A Taxonomy for Deep Learning in Natural Language Processing

dc.contributor.author Landolt, Severin
dc.contributor.author Wambsganss, Thiemo
dc.contributor.author Söllner, Matthias
dc.date.accessioned 2020-12-24T19:11:40Z
dc.date.available 2020-12-24T19:11:40Z
dc.date.issued 2021-01-05
dc.description.abstract Despite a large number of available techniques around Deep Learning in Natural Language Processing (NLP), no holistic framework exists which supports researchers and practitioners to organise knowledge when designing, comparing and evaluating NLP applications. This paper addresses this lack of a holistic framework by developing a taxonomy for Deep Learning in Natural Language Processing. Based on a systematic literature review as proposed by Webster and Watson and vom Brocke et al. and the iterative taxonomy development process of Nickerson et al. we derived five novel dimensions and 38 characteristics based on a sample of 205 papers. Our research suggests, that a Deep Learning NLP approach can be distinguished by five dimensions which were partly derived from the CRISP-DM methodology: application understanding, data preparation, modeling, learning technique and evaluation. We, therefore, hope to provide guidance and support for researchers and practitioners when using Deep Learning for NLP to design, compare and evaluate NLP applications.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2021.129
dc.identifier.isbn 978-0-9981331-4-0
dc.identifier.uri http://hdl.handle.net/10125/70741
dc.language.iso English
dc.relation.ispartof Proceedings of the 54th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Data, Text and Web Mining for Business Analytics
dc.subject deep learning
dc.subject framework
dc.subject information systems
dc.subject natural language processing
dc.subject taxonomy
dc.title A Taxonomy for Deep Learning in Natural Language Processing
prism.startingpage 1061
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