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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Vydáno v:2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) s. 352 - 353
Hlavní autoři: Dubnicek, Ryan, Kudeki, Deren
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2021
Témata:
Data mining
Data models
digital libraries
Feature extraction
HathiTrust
HTRC Extracted Features Dataset
Libraries
text and data mining
Tutorials
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Shrnutí: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