Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Multi-modal entity alignment (MMEA) aims to discover identical entities across different
knowledge graphs (KGs) whose entities are associated with relevant images. However …

Entity alignment (EA) is a fundamental data integration task that identifies equivalent entities
between different knowledge graphs (KGs). Temporal Knowledge graphs (TKGs) extend …

Abstract Knowledge Graph (KG) stores human knowledge facts in an intuitive graphical
structure but faces challenges such as incomplete construction or inability to handle new …

As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to
identify identical entities across disparate knowledge graphs (KGs) by exploiting associated …

Entity Matching (EM), which aims to identify whether two entity records from two relational
tables refer to the same real-world entity, is one of the fundamental problems in data …

Entity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core
step of bridging and integrating multi-source KGs. In this paper, we argue that existing GNN …

Hypergraphs can model higher-order relationships among data objects that are found in
applications such as social networks and bioinformatics. However, recent studies on …

Entity alignment (EA) identifies equivalent entities that locate in different knowledge graphs
(KGs), and has attracted growing research interests over the last few years with the …

The recommender systems are one of the most effective big data tools for solving the
information overload problem, but data sparsity greatly affects its performance. However …