Trustworthy Domain-Specific AI for Structured Knowledge Retrieval and Reasoning
This dissertation presents a scalable architecture for transforming unstructured, domain-specific text into structured knowledge for retrieval and reasoning. It integrates semi-automatic corpus curation, semantic structuring, retrieval, and inference into an interpretable pipeline. The research introduces Binary Bleed, an adapted binary search method that reduces low-rank search complexity for Non-negative Matrix Factorization (NMF), and Hierarchical NMF with automatic latent feature selection (HNMFk), a depth-adaptive topic modeling method that produces interpretable taxonomies guided by subject matter experts. These representations populate a typed Knowledge Graph and a semantically ali...
| Authors | Ryan C. Barron |
|---|---|
| Primary category | cs.IR |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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