As a powerful expression of human knowledge in a structural form, knowledge graph (KG)
has drawn great attention from both the academia and the industry and a large number of …

With the advent of the electric power big data era, semantic interoperability and
interconnection of power data have received extensive attention. Knowledge graph …

Knowledge graph (KG) embedding aims to study the embedding representation to retain the
inherent structure of KGs. Graph neural networks (GNNs), as an effective graph …

Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Recently, a large number of studies focus on semantically or syntactically …

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. To
better comprehend long complicated sentences and obtain accurate aspect-specific …

Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …

Abstract Knowledge graphs are multi-relational data that contain massive entities and
relations. As an effective graph representation technique based on deep learning, graph …

Graph neural networks (GNN) have emerged as a new state-of-the-art for learning
knowledge graph representations. Although they have shown impressive performance in …

When answering natural language questions over knowledge bases (KBs), different
question components and KB aspects play different roles. However, most existing …

Knowledge graphs are large graph-structured knowledge bases with incomplete or partial
information. Numerous studies have focused on knowledge graph embedding to identify the …