Using Deep Learning To Predict Paper Categories Based On Abstracts

Abstract

Academic paper categorization is a criticalstep in the field of information retrieval and information processing. This paper “USING DEEP LEARNING TO PREDICT PAPER CATEGORIES BASED ON ABSTRACTS” proposes a novel approach to the automatic classification of academic papers based on their abstract content, utilizing the power of deep learning techniques. The paper's primary objective is to develop a predictive model for categorizing academic papers. The study's findings are presented through in-depth analyses, including a classification report and confusion matrix, providing a comprehensive assessment of the model's predictive capabilities. The conclusion summarizes key findings, discusses their implications, and suggests potential avenues for future research or improvements. The results of this study suggest several promising directions for future research in automated academic paper classification, offering a dynamic framework aligned with evolving research landscapes. My model has attained an accuracy of 79