Empowering Interdisciplinary Research with BERT-Based Models: An Approach Through SciBERT-CNN with Topic Modeling

arXiv:2404.13078v1 Announce Type: cross
Abstract: Researchers must stay current in their fields by regularly reviewing academic literature, a task complicated by the daily publication of thousands of papers. Traditional multi-label text classification methods often ignore semantic relationships and fail to address the inherent class imbalances. This paper introduces a novel approach using the SciBERT model and CNNs to systematically categorize academic abstracts from the Elsevier OA CC-BY corpus. We use a multi-segment input strategy that processes abstracts, body text, titles, …

abstract academic arxiv bert class classification cnn cs.cl cs.lg current daily fields literature modeling paper papers publication relationships research researchers semantic text text classification through topic modeling type