers’ limited understanding of the research field and their ability to use large language models (LLMs) like ChatGPT effectively for research surveys. The study evaluates the strengths and limitations of the fish-bone diagram as a viable tool for supporting research surveys, highlighting its potential in facilitating novice researchers’ access to accurate information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps beginners in research learn about new topics more easily. It creates a special kind of map that shows how different ideas are connected. This map is called the “fish-bone diagram.” The map uses words and phrases from academic papers to show how concepts are related. This can help beginners understand big ideas better and use large language models like ChatGPT more effectively for research surveys. The study looks at the strengths and weaknesses of this map as a tool for helping researchers learn. |
Keywords
» Artificial intelligence » Knowledge graph
