PDF to Text Converter using Natural Language Processing Approach

Extracting text from PDF documents is a challenging task that requires high accuracy and consistency, particularly when dealing with academic literature. While numerous systems are available, many fail to deliver satisfactory performance. This is a significant problem for researchers involved in text mining and project analysis, as they require a reliable tool for converting PDFs to text. In this paper, we propose a Natural Language Processing-based PDF-to-text (NLPDF) conversion system that consists of two major steps: extracting content from the PDF and reconstructing the text. We evaluate the performance of our system using four metrics: Precision, Recall, F-Measure (AF), and standard deviation. We compare our system with eight other benchmarked systems currently available in the market. The experimental results clearly demonstrate the effectiveness of our proposed system.