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 ...

Graphs, visual representations outlining the relationships between different entities, concepts or variables, can be very effective in summarizing complex patterns and information. Past psychology ...

To address this issue, this paper focuses on how to better extend the representation learning from a single space to Riemannian manifolds, which are capable of representing more complex structures. We ...