Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory. This past October, as Jacob Holm and Eva Rotenberg were thumbing through a ...

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

A couple of weeks ago, I attended and spoke at the first stop in the Neo4j GraphTour in Washington D.C. and I was able to get the best answer yet to a question that I’d been pondering: what’s the ...

A professor has helped create a powerful new algorithm that uncovers hidden patterns in complex networks, with potential uses in fraud detection, biology and knowledge discovery. University of ...

With the rapid development of mobile networks, location-based services have become deeply embedded in people's daily lives. Although the k-NN search problem has obtained a lot of research results, the ...

Recently, Guangzhou Oumi Blockchain Technology Co., Ltd. announced its application for a patent titled "A Method for Deploying Strategies of Fusion Model Knowledge Graphs and Artificial Intelligence ...

This is a preview. Log in through your library . Abstract We propose a linear-time, single-pass, top-down algorithm for multiple testing on directed acyclic graphs, where nodes represent hypotheses ...

It hadn’t occurred to me in quite these terms before, but Google has an algorithm for its Knowledge Graph. I have been tracking the Knowledge Graph API for five years. The resultScores have always ...