Campus Units

English, Industrial and Manufacturing Systems Engineering, Veterinary Diagnostic and Production Animal Medicine, Virtual Reality Applications Center

Document Type

Conference Proceeding

Publication Version

Published Version

Publication Date

12-15-2017

Journal or Book Title

Proceedings of the 6th International Workshop on Mining Scientific Publications (WOSP 2017)

First Page

34

Last Page

39

DOI

10.1145/3127526.3127533

Conference Title

ICPE ACM/SPEC International Conference on Performance Engineering

Conference Date

December 15, 2017

City

Toronto, ON, Canada

Abstract

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.

Comments

This proceeding is published as Ramezani, M., V. Kalivarapu, S. B. Gilbert, S. Huffman, E. Cotos, and A. O'Conner. "Rapid Tagging and Reporting for Functional Language Extraction in Scientific Articles." In Proceedings of the 6th International Workshop on Mining Scientific Publications, pp. 34-39. ACM, 2017. doi: 10.1145/3127526.3127533. Posted with permission.

Rights

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Copyright Owner

The Authors

Language

en

File Format

application/pdf

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