Summary of Advances in Machine Learning Research Using Knowledge Graphs, by Jing Si et al.
Advances in Machine Learning Research Using Knowledge Graphs
by Jing Si, Jianfei Xu
First submitted to arxiv on: 23 Dec 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 The paper utilizes CSSCI-indexed literature from CNKI to analyze the current state and emerging trends in Chinese machine learning research. It employs CiteSpace visualization software to create knowledge graphs on collaboration networks, keyword co-occurrences, and research hotspots. The analysis reveals insights into the field’s dynamics, challenges, and potential areas for future exploration. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The study explores the world of machine learning in China by looking at how researchers work together and what keywords are used most often. It uses special software to create maps that show these connections, giving us a better understanding of what’s happening in this field right now. The results help identify areas where research is struggling or could be improved. |
Keywords
» Artificial intelligence » Machine learning
