HAL (France)
open access
Mining tractable sets of graph patterns with the minimum description length principle
Nowadays, large quantities of graph data can be found in many fields, encoding information about their respective domains. Such data can reveal useful knowledge to the user that analyzes it. However, the size and complexity of real-life datasets hinders their usage by human analysts. To help the use
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- $Δ$-Motif: Parallel Subgraph Isomorphism via Tabular Operations for Scalable Layout Selection#925059
- $Δ$-Motif: Parallel Subgraph Isomorphism via Tabular Operations for Scalable Layout Selection#920825
- Automated Inference of Graph Transformation Rules#622689
- ClusterGraph: a new tool for visualisation and compression of multidimensional data.#362329
- Student-Generated Knowledge Graphs about Sustainability#1038672
Record · ID 1166403
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive