Jul 1, 2018 · In this paper, we propose an embedding method by minimizing a path-specific margin-based loss function for knowledge graph embedding, called PaSKoGE.

Knowledge graph embedding aims to represent entities, relations and multi-step relation paths of a knowledge graph as vectors in low-dimensional vector ...

This paper proposes pTransE to consider relation paths as translations between entities for representation learning, and addresses two key challenges: (1) we ...

Embedding of a knowledge graph. The vector representation of the entities and relations can be used for different machine learning applications.

Nov 8, 2023 · Reasoning on large-scale knowledge graphs has been long dominated by embedding methods. While path-based methods possess the inductive ...

Mar 3, 2018 · In this paper, we propose a novel relation path embedding model (RPE) to explicitly model knowledge graph by taking full advantage of the semantics of relation ...

Aug 24, 2024 · We propose Power-Link, the first path-based KGC explainer that explores GNN-based models. We design a novel simplified graph-powering technique.

Apr 16, 2024 · In this paper, we integrated and optimized a pipeline for selecting reasoning paths from KG based on LLM, which can reduce the dependency on LLM.

Jun 30, 2023 · In contrast, path-based embedding methods can capture path information and utilize extra semantics to improve KGC. However, most path-based ...

Oct 12, 2024 · The path embeddings are obtained by combining the embeddings of individual relations in the path using a composition operator (addition, ...