Iterative rule-guided reasoning over sparse knowledge graphs with deep reinforcement learning
Y Xia, 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 …
Correlation embedding learning with dynamic semantic enhanced sampling for knowledge graph completion
Abstract Knowledge graph completion aims to solve the problem of incompleteness and
sparsity in knowledge graphs. However, the negative sampling strategy in current …
sparsity in knowledge graphs. However, the negative sampling strategy in current …
A collaborative learning framework for knowledge graph embedding and reasoning
Abstract Knowledge graph embedding (KGE) and knowledge graph reasoning (KGR) aim to
automatic completion of knowledge graph (KG). The difference is that most KGE models …
automatic completion of knowledge graph (KG). The difference is that most KGE models …
Multihop question answering by using sequential path expansion with backtracking
I AlAgha - IEEE Access, 2022 - ieeexplore.ieee.org
Multi-hop question answering from knowledge graphs has gained a growing attention in the
past few years due to its vast applications in AI. Existing approaches in this regard mostly …
past few years due to its vast applications in AI. Existing approaches in this regard mostly …
Heterogeneous relational reasoning in knowledge graphs with reinforcement learning
Path-based relational reasoning over knowledge graphs has become increasingly popular
due to a variety of downstream applications such as question answering in dialogue …
due to a variety of downstream applications such as question answering in dialogue …
MPNet: temporal knowledge graph completion based on a multi-policy network
J Wang, RF Wu, YW Wu, FY Zhang, SR Zhang… - Applied Intelligence, 2024 - Springer
Temporal knowledge graphs completion (TKGC) is a critical task that aims to forecast facts
that will occur in future timestamps. It has attracted increasing research interest in recent …
that will occur in future timestamps. It has attracted increasing research interest in recent …