ODU Digital Commons
metadata only
Exploring Marshall–Olkin Models Through Bibliometric and Topic Modeling Approaches Uses Latent Dirichlet Allocation (1981-2025): A Study Based on Scopus Data
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
- HiCoSpanTM: A Hierarchical Contrastive and Span-Aware Topic Modeling Framework#376913
- Corporate social responsibility (CSR) versus corporate social advocacy (CSA): Conceptual boundaries, distinct roots, and growing convergence revealed by topic modeling and word embedding#236868
- Knowledge structure, latent topics, and emerging trends in quercetin-immunity research from 2006 to 2025: a bibliometric and LDA topic-modeling analysis.#1080710
- The Emergence of Social Science of Large Language Models#972964
- Cybersecurity and Artificial Intelligence Applications: A Bibliometric Analysis Based on Scopus Database#323639
Record · ID 169466
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