In response to the above limitations, we propose a general graph transformer framework for knowledge graph embedding (TGformer). It is the first to use a graph transformer to build knowledge ...

To address these issues, we propose an easily pluggable hierarchical knowledge graph embedding framework. High-quality corrupted entities are generated through semantic and structural information, and ...

This frameworks allows to generate and compare whole Knowledge Graph embeddings based on six graph embedding techniques: ...

The database for modern applications. Common use cases: knowledge graphs for AI, fraud detection, personalization, and search. Built and maintained by @hypermodeinc.

Graphs, maps and charts from The Times — and an invitation to students to discuss them live. What do you notice and wonder about the severity of drought in the U.S.? By The Learning Network ...

The Graph price prediction anticipates a high of $0.2640 by the end of 2024. In 2027, it will range between $0.7517 and $0.9167, with an average price of $0.7737. In 2030, it will range between $2.22 ...