large-scale graphs

DataFunSummit

Oct 31, 2024 · Artificial Intelligence

Community Recommendation in Tencent Games: Adaptive K‑Free Community Detection and Constrained Large‑Scale Community Recommendation (ComRec)

This article presents Tencent's research on community recommendation for online games, introducing an adaptive K‑Free community detection algorithm (DAG) to address cold‑start and unknown community count, a constrained large‑scale recommendation method (ComRec), their evaluation metrics, experimental results, and deployment insights.

Graph Neural NetworksRecommendation systemsTencent games

0 likes · 20 min read

Community Recommendation in Tencent Games: Adaptive K‑Free Community Detection and Constrained Large‑Scale Community Recommendation (ComRec)

DataFunTalk

Aug 4, 2024 · Artificial Intelligence

Community Recommendation in Tencent Games: Adaptive K‑Free Community Detection and Constrained Large‑Scale Community Recommendation (ComRec)

This article presents Tencent's research on community recommendation for online games, covering the motivation behind recommending player groups, the challenges of cold‑start and data sparsity, the adaptive K‑Free community detection algorithm (DAG) with joint structural‑semantic learning, the constrained large‑scale ComRec algorithm, extensive offline and online experiments, and practical deployment insights.

Graph Neural NetworksTencent gamescommunity recommendation

0 likes · 20 min read

AntTech

Sep 7, 2023 · Artificial Intelligence

Ant Group Open-sources Ant Graph Learning (AGL), the First General Industrial Graph Learning System

Ant Group announced the open-source release of Ant Graph Learning (AGL), a pioneering industrial‑grade graph learning platform that supports trillion‑scale graph data, offers ready‑to‑use algorithms, and aims to lower the barrier for large‑scale graph AI applications across industries.

Ant GroupOpen Sourcegraph learning

0 likes · 4 min read

Ant Group Open-sources Ant Graph Learning (AGL), the First General Industrial Graph Learning System

DataFunSummit

Jun 15, 2022 · Artificial Intelligence

Introducing DGL: An Efficient, Easy‑to‑Use Graph Deep Learning Platform and Its Future Roadmap

This article presents an overview of the Deep Graph Library (DGL), covering graph data and graph neural networks, DGL's advantages such as flexible APIs, operator fusion, large‑scale training support, its open‑source ecosystem, recent projects, performance comparisons, and future development plans.

DGLDeep LearningGraph Neural Networks

0 likes · 18 min read

Introducing DGL: An Efficient, Easy‑to‑Use Graph Deep Learning Platform and Its Future Roadmap

DataFunTalk

May 14, 2022 · Artificial Intelligence

Introducing DGL: An Efficient, User‑Friendly, Open Graph Deep Learning Platform

This article presents an overview of graph data and graph neural networks, explains the core concepts of message‑passing GNNs, highlights DGL’s flexible API, high‑performance system design, large‑scale training capabilities and open‑source ecosystem, and outlines future plans and community resources.

DGLDeep LearningGraph Neural Networks

0 likes · 17 min read

Introducing DGL: An Efficient, User‑Friendly, Open Graph Deep Learning Platform

DataFunSummit

Jan 14, 2022 · Artificial Intelligence

Graph Attention Multi‑Layer Perceptron (GAMLP) and Node‑Dependent Local Smoothing (NDLS) for Scalable and Flexible Graph Neural Networks

This presentation introduces Tencent Angel Graph's NDLS and GAMLP techniques that address GNN scalability and flexibility by adaptively selecting propagation depth per node, employing node‑wise feature and label propagation with attention mechanisms, and demonstrating superior performance on large‑scale and sparse graph benchmarks.

AttentionDeep LearningGAMLP

0 likes · 16 min read

Graph Attention Multi‑Layer Perceptron (GAMLP) and Node‑Dependent Local Smoothing (NDLS) for Scalable and Flexible Graph Neural Networks

JD Retail Technology

Oct 21, 2020 · Artificial Intelligence

Galileo: A Distributed Graph Deep Learning Framework for Large‑Scale Industrial Scenarios

The article introduces Galileo, JD Retail's distributed graph deep‑learning platform that supports heterogeneous and dynamic graphs, ultra‑large scale training, flexible model customization, and seamless integration with TensorFlow and PyTorch, highlighting its architecture, core challenges, built‑in algorithms, and upcoming open‑source release.

AI PlatformDeep LearningGraph Neural Networks

0 likes · 11 min read

Galileo: A Distributed Graph Deep Learning Framework for Large‑Scale Industrial Scenarios