Topics
We are interested in (including but not limited to) topics as follows.
KG-enhanced web search
KG-based virtual assistant systems
Efficient graph neural networks tailored for KG embedding
Efficient contrastive learning models tailored for KG refinement, including KG completion and KG error detection
KG-based recommender systems
Theoretical analysis of and insights into KG reasoning
Effective KG construction algorithms dedicated to specific scenarios
Algorithms that bridge the gap between KG embedding and
applications in various domains, such as recommendations, education, sports, and transportation