Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Abstract: Federated Graph Learning (FGL) demonstrates tremendous potential in distributed graph data analysis and modeling. The rapid growth of graph data and the increasing awareness of privacy ...

Creating simple data classes in Java traditionally required substantial boilerplate code. Consider how we would represent Java’s mascots, Duke and Juggy: public class JavaMascot { private final String ...

Credit: Image generated by VentureBeat with FLUX-pro-1.1 Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

Neo4j Inc. today announced a new serverless offering that dramatically simplifies the deployment of its graph database offering, making it easier to use with artificial intelligence applications. Most ...

Structure content for AI search so it’s easy for LLMs to cite. Use clarity, formatting, and hierarchy to improve your visibility in AI results. In the SEO world, when we talk about how to structure ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management.

Abstract: Over the past few years, multiview attributed graph clustering has achieved promising performance via various data augmentation strategies. However, we observe that the aggregation of node ...