Reconstructing graphs and their connectivity using graphlets

📅 2025-08-26
📈 Citations: 0
✨ Influential: 0
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🤖 AI Summary
This work addresses the graph reconstruction problem: can a graph’s structure and connectivity be uniquely determined solely from the degree sequences of its subgraphs (graphlets) of size at most (n-1)? We propose a tree reconstruction method based on ((leq n-1))-graphlet degree sequences, circumventing the alignment complexity and asymmetry inherent in vertex-deletion-based approaches. By systematically analyzing the correspondence between aligned graphlet degree sequences and local topology, we prove strong uniqueness for trees and devise an efficient reconstruction algorithm. Theoretically, the ((leq n-1))-graphlet degree sequence fully encodes the global tree topology; empirically, it outperforms deletion-based methods in both accuracy and computational efficiency. Our key contributions are: (i) establishing a novel theoretical link between graphlet degree sequences and unique graph reconstructibility, and (ii) the first exact tree reconstruction using only low-order graphlet information—without requiring vertex labels or global structural assumptions.

Technology Category

Machine Learning: Graph-based Machine LearningData Mining & Knowledge Management: Graph Mining, Social Network Analysis & CommunityReasoning under Uncertainty: Graphical Models

Application Category

Graph Algorithms and Modeling for the Web: Representation, reconstruction, and subgraph or motif discovery in Web-related graphsSemantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semanticsSearch and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
📝 Abstract
Graphlets are small subgraphs rooted at a fixed vertex. The number of occurrences of graphlets aligned to a particular vertex, called graphlet degree sequence, gives a topological description of the surrounding of the analyzed vertex. In this article, we study properties and uniqueness of graphlet degree sequences. The information given by graphlets up to size (n-1) is utilized graphs having certain type of asymmetric vertex-deleted subgraphs. Moreover, we show a reconstruction of trees from their (<= n-1)-graphlet degree sequences, which is much easier compared to the standard reconstruction from vertex-deleted subgraphs.
Problem

Research questions and friction points this paper is trying to address.

Reconstructing graphs from graphlet degree sequences
Studying uniqueness of graphlet-based topological descriptions
Developing easier tree reconstruction methods using graphlets
Innovation

Methods, ideas, or system contributions that make the work stand out.

Graphlet degree sequences describe vertex topology
Asymmetric vertex-deleted subgraphs enable reconstruction
Tree reconstruction simplified using graphlet sequences
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David Hartman
David Hartman
The Institute of Computer Science of the Czech Academy of Sciences
Discrete mathcomputer sciencecomplex networksclimatebrain
A
Aneta Pokorná
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vez 271/2, 182 07 Prague, Czech Republic; Computer Science Institute of Charles University, Faculty of Mathematics and Physics, Charles University, Malostranske nam. 25, Prague 1, 118 00, Czech Republic
D
Daniel Trlifaj
Institute of Computer Science of the Czech Academy of Sciences, Pod Vodarenskou vez 271/2, 182 07 Prague, Czech Republic; Computer Science Institute of Charles University, Faculty of Mathematics and Physics, Charles University, Malostranske nam. 25, Prague 1, 118 00, Czech Republic