Summary of Multi-level Shared Knowledge Guided Learning For Knowledge Graph Completion, by Yongxue Shan et al.
Multi-level Shared Knowledge Guided Learning for Knowledge Graph Completion
by Yongxue Shan, Jie Zhou, Jie Peng, Xin Zhou, Jiaqian Yin, Xiaodong Wang
First submitted to arxiv on: 8 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 In Knowledge Graph Completion (KGC), researchers aim to enhance representation and performance by leveraging shared knowledge within existing datasets. The paper introduces Shared Knowledge Guided learning method (SKG) that operates at dataset and task levels. At the dataset level, SKG-KGC broadens original data by identifying shared features via text summarization. For three typical KGC subtasks (head entity prediction, relation prediction, and tail entity prediction), a multi-task learning architecture with dynamically adjusted loss weights is proposed. This approach allows models to focus on challenging tasks, mitigating the imbalance of knowledge sharing among subtasks. Experimental results show that SKG-KGC outperforms existing text-based methods significantly on three well-known datasets, particularly on WN18RR. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to complete a puzzle by filling in missing pieces. In this case, the puzzle is made up of words and ideas connected to each other. Researchers want to make it easier to fill in these gaps by sharing knowledge between different parts of the puzzle. They came up with a new way to do this called Shared Knowledge Guided learning method (SKG). This method helps machines learn from multiple tasks at once, rather than just one task at a time. By doing so, SKG can improve performance and make it easier for machines to understand complex connections between words and ideas. |
Keywords
» Artificial intelligence » Knowledge graph » Multi task » Summarization
