Computational assessment of long-term memory structures from SDA-M related to action sequences.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2019
2019
Historique:
received:
21
08
2018
accepted:
02
02
2019
entrez:
23
2
2019
pubmed:
23
2
2019
medline:
19
11
2019
Statut:
epublish
Résumé
Assistance systems should be able to adapt to individual task-related skills and knowledge. Structural-dimensional analysis of mental representations (SDA-M) is an established method for retrieving human memory structures related to specific activities. For this purpose, SDA-M involves a semi-automatized survey of users (the "split procedure"), which yields data about users' associations between action representations in long-term memory. Up to now this data about associations has commonly been clustered and visualized by SDA-M software in the form of dendrograms that can be used by human experts as a tool to (manually) assess users' individual expertise and identify potential issues with respect to predefined action sequences. This article presents new algorithmic approaches for automatizing the process of assessing task-related memory structures based on SDA-M data to predict probable errors in action sequences. This automation enables direct integration into technical systems, e.g. user-adaptive assistance systems. An evaluation study has compared the automatized computational assessments to predictions made by human scholars based on visualizations of SDA-M data. The different algorithms' outputs matched human experts' manual assessments in 84% to 86% of the test cases.
Identifiants
pubmed: 30794606
doi: 10.1371/journal.pone.0212414
pii: PONE-D-18-24642
pmc: PMC6386273
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0212414Commentaires et corrections
Type : ErratumIn
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Front Psychol. 2016 Jan 08;6:1981
pubmed: 26779089
Science. 2017 Feb 3;355(6324):489
pubmed: 28154052
Clin Rehabil. 2018 Jan;32(1):103-115
pubmed: 28719981
Front Comput Neurosci. 2013 Sep 18;7:127
pubmed: 24065915
Psychol Res. 2012 Nov;76(6):768-76
pubmed: 22075763
PLoS One. 2015 Feb 25;10(2):e0118219
pubmed: 25714486
Front Comput Neurosci. 2015 Oct 09;9:126
pubmed: 26500533
Psychon Bull Rev. 2001 Dec;8(4):629-47
pubmed: 11848582
Front Public Health. 2016 Feb 18;4:24
pubmed: 26925398
Hum Mov Sci. 2007 Aug;26(4):525-54
pubmed: 17698232
Psychol Rev. 2004 Oct;111(4):1036-60
pubmed: 15482072
Front Hum Neurosci. 2014 May 22;8:328
pubmed: 24904368
PLoS One. 2016 Jul 07;11(7):e0158832
pubmed: 27387139
Clin Rehabil. 2007 Sep;21(9):822-32
pubmed: 17875562
Neurosci Lett. 2006 Jan 2;391(3):77-81
pubmed: 16266782
Prog Brain Res. 2009;174:231-50
pubmed: 19477343