Hu, Zhiwei, Gutiérrez-Basulto, Víctor  ORCID: https://orcid.org/0000-0002-6117-5459, Xiang, Zhiliang ORCID: https://orcid.org/0000-0002-0263-7289, Li, Ru and Pan, Jeff Z.
2027.
Monotonicity-aware knowledge fusion for hyper-relational knowledge representation.
Information Fusion: An International Journal on Multi-Sensor, Multi-Source Information Fusion
137
, 104643.
10.1016/j.inffus.2026.104643
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Abstract
Hyper-relational knowledge graphs (HKGs) extend traditional knowledge graphs by enriching triples with attribute–value qualifiers, enabling the fusion of multi-granular factual knowledge. The task of hyper-relational knowledge graph completion (HKGC) aims to infer plausible missing links by jointly exploiting information from both main triples and their qualifiers. Existing approaches mainly emphasize direct interactions between triples and qualifier pairs, but often overlook the monotonicity properties that naturally emerge from the fusion of coarse-grained and fine-grained knowledge. To address this, we propose the HyperMono model, which introduces a two-stage reasoning mechanism. In the first stage, triple-level reasoning produces coarse-grained inference signals, which are then refined in the second stage through triple+qualifier reasoning to achieve fine-grained predictions. This design leverages qualifiers to refine the candidate answer space derived from the main triple, providing a qualifier-aware prediction process that reduces answer drift in hyper-relational reasoning. To implement this property, HyperMono represents triples as cones and models each qualifier as a cone that incrementally shrinks the triple cone. Furthermore, HyperMono integrates neighborhood context information to semantically strengthen entity representations, thus realizing a richer fusion of structural and contextual knowledge. Extensive experiments on three real-world datasets under multiple evaluation scenarios demonstrate that HyperMono significantly outperforms state-of-the-art baselines. Datasets and code are available at the following website: https://github.com/zhiweihu1103/HKGC-HyperMono.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Computational & Mathematical Sciences Schools > Computer Science & Informatics |
| Additional Information: | RRS policy applied |
| Publisher: | Elsevier |
| ISSN: | 1566-2535 |
| Date of First Compliant Deposit: | 5 August 2026 |
| Last Modified: | 05 Aug 2026 09:00 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/188723 |
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