Cargando…
Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm
We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051716/ https://www.ncbi.nlm.nih.gov/pubmed/27706234 http://dx.doi.org/10.1371/journal.pone.0163623 |
_version_ | 1782458129994219520 |
---|---|
author | Loach, James C. Wang, Jinzhao |
author_facet | Loach, James C. Wang, Jinzhao |
author_sort | Loach, James C. |
collection | PubMed |
description | We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and algorithms. Our algorithm is applicable to any scheduling task where nodes have intrinsic differences in importance and must be visited in topological order. |
format | Online Article Text |
id | pubmed-5051716 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50517162016-10-27 Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm Loach, James C. Wang, Jinzhao PLoS One Research Article We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and algorithms. Our algorithm is applicable to any scheduling task where nodes have intrinsic differences in importance and must be visited in topological order. Public Library of Science 2016-10-05 /pmc/articles/PMC5051716/ /pubmed/27706234 http://dx.doi.org/10.1371/journal.pone.0163623 Text en © 2016 Loach, Wang http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Loach, James C. Wang, Jinzhao Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title | Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title_full | Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title_fullStr | Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title_full_unstemmed | Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title_short | Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm |
title_sort | optimizing the learning order of chinese characters using a novel topological sort algorithm |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051716/ https://www.ncbi.nlm.nih.gov/pubmed/27706234 http://dx.doi.org/10.1371/journal.pone.0163623 |
work_keys_str_mv | AT loachjamesc optimizingthelearningorderofchinesecharactersusinganoveltopologicalsortalgorithm AT wangjinzhao optimizingthelearningorderofchinesecharactersusinganoveltopologicalsortalgorithm |