@inproceedings{ac5d3bc9244f41c796534c6d9c2f4f10,
title = "Tikkoun sofrim: A Webapp for personalization and adaptation of crowdsourcing transcriptions",
abstract = "This paper briefly describes aspects of the Tikkoun Sofrim crowdsourcing webApp. Tikkoun Sofrim is a webApp which allows users to correct automatic transcriptions (AT) done by an AI Neural network engine. We look at the background of the crowdsourcing phenomenon in the use of automatic transcription of digital humanities documents. System structure is briefly described. We then examine personalization and adaption aspects at different stages of the user/application lifecycle Finally, we briefly outline future challenges.",
keywords = "Crowdsourcing, Digital humanities, Midrash tanhuma, Transcription",
author = "Wecker, \{Alan J.\} and Uri Schor and Dror Elovits and Ezra, \{Daniel Stoekl Ben\} and Vered Raziel-Kretzmer and Tsvi Kuflik and Avigail Ohali and Moshe Lavee and Lily Signoret",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright is held by the owner/author(s).; 27th ACM International Conference on User Modeling, Adaptation and Personalization, UMAP 2019 ; Conference date: 09-06-2019 Through 12-06-2019",
year = "2019",
month = jun,
day = "6",
doi = "10.1145/3314183.3324972",
language = "American English",
series = "ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization",
pages = "109--110",
booktitle = "ACM UMAP 2019 Adjunct - Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization",
}