mlsanityData to 14 Oct 2026

FLORA: Unsupervised Knowledge Graph Alignment by Fuzzy Logic

arXiv 2510.20467 ↗First posted 23 Oct 2025cs.AI cs.DBcited by 0

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Abstract (arXiv)

Knowledge graph alignment is the task of matching equivalent entities (that is, instances and classes) and relations across two knowledge graphs. Most existing methods focus on pure entity-level alignment, computing the similarity of entities in some embedding space. They lack interpretable reasoning and need training data to work. In this paper, we propose FLORA, a simple yet effective method that (1) is unsupervised, i.e., does not require training data, (2) provides a holistic alignment for entities and relations iteratively, (3) is based on fuzzy logic and thus delivers interpretable results, (4) provably converges, (5) allows dangling entities, i.e., entities without a counterpart in the other KG, and (6) achieves state-of-the-art results on major benchmarks.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 30 of its 61 references that are in the map. First posted on arXiv 23 Oct 2025.

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30 of 61 references.

References · 30

  1. 2020Language-agnostic BERT Sentence Embeddingcited by 627
  2. 2017Cross-lingual Entity Alignment via Joint Attribute-Preserving Embeddingcited by 127
  3. 2020A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphscited by 120
  4. 2019Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphscited by 106
  5. 2020KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoningcited by 106
  6. 2019Multi-view Knowledge Graph Embedding for Entity Alignmentcited by 74
  7. 2015Hinge-Loss Markov Random Fields and Probabilistic Soft Logiccited by 63
  8. 2020Exploring and Evaluating Attributes, Values, and Structures for Entity Alignmentcited by 63
  9. 2020TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphscited by 41
  10. 2024Macro Graph Neural Networks for Online Billion-Scale Recommender Systemscited by 40
  11. 2023OLaLa: Ontology Matching with Large Language Modelscited by 35
  12. 2022SelfKG: Self-Supervised Entity Alignment in Knowledge Graphscited by 32
18 more
  1. 2021From Alignment to Assignment: Frustratingly Simple Unsupervised Entity Alignmentcited by 26
  2. 2024Entity Alignment with Noisy Annotations from Large Language Modelscited by 22
  3. 2023Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignmentcited by 21
  4. 2021OntoEA: Ontology-guided Entity Alignment via Joint Knowledge Graph Embeddingcited by 19
  5. 2021Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embeddingcited by 18
  6. 2023A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignmentcited by 16
  7. 2024Unlocking the Power of Large Language Models for Entity Alignmentcited by 15
  8. 2020The Knowledge Graph Track at OAEI -- Gold Standards, Baselines, and the Golden Hammer Biascited by 9
  9. 2022Large-scale Entity Alignment via Knowledge Graph Merging, Partitioning and Embeddingcited by 9
  10. 2022Informed Multi-context Entity Alignmentcited by 8
  11. 2022Facing Changes: Continual Entity Alignment for Growing Knowledge Graphscited by 8
  12. 2024Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignmentcited by 8
  13. 2022Interactive Contrastive Learning for Self-supervised Entity Alignmentcited by 7
  14. 2023From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignmentcited by 6
  15. 2022Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignmentcited by 5
  16. 2024Learning High-Quality and General-Purpose Phrase Representationscited by 4
  17. 2023PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering Groundingcited by 3
  18. 2024NALA: an Effective and Interpretable Entity Alignment Methodcited by 1

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