Knowledge graph (KG) completion is a challenging yet essential task that has attracted increasing attention in recent years. While entities in KGs typically present complex semantics (a phenomenon ...

For a long time, universities worked off a simple idea: knowledge was scarce. You paid for tuition, showed up to lectures, ...

Bet365 had a breakthrough by combining metadata tagging and GraphRAG to give gen AI the all-important context it needed.

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.

In a paper published in Journal of Geo-information Science, a group of researchers pioneered a new paradigm by leveraging large language models (LLMs) in constructing typhoon disaster knowledge graphs ...

The essence of knowledge representation learning is to embed the knowledge graph into a low-dimensional vector space to make knowledge computable and deductible. Semantic indiscriminate knowledge ...