Why every eCommerce platform needs a knowledge graph: better search, smarter recommendations, and AI-powered enterprise ...

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This repository for the paper 📘: A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. The README file here maintains a list of ...

Excel's People Graph add-in turns simple tables into clean, icon-based visuals that automatically update when your data ...

Spread the love“`html In a move that few anticipated, Google has unveiled a groundbreaking open standard for AI agents called the OKF AI standard. Launched in June 2026, this innovative framework has ...

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 ...

Spread the love“`html Did you hear about Google’s latest move in the artificial intelligence space? Probably not, and that’s precisely the point. While the tech giant is famous for its splashy product ...

Abstract: Recommendation systems play a crucial role in uncovering concealed interactions among users and items within online social networks. Recently, Graph Neural Network (GNN)-based recommendation ...

High-impact AI implementations are more likely to treat data architecture, governance, and operationalization as strategic requirements, according to TDWI's 2026 Blueprint report.

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...

Here's why revenue teams need a "Marketing Engineer" — a systems designer who orchestrates agentic AI workflows — and how to hire and structure the role.

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...