综述知识图谱嵌入可视化方法与挑战，指出界面模块化不足。
Visualization of Knowledge Graphs with Embeddings: an Essay on Recent Trends and Methods
- 分两类：用嵌入辅助探索图谱，或解释嵌入本身
- 现有框架多满足直观界面与性能，但缺乏模块化设计
- 适合研究知识图谱可视化与人机交互的学者参考
本文探讨知识图谱（Knowledge Graphs, KGs）在嵌入技术辅助下的可视化分析与探索最新趋势。针对四类核心挑战——直观且模块化的用户界面需求、大数据处理性能、查询语言使用难度等——综述当前可视化框架与方法。发现多数框架能较好支持直观界面、高效性能及查询功能，但模块化设计仍普遍缺失。在知识图谱嵌入方面，区分了两类方法：一类利用嵌入促进图谱探索，另一类聚焦于解释嵌入本身，二者存在显著差异。最后提出未来方向，包括弥补未满足需求、引入新型视觉特征，以及针对关系可视化这一知识图谱特有元素开展实验。
原文摘要 · Abstract (English)
In this essay we discuss the recent trends in visual analysis and exploration of Knowledge Graphs, particularly in conjunction with Knowledge Graph Embedding techniques. We present an overview of the current state of visualization techniques and frameworks for KGs, in relation to four identified challenges. The challenges in visualizing Knowledge Graphs include the need for intuitive and modular interfaces, performance in handling big data, and difficulties for users in understanding and using query languages. We find frameworks that generally satisfy the intuitive UI, performance, and query support requirements, but few satisfying the modularity requirement. In the context of Knowledge Graph Embeddings, we divide the approaches that use embeddings to facilitate exploration of Knowledge Graphs from those that aim at the explanation of the embeddings themselves. We find significant differences between the two perspectives. Finally, we highlight some possible directions for future work, including diffusion of the unmet requirements, implementation of new visual features, and experimentation with relation visualization as a peculiar element of Knowledge Graphs.
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