Introduction to and Hands-On Use Cases with HathiTrust Research Center's Extracted Features 2.0 Dataset

This tutorial will introduce attendees to the HathiTrust Research Center's Extracted Features Dataset, and demo new data fields and functionality introduced in the latest version, 2.0. Generated from the over 17 million volumes in the HathiTrust Digital Library, the EF 2.0 Dataset supports text...

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Bibliographic Details
Published in:	2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) pp. 352 - 353
Main Authors:	Dubnicek, Ryan, Kudeki, Deren
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.09.2021
Subjects:	Data mining Data models digital libraries Feature extraction HathiTrust HTRC Extracted Features Dataset Libraries text and data mining Tutorials
Online Access:	Get full text
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Summary:	This tutorial will introduce attendees to the HathiTrust Research Center's Extracted Features Dataset, and demo new data fields and functionality introduced in the latest version, 2.0. Generated from the over 17 million volumes in the HathiTrust Digital Library, the EF 2.0 Dataset supports text and data mining methods while still adhering to a public domain, restriction-free data model. This tutorial will introduce the EF 2.0 Dataset, the key concepts behind its creation, and hands-on research use cases for the dataset using IPython notebooks.
DOI:	10.1109/JCDL52503.2021.00073