Path Based Hierarchical Clustering on Knowledge Graphs
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Abstract (arXiv)
Knowledge graphs have emerged as a widely adopted medium for storing relational data, making methods for automatically reasoning with them highly desirable. In this paper, we present a novel approach for inducing a hierarchy of subject clusters, building upon our earlier work done in taxonomy induction. Our method first constructs a tag hierarchy before assigning subjects to clusters on this hierarchy. We quantitatively demonstrate our method's ability to induce a coherent cluster hierarchy on three real-world datasets.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 2 of its 16 references that are in the map. First posted on arXiv 27 Sep 2021.
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Citing papers per year: 2024: 1.
1 paper.
- 2024Hierarchical Blockmodelling for Knowledge Graphscited by 0
- 2024Hierarchical Blockmodelling for Knowledge Graphs28 Aug 2024