<![CDATA[Advances in mobile technology have driven the development of various applications that enhance efficiency in information processing. This study discusses the development of a mobile-based document summarization application that utilizes Optical Character Recognition (OCR) technology to extract text from physical documents and images. As opposed to other summarization software that uses OCR, this tool has a lighter design tailored for mobile users such that it becomes viable for students and professionals who desire instant summaries readily available. The application process of the software entails taking a snap of the document, extracting text through an OCR process, and generating summaries using an NLP-based Application Programming Interface (API). Evaluation results indicate that the application registered an average extraction accuracy of 95% for text and provided short and contextually correct summaries. Such results indicate the novelty and efficacy of the proposed approach in improving mobile information management productivity and efficiency]]>
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