Komari
Structural Signal Mining (Critical Nodes in Complex Networks)

Execution node

Structural Signal Mining (Critical Nodes in Complex Networks)

Ongoing domain Structural Signal Mining Updated

Build the low-dimensional structural direction around critical-node identification in complex networks, then bridge it to semantic-network transfer.

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Execution progress 11.1%
Milestones
3
Descendants
2
Blog links
7
Artifacts
1

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Execution metrics for Structural Signal Mining (Critical Nodes in Complex Networks) and descendant roadmap nodes
Node Level Status Progress Children Related Blog Related Artifacts Milestones Next Target Last Updated
Structural Signal Mining (Critical Nodes in Complex Networks) domain Ongoing 11.1% 1 7 1 1/3
2027/10/31 Pending O1-KR3 deadline: transfer critical-node methods to semantic networks
2027/10/31
O1-KR1: Critical Node Identification on Multi-layer Heterogeneous Networks pillar Ongoing 0.0% 1 2 1 0/3
2026/03/31 Ongoing Finish baselines, data splits, and critical-node metric definitions
2026/06/30
O1-KR3: Transfer Structural Methods to Semantic Networks task Pending 0.0% 0 2 1 0/3
2027/03/31 Planned Define mapping protocols from structural features to semantic-network features
2027/10/31

Overview

This direction prioritizes structure-first signal discovery: improve critical-node robustness in multi-layer heterogeneous graphs, then connect the methods to semantic-network modeling.

Success Criteria

  • A stable and reproducible workflow on complex-network benchmarks.
  • Smooth transfer of structural methods to semantic information networks with robust performance.

Research log

07

本体工程：如何呈现 (Ontology Engineering: How to present)

2026/07/23

本体工程：深入本体构建 (Ontology Engineering: Deepdive into Ontology Construction)

2026/07/21

本体工程：本体论 (Ontology Engineering: Ontology)

2026/07/20

本体工程：初识本体的构建 (Ontology Engineering: First Time View of Ontology building)

2026/07/20

本体工程

2025/09/19

统计关系学习(Statistical relational learning)

2025/07/16

《图论导论》前言与导论

2025/07/08

Materialized signal

01

Identifying Critical Nodes with Deep Learning and Reinforcement Learning

PAPER

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