A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
Towards foundation models for knowledge graph reasoning
Foundation models in language and vision have the ability to run inference on any textual
and visual inputs thanks to the transferable representations such as a vocabulary of tokens …
and visual inputs thanks to the transferable representations such as a vocabulary of tokens …
Incorporating anticipation embedding into reinforcement learning framework for multi-hop knowledge graph question answering
H Cui, T Peng, F **ao, 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 …
CRFR: Improving conversational recommender systems via flexible fragments reasoning on knowledge graphs
Although paths of user interests shift in knowledge graphs (KGs) can benefit conversational
recommender systems (CRS), explicit reasoning on KGs has not been well considered in …
recommender systems (CRS), explicit reasoning on KGs has not been well considered in …
Step by step: A hierarchical framework for multi-hop knowledge graph reasoning with reinforcement learning
Recently, knowledge graph reasoning has sparked great interest in research community,
which aims at inferring missing information in triples and provides critical support to various …
which aims at inferring missing information in triples and provides critical support to various …
Path-based multi-hop reasoning over knowledge graph for answering questions via adversarial reinforcement learning
H Cui, T Peng, R Han, J Han, L Liu - Knowledge-Based Systems, 2023 - Elsevier
Multi-hop knowledge graph question answering targets at pinpointing the answer entities by
inferring across multiple triples in knowledge graphs. To enhance model interpretability …
inferring across multiple triples in knowledge graphs. To enhance model interpretability …
Investigating the challenges and prospects of construction models for dynamic knowledge graphs
Recently, Dynamic knowledge graphs (DKGs) have been considered the foundation stone
for several powerful knowledge-aware applications. DKG has a great advancement over …
for several powerful knowledge-aware applications. DKG has a great advancement over …
Iterative rule-guided reasoning over sparse knowledge graphs with deep reinforcement learning
Y **a, M Lan, J Luo, X Chen, G Zhou - Information Processing & …, 2022 - Elsevier
In recent years, reasoning over knowledge graphs (KGs) has been widely adapted to
empower retrieval systems, recommender systems, and question answering systems …
empower retrieval systems, recommender systems, and question answering systems …
Reinforcement learning with dynamic completion for answering multi-hop questions over incomplete knowledge graph
H Cui, T Peng, R Han, B Zhu, H Bi, L Liu - Information Processing & …, 2023 - Elsevier
Text-enhanced and implicit reasoning methods are proposed for answering questions over
incomplete knowledge graph (KG), whereas prior studies either rely on external resources …
incomplete knowledge graph (KG), whereas prior studies either rely on external resources …
Attention-based exploitation and exploration strategy for multi-hop knowledge graph reasoning
B Shang, Y Zhao, Y Liu, C Wang - Information Sciences, 2024 - Elsevier
Abstract Knowledge Graphs (KGs) typically suffer from incompleteness. A popular approach
to solve this problem is multi-hop reasoning through Reinforcement Learning (RL) …
to solve this problem is multi-hop reasoning through Reinforcement Learning (RL) …