arXiv: cs.AI preprintsInternational6 November 2026
KG-Neighbor: Knowledge-Guided Neighborhood Construction for Embedding Visualization
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arXiv:2611.07246v1 Announce Type: cross Abstract: In embedding visualizations, nearby instances are interpreted as semantically related, although neighborhoods derived from input embeddings may not reflect content relationships. Neighborhood-based dimensionality reduction (DR) methods can propagate this limitation by optimizing layouts from embedding-based neighborhood graphs. We propose Knowledge-Guided Neighborhood Graph Construction (KGN), which represents relational knowledge derived from each instance as a set of knowledge graph (KG) triples. It uses the degree of triple sharing as pairwi
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