{"title":"介绍和动手用例与HathiTrust研究中心的提取特征2.0数据集","authors":"Ryan Dubnicek, Deren Kudeki","doi":"10.1109/JCDL52503.2021.00073","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Introduction to and Hands-On Use Cases with HathiTrust Research Center's Extracted Features 2.0 Dataset\",\"authors\":\"Ryan Dubnicek, Deren Kudeki\",\"doi\":\"10.1109/JCDL52503.2021.00073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":112400,\"journal\":{\"name\":\"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/JCDL52503.2021.00073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/JCDL52503.2021.00073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.