Skip to content

UvA-DARE (Digital Academic Repository) CRL-MM: Context-Aware Relational Learning and Multidimensional Matching for Few-Shot Knowledge Graph Completion

· 0 citations · 55 references

TL;DR

A novel FKGC model, context-aware relational learning and multidimensional matching (CRL-MM), which considers the entity pair and its neighborhood as a unified contextual whole, aggregating neighborhood information through adaptive task relations and paired entity awareness to improve entity encoding.

View source

Similar papers

Open access 2026

A Dual-Level Structural Context Collaborative Framework for Knowledge Graph Completion

These results demonstrate that collaborative modeling of instance-level and batch-level structural context can effectively enhance structure-aware entity representation and improve fine-grained entity prediction.

Jing Wang, Tian Xia, Hao Li · 0 citations
Open access Sep 2026

MSSC-EM: A Multi-Semantic Self-Supervised Collaborative Entity Matching Framework

Entity matching (EM) aims to determine whether two tuples from heterogeneous data sources refer to the same real-world entity and serves as a fundamental task in data integration, knowledge graph construction, and intelligent information retrieval. However, existing EM methods still suffer from three major limitations:...

Yao-Li Xu, Chun-Li Xie, Zhi-Lei Yin et al. · 0 citations
Aug 2026

Knowledge Graph Completion Model Based on Semantic Constrained Hybrid Scoring

A knowledge graph completion model based on semantic constrained hybrid scoring (SCHS) is proposed, which integrates three synergistic mechanisms that essentially resolves the rigid trade-off between geometric alignment and flexible semantic matching.

Peng-Song Duan, Jia-Ke Zhao, Bo Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

PEARL: Path-Entity Aligned Relational Learning with Contextual Subgraphs for Inductive Knowledge Graph Completion

PEARL is proposed, a Path-Entity Aligned Relational Learning framework that models paths as context-conditioned reasoning signals and employs a dual-view contrastive objective that promotes representation consistency under stochastic contextual perturbations.

Yun Yang, Longlong Li, Cunquan Qu · 0 citations
#artificial intelligence Preprint Sep 2026

URA-NER: A Unified Retrieval-Augmented Framework with Retrieval Alignment and Uncertainty Reduction for Low-Resource NER

A novel unified retrieval-augmented framework, URA-NER, including three key components: Progressive Granularity Retrieval, Model-aware Representation Enhancement, and Reason-aware Knowledge Verification is proposed, including three key components: Progressive Granularity Retrieval, Model-aware Representation Enhancemen...

Jing-Yu Wang, Shijie Wu, Fu-Sheng Jin · 0 citations
Open access Aug 2026

Towards Building a Multi-Source Heterogeneous Knowledge Graph for Complex Material Question Answering

Results indicate that integrating multi-source domain knowledge with relation-preserved retrieval and attribute-supported filtering provides more focused and inspectable evidence, thereby supporting more accurate complex material question answering.

Peize Li, Xi Guo, Nan Yin et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.