Influential Article Review - Development of an Advanced Digital Extraction Method

Authors

  • Ervin Haynes
  • Russell Davis
  • Clayton Huff

Keywords:

Entity extraction, Machine learning, Precision of extraction, Text analytics, Natural language processing

Abstract

This paper examines technology. We present insights from a highly influential paper. Here are the highlights from this paper: The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and applications. The improvement of entities extraction precision also increases the relationships extraction precision, which is particularly important in certain domains (such as intelligence systems, social networking, genetic studies, healthcare, etc.). These increases in precision improve the end users’ experience quality in using the extraction system because it lowers the time that users spend for training the system and correcting outputs, focusing more on analyzing the information extracted to make better data-driven decisions. For our overseas readers, we then present the insights from this paper in Spanish, French, Portuguese, and German.

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Published

2019-12-13

How to Cite

Haynes, E., Davis, R., & Huff, C. (2019). Influential Article Review - Development of an Advanced Digital Extraction Method. Journal of Strategic Innovation and Sustainability, 14(7). Retrieved from https://mail.articlegateway.com/index.php/JSIS/article/view/3427

Issue

Section

Articles