NeuroSym-BioCAT: Leveraging Neuro-Symbolic Methods for Biomedical Scholarly Document Categorization and Question Answering

The growing volume of biomedical scholarly document abstracts presents an increasing challenge in efficiently retrieving accurate and relevant information. To address this, we introduce a novel approach that integrates an optimized topic modelling framework, OVB-LDA, with the BI-POP CMA-ES optimizat...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Zamil, Parvez, Rabby, Gollam, Rahman, Md Sadekur, Auer, Sören
Format:	Artikel
Sprache:	eng
Schlagworte:	Biomedical materials Classification Documents Information retrieval Large language models Optimization techniques Questions Task complexity
Online-Zugang:	Volltext
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