English, Industrial and Manufacturing Systems Engineering, Veterinary Diagnostic and Production Animal Medicine, Virtual Reality Applications Center
Journal or Book Title
Proceedings of the 6th International Workshop on Mining Scientific Publications (WOSP 2017)
ICPE ACM/SPEC International Conference on Performance Engineering
December 15, 2017
Toronto, ON, Canada
This paper describes the development of a web-based application for tagging scientific articles, in part to create machine learning training datasets for automated functional language identification and extraction (AFLEX). The initial intent for this work was to provide a new member of the ecosystem of tools that facilitate the structured automation of systematic reviews, an area of work that typically requires critical analysis of multiple research studies and provides an exhaustive summary of literature related to a research question. However, the tool’s modular interface allows use across disciplines. A user may upload PDF or text documents and quickly tag selected parts of the document with a customizable set of discipline-specific tags, and export results to CSV or JSON formats. An integrated back-end database stores tagging data for comparison between taggers or visual display of results on the web browser. While other discipline-specific text tagging tools exist, the authors have not encountered a cloud-based customizable tool for PDF and text annotation as flexible as the AFLEX Tag Tool developed by the authors.
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Ramezani, Mahdi; Kalivarapu, Vijay K.; Gilbert, Stephen B.; Huffman, Sarah R.; Cotos, Elena; and O'Connor, Annette M., "Rapid Tagging and Reporting for Functional Language Extraction in Scientific Articles" (2017). Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters. 111.