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A comprehensive overview of knowledge graph completion
T Shen, F Zhang, J Cheng - Knowledge-Based Systems, 2022 - Elsevier
Abstract Knowledge Graph (KG) provides high-quality structured knowledge for various
downstream knowledge-aware tasks (such as recommendation and intelligent question …
downstream knowledge-aware tasks (such as recommendation and intelligent question …
Research commentary on recommendations with side information: A survey and research directions
Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer …
overload problem in recent decades. Traditional recommender systems, however, suffer …
Knowledge graph embedding: A survey of approaches and applications
Knowledge graph (KG) embedding is to embed components of a KG including entities and
relations into continuous vector spaces, so as to simplify the manipulation while preserving …
relations into continuous vector spaces, so as to simplify the manipulation while preserving …
[PDF][PDF] Representation learning of knowledge graphs with hierarchical types.
R ** by heterogeneous partial-label embedding
Current systems of fine-grained entity ty** use distant supervision in conjunction with
existing knowledge bases to assign categories (type labels) to entity mentions. However, the …
existing knowledge bases to assign categories (type labels) to entity mentions. However, the …
Knowledge graph embedding with concepts
N Guan, D Song, L Liao - Knowledge-Based Systems, 2019 - Elsevier
Abstract Knowledge graph embedding aims to embed the entities and relationships of a
knowledge graph in low-dimensional vector spaces, which can be widely applied to many …
knowledge graph in low-dimensional vector spaces, which can be widely applied to many …