On Analyzing Graphs with Motif-Paths
Summary: Motif-paths, concatenations of motif instances, offer high-order structure for graph analysis beyond traditional edge-based approaches. The work applies motif-paths to link prediction, local clustering, and node ranking, and introduces a defragmentation method to connect previously disconnected motif-paths, with experiments on real graphs showing improved effectiveness. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Xiaodong Li (University of Hong Kong)
- 2. Reynold Cheng (University of Hong Kong)
- 3. Kevin Chen-Chuan Chang (University of Illinois Urbana-Champaign)
- 4. Caihua Shan (University of Hong Kong)
- 5. Chenhao Ma (University of Hong Kong)
- 6. Hongtai Cao (University of Illinois Urbana-Champaign)
BibTeX Citation
@article{li_vldb21,
title = {{On Analyzing Graphs with Motif-Paths}},
author = {Li, Xiaodong and Cheng, Reynold and Chang, Kevin Chen-Chuan and Shan, Caihua and Ma, Chenhao and Cao, Hongtai},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {6},
pages = {1111--1123},
doi = {10.14778/3447689.3447714},
url = {https://doi.org/10.14778/3447689.3447714},
year = {2021}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,064 | Finding Locally Densest Subgraphs: A Convex Programming Approach | 2022 | VLDB | 7.6898682e-05 |
| 4,923 | A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery | 2022 | SIGMOD | 6.3522796e-05 |
| 7,457 | DeepTEA: Effective and Efficient Online Time-dependent Trajectory Outlier Detection | 2022 | VLDB | 5.5223267e-05 |
| 8,178 | Efficient Maximal Motif-Clique Enumeration over Large Heterogeneous Information Networks | 2024 | VLDB | 5.382671e-05 |
| 11,562 | ZeroEA: A Zero-Training Entity Alignment Framework via Pre-Trained Language Model | 2024 | VLDB | 4.9793485e-05 |
| 11,664 | MOSER: Scalable Network Motif Discovery using Serial Test | 2024 | VLDB | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 184 | Querying K-Truss Community in Large and Dynamic Graphs | 2014 | SIGMOD | 0.00026100147 |
| 284 | Online Search of Overlapping Communities | 2013 | SIGMOD | 0.00022208562 |
| 1,414 | Effective Community Search over Large Spatial Graphs | 2017 | VLDB | 0.0001073756 |
| 1,940 | A General Framework for Estimating Graphlet Statistics via Random Walk | 2017 | VLDB | 9.3302142e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 2,010 | Mining Significant Graph Patterns by Leap Search | 2008 | SIGMOD |
| 2 | 2,985 | Motivo: fast motif counting via succinct color coding and adaptive sampling | 2019 | VLDB |
| 3 | 4,647 | Mining Graph Patterns Efficiently via Randomized Summaries | 2009 | VLDB |
| 4 | 176 | Graph Indexing: A Frequent Structure-based Approach | 2004 | SIGMOD |
| 5 | 12,065 | Simulation-based Approximate Graph Pattern Matching | 2020 | SIGMOD |
| 6 | 5,096 | Querying Graph Patterns | 2011 | PODS |
| 7 | 4,320 | On Dense Pattern Mining in Graph Streams | 2010 | VLDB |
| 8 | 355 | On Graph Query Optimization in Large Networks | 2010 | VLDB |
| 9 | 7,606 | Mining Attribute-structure Correlated Patterns in Large Attributed Graphs | 2012 | VLDB |
| 10 | 3,539 | Hypergraph Motifs: Concepts, Algorithms, and Discoveries | 2020 | VLDB |