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
