Chapter 2. HAMLET: Neural-Net-Powered Prototypes for Library Discovery

Authors

  • Andromeda Yelton

Abstract

Chapter 2 of Library Technology Reports (vol. 55, no. 1), "HAMLET: Neural-Net-Powered Prototypes for Library Discovery"

In this chapter, contributing author Andromeda Yelton discusses HAMLET (How about Machine Learning Enhancing Theses?), a machine learning system that Yelton created. It contains three different prototypes: a recommendation engine, an oracle file uploader, and a literature review buddy. Throughout this piece, she informs readers of neural-net-powered machine learning—what it is and how she used it to create HAMLET—and also discusses the benefits and potential problems associated with such systems. She ends the chapter looking toward the future of this technology and what it means for libraries.

Author Biography

Andromeda Yelton

Andromeda Yelton (https://andromedayelton.com) is a software engineer and librarian. Currently, she is at the Berkman Klein Center. She has written code for the MIT Libraries, the Wikimedia Foundation, and more. She has written, spoken, and taught internationally on a variety of library technology subjects. She is Past President of the Library & Information Technology Association.

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Published

2018-12-28

Issue

Vol. 55 No. 1 (2019): January

Section

Chapters