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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
TU Dublin Research Portal
Dataset
License: CC BY SA
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Smith_ISL_NMF_V1.0.0

Authors: Smith, Robert G.;

Smith_ISL_NMF_V1.0.0

Abstract

This is an dataset of Irish Sign Language (ISL) Non-Manual Feature data. # Cite: Robert G. Smith, (2023). Exploiting Association Rules Mining to Inform the Use of Non-Manual Features in Sign Language Processing. PhD Dissertation. Technological University Dublin. Dublin, Ireland. Robert G. Smith. (2024). TUD-RSmith/PhD-Appendices: First release - Smith_NMF Dataset V1.0.0 (Smith_NMF_v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.10639554 [![DOI](https://zenodo.org/badge/560578153.svg)](https://zenodo.org/doi/10.5281/zenodo.10639533) ## AboutThis dataset was published in the appendix of a PhD Dissertation by Robert G. Smith robert.smith@tudublin.ie Cite: Robert G. Smith, Exploiting Association Rules Mining to Inform the Use of Non-Manual Features in Sign Language Processing, PhD Dissertation, Technological University Dublin, Ireland, 2023. The dataset is comprised of several smaller datasets: ### Appendix C [Appendix C](https://github.com/TUD-RSmith/PhD-Appendices/tree/main/AppendixC-most_frequent_lexical_items_in_the_SOI_corpus)lexical frequency list (see: Smith, R. G. & Hofmann, M., (2020). A Lexical Frequency Analysis of Irish Sign Language. TEANGA, the Journal of the Irish Association for Applied Linguistics, 11, 18–47. https://doi.org/10.35903/teanga.v11i1.162) ### Appendix D[Appendix D](https://github.com/TUD-RSmith/PhD-Appendices/tree/main/AppendixD-all_association_rules)Association rules. This was the main output of the PhD work. See the dissertation for method. (this dir includes filtered and unfiltered data) ### Appendix E[Appendix E](https://github.com/TUD-RSmith/PhD-Appendices/tree/main/AppendixE-Datasets)Datasets used to generate association rules ### Appendix F[Appendix F](https://github.com/TUD-RSmith/PhD-Appendices/tree/main/AppendixF-Source_code)Source code (R) used to generate rules listed in Appendix D ### Appendix G[Appendix G](https://github.com/TUD-RSmith/PhD-Appendices/tree/main/AppendixG-integrity_test)Source code (R) used for integrity testing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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