Summary of Cyber-security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization, By Ryan Barron et al.
Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization
by Ryan Barron, Maksim E. Eren, Manish Bhattarai, Selma Wanna, Nicholas Solovyev, Kim Rasmussen, Boian S. Alexandrov, Charles Nicholas, Cynthia Matuszek
First submitted to arxiv on: 24 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a method for constructing Knowledge Graphs (KGs) from unstructured text in cybersecurity literature. The proposed approach extracts structured ontology from scientific papers to build multi-modal KGs, which represent both observable information and latent patterns of text. The authors demonstrate this concept by consolidating over two million scientific papers from arXiv into the cyber-domain using hierarchical and semantic non-negative matrix factorization (NMF). This methodology enables the creation of domain-specific KGs for extracting actionable insights from large text datasets. By leveraging KGs, researchers can uncover hidden patterns, named entities, topics or clusters, and keywords in cybersecurity literature. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps organize information from many scientific papers on cybersecurity into a special kind of library called a Knowledge Graph (KG). The KG stores facts in a structured way, making it easier to find important details. One challenge is that the text data is unstructured, so the authors developed a method to extract useful patterns and relationships from the text. They tested this approach on over two million papers and created a cybersecurity-specific KG that can help researchers uncover hidden connections and insights. |
Keywords
» Artificial intelligence » Knowledge graph » Multi modal
