LightNE: A Lightweight Graph Processing System for Network Embedding
Summary: LightNE is a CPU-only, single-machine graph embedding system, scalable to graphs with billions of edges, combining NetSMF and ProNE. Downsampling to reduce NetSMF sample needs; GBBS-based stack; sparse hash tables for sparsifier; MKL-based randomized SVD. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jiezhong Qiu
- 2. Laxman Dhulipala
- 3. Jie Tang
- 4. Richard Peng
- 5. Chi Wang
Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,561 | Accelerating Sampling and Aggregation Operations in GNN Frameworks with GPU Initiated Direct Storage Accesses | 2024 | VLDB | 5.4332062e-05 |
| 6,985 | CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression | 2023 | SIGMOD | 4.8729387e-05 |
| 7,394 | Efficient Estimation of Pairwise Effective Resistance | 2023 | SIGMOD | 4.7427524e-05 |
| 10,732 | Effective and Efficient Attributed Hypergraph Embedding on Nodes and Hyperedges | 2025 | VLDB | 4.1945683e-05 |
| 10,885 | Efficient Graph Embedding Generation and Update for Large-Scale Temporal Graph | 2025 | VLDB | 4.1945683e-05 |
| 10,958 | Efficient Approximation of Kemeny’s Constant for Large Graphs | 2024 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,474 | Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank | 2020 | VLDB | 0.00011825229 |
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