A knowledge graph-aided concept–knowledge approach for evolutionary smart product–service system development
In order to meet user expectations and to optimize user experience with a higher degree of
flexibility and sustainability, the Smart product–service system (Smart PSS), as a novel value …
flexibility and sustainability, the Smart product–service system (Smart PSS), as a novel value …
Incorporating context graph with logical reasoning for inductive relation prediction
Relation prediction on knowledge graphs (KGs) aims to infer missing valid triples from
observed ones. Although this task has been deeply studied, most previous studies are …
observed ones. Although this task has been deeply studied, most previous studies are …
Dyernie: Dynamic evolution of riemannian manifold embeddings for temporal knowledge graph completion
There has recently been increasing interest in learning representations of temporal
knowledge graphs (KGs), which record the dynamic relationships between entities over …
knowledge graphs (KGs), which record the dynamic relationships between entities over …
Knowledgenavigator: Leveraging large language models for enhanced reasoning over knowledge graph
T Guo, Q Yang, C Wang, Y Liu, P Li, J Tang… - Complex & Intelligent …, 2024 - Springer
Large language models have achieved outstanding performance on various downstream
tasks with their advanced understanding of natural language and zero-shot capability …
tasks with their advanced understanding of natural language and zero-shot capability …
Communicative message passing for inductive relation reasoning
Relation prediction for knowledge graphs aims at predicting missing relationships between
entities. Despite the importance of inductive relation prediction, most previous works are …
entities. Despite the importance of inductive relation prediction, most previous works are …
Normalizing flow-based neural process for few-shot knowledge graph completion
Knowledge graphs (KGs), as a structured form of knowledge representation, have been
widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC) …
widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC) …
Incorporating anticipation embedding into reinforcement learning framework for multi-hop knowledge graph question answering
H Cui, T Peng, F Xiao, J Han, R Han, L Liu - Information Sciences, 2023 - Elsevier
Multi-hop knowledge graph question answering (KGQA) aims to pinpoint answer entities by
reasoning across multiple triples in knowledge graphs (KGs). To enhance model …
reasoning across multiple triples in knowledge graphs (KGs). To enhance model …
A survey of reasoning with foundation models
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
[HTML][HTML] Knowledge graph quality control: A survey
X Wang, L Chen, T Ban, M Usman, Y Guan, S Liu… - Fundamental …, 2021 - Elsevier
A knowledge graph (KG), a special form of semantic network, integrates fragmentary data
into a graph to support knowledge processing and reasoning. KG quality control is important …
into a graph to support knowledge processing and reasoning. KG quality control is important …
Conversational question answering over knowledge graphs with transformer and graph attention networks
This paper addresses the task of (complex) conversational question answering over a
knowledge graph. For this task, we propose LASAGNE (muLti-task semAntic parSing with …
knowledge graph. For this task, we propose LASAGNE (muLti-task semAntic parSing with …