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Tencent Cloud Developer
Tencent Cloud Developer
May 29, 2024 · Artificial Intelligence

Distributed Network Embedding Algorithm for Billion‑Scale Graph Data in Tencent Games

Tencent’s Game Social Algorithm Team presents a Spark‑based distributed network embedding framework that recursively partitions hundred‑billion‑edge game graphs into manageable subgraphs, runs node2vec locally, and fuses results, enabling efficient link prediction and node classification across multiple games within hours.

Game AnalyticsSparkdistributed computing
0 likes · 7 min read
Distributed Network Embedding Algorithm for Billion‑Scale Graph Data in Tencent Games
JD Cloud Developers
JD Cloud Developers
Sep 20, 2023 · Artificial Intelligence

Unlocking Hidden Communities: A Deep Dive into Graph Community Detection Algorithms

This article explains the fundamentals of community detection in graph computing, contrasting it with clustering, describing key concepts such as modularity, and reviewing classic algorithms like Louvain, node2vec‑based methods, and Infomap, while highlighting their applications across domains.

Infomapcommunity-detectiongraph algorithms
0 likes · 11 min read
Unlocking Hidden Communities: A Deep Dive into Graph Community Detection Algorithms
JD Tech
JD Tech
Sep 12, 2023 · Fundamentals

Community Detection Algorithms: Concepts, Types, and Classic Methods

This article introduces community detection as a fundamental graph algorithm, explains its basic concepts and types, compares it with clustering, discusses evaluation metrics like modularity, and reviews classic methods such as Louvain, node2vec‑based approaches, and the information‑theoretic Infomap algorithm.

InfomapUnsupervised Learningcommunity-detection
0 likes · 13 min read
Community Detection Algorithms: Concepts, Types, and Classic Methods
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
May 9, 2023 · Artificial Intelligence

Enhanced Graph Embedding with Side Information (EGES) for User Growth and Cold‑Start Mitigation

This article presents EGES, a graph‑embedding model that incorporates side information to construct a directed user graph, apply biased random‑walk sampling, and train weighted Skip‑Gram embeddings, thereby improving large‑scale user acquisition and addressing cold‑start challenges in recommendation systems.

EGEScold startgraph embedding
0 likes · 9 min read
Enhanced Graph Embedding with Side Information (EGES) for User Growth and Cold‑Start Mitigation
Tencent Cloud Developer
Tencent Cloud Developer
Jun 9, 2021 · Artificial Intelligence

Overview of Common Graph Embedding Methods in Industry

The article surveys six widely‑used graph‑embedding techniques—DeepWalk, Node2Vec, LINE, SDNE, EGES and Metapath2Vec—explaining how each transforms graph topology into low‑dimensional vectors via random walks, biased sampling, proximity‑based objectives, deep auto‑encoders, side‑information integration, or meta‑path‑guided walks for industrial applications.

DeepWalkEGESMetaPath2Vec
0 likes · 14 min read
Overview of Common Graph Embedding Methods in Industry
MaGe Linux Operations
MaGe Linux Operations
Aug 18, 2020 · Artificial Intelligence

Understanding node2vec: Biased Random Walks for Graph Embedding

This article explains the node2vec algorithm, its mathematical foundations, biased random‑walk sampling strategy with parameters p and q, implementation details using the Alias method, and demonstrates its superior performance on node classification and visualization tasks compared with DeepWalk and LINE.

Pythongraph embeddingmachine learning
0 likes · 9 min read
Understanding node2vec: Biased Random Walks for Graph Embedding
Sohu Tech Products
Sohu Tech Products
May 27, 2020 · Artificial Intelligence

Overview of Graph Embedding Techniques: DeepWalk, LINE, node2vec, and EGES

This article provides a comprehensive overview of graph embedding methods—including DeepWalk, LINE, node2vec, and EGES—explaining their algorithms, random‑walk strategies, proximity definitions, incorporation of side information, and their applications in large‑scale recommendation systems.

DeepWalkRecommendation Systemsgraph embedding
0 likes · 20 min read
Overview of Graph Embedding Techniques: DeepWalk, LINE, node2vec, and EGES
DataFunTalk
DataFunTalk
Apr 28, 2019 · Artificial Intelligence

Graph Algorithms for Fraud Detection and Community Detection: Modularity, Louvain, Infomap, node2vec and comE

This article explains how graph‑based algorithms such as centrality measures, modularity optimization, Louvain, Infomap, node2vec and the comE framework can be applied to financial fraud detection and community discovery, detailing their principles, formulas, implementation steps and evaluation metrics.

Infomapcommunity-detectionfraud detection
0 likes · 14 min read
Graph Algorithms for Fraud Detection and Community Detection: Modularity, Louvain, Infomap, node2vec and comE