Motivo: fast motif counting via succinct color coding and adaptive sampling

Summary: Motivo uses compact color-coding structures and a biased coloring trick to cut coloring costs, enabling scalable motif counting. Adaptive sampling via fractional set cover yields guarantees for all motifs, enabling rare motif estimates on graphs with billions of edges. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 11854
Venue: VLDB
Year: 2019
Pagerank: 7.1253867e-05
Overall Rank: 3,410 | 76.28%
DOI: 10.14778/3342263.3342640

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
3,001	Neural Subgraph Counting with Wasserstein Estimator	2022	SIGMOD	7.7404487e-05
3,778	A Learned Sketch for Subgraph Counting	2021	SIGMOD	6.7747398e-05
4,626	Efficient Biclique Counting in Large Bipartite Graphs	2023	SIGMOD	6.0399035e-05
5,518	Hypergraph Motifs: Concepts, Algorithms, and Discoveries	2020	VLDB	5.4621935e-05
5,597	Efficient Shortest Path Counting on Large Road Networks	2022	VLDB	5.4178241e-05
6,289	Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach	2024	VLDB	5.1275309e-05
7,317	Accurate and Fast Approximate Graph Pattern Mining at Scale	2025	VLDB	4.7639399e-05
7,934	Fast Local Subgraph Counting	2024	VLDB	4.613363e-05
10,258	TIMEST: Temporal Information Motif Estimator Using Sampling Trees	2026	VLDB	4.1945683e-05
10,623	Efficient and Adaptive Estimation of Local Triadic Coefficients	2025	VLDB	4.1945683e-05
10,632	Efficient and Accurate Subgraph Counting: A Bottom-up Flow-learning Based Approach	2025	VLDB	4.1945683e-05

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
1,740	A General Framework for Estimating Graphlet Statistics via Random Walk	2017	VLDB	0.0001071792

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