Proceedings of the Thirteenth Workshop on Innovative Use of NLP For Building Educational Applications 2018
DOI: 10.18653/v1/w18-0507
|View full text |Cite
|
Sign up to set email alerts
|

A Report on the Complex Word Identification Shared Task 2018

Abstract: We report the findings of the second Complex Word Identification (CWI) shared task organized as part of the BEA workshop colocated with NAACL-HLT'2018. The second CWI shared task featured multilingual and multi-genre datasets divided into four tracks: English monolingual, German monolingual, Spanish monolingual, and a multilingual track with a French test set, and two tasks: binary classification and probabilistic classification. A total of 12 teams submitted their results in different task/track combinations … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
107
0
1

Year Published

2019
2019
2023
2023

Publication Types

Select...
5
2
1

Relationship

0
8

Authors

Journals

citations
Cited by 97 publications
(108 citation statements)
references
References 32 publications
0
107
0
1
Order By: Relevance
“…word length and frequency) [17]. Among these markers, especially frequency has been treated in detail and ascertained multiple times to have a strong relation to word difficulty based on a variety of evaluation methods ranging from decision trees to deep recurrent neural networks [18], [19] and not only in English but other languages as well [20], [21]. This relation is possibly due to the fact that frequent use of a word or word-family can enhance peoples' familiarity to it (e.g.…”
Section: Background and Related Workmentioning
confidence: 99%
“…word length and frequency) [17]. Among these markers, especially frequency has been treated in detail and ascertained multiple times to have a strong relation to word difficulty based on a variety of evaluation methods ranging from decision trees to deep recurrent neural networks [18], [19] and not only in English but other languages as well [20], [21]. This relation is possibly due to the fact that frequent use of a word or word-family can enhance peoples' familiarity to it (e.g.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Simplification can be targeted by identifying complex words (e.g. Paetzold and Specia, 2016;Yimam et al, 2018), and then performing lexical simplification (e.g. Glavaš andŠtajner, 2015;Glavaš and Vulić, 2018;Horn et al, 2014;Kriz et al, 2018).…”
Section: Related Workmentioning
confidence: 99%
“…São vários os trabalhos futuros que antevemos para essa pesquisa: avaliar outros métodos de AM para a tarefa além da Regressão Logística, por exemplo,Árvores de decisão, Random Forest, Bagging, Boosting, SVM; incrementar o número de features da abordagem baseada em AM, usando tamanho das palavras, número de sílabas, número de sentidos e sinônimos em tesauros; além de avaliar modelos avançados de deep learning, que são uma tendência daárea para a tarefa. Yimam, S. M., Biemann, C., Malmasi, S., Paetzold, G. H., Specia, L.,Štajner, S., Tack, A., and Zampieri, M. (2018). A report on the complex word identification shared task 2018. arXiv preprint arXiv:1804.09132.…”
Section: Conclusões E Trabalhos Futurosunclassified
“…There are some tools for Brazilian Portuguese such as the Flesch Index [30], which is adapted for Portuguese and used in the Microsoft Word, and mainly the Coh-Metrix-Port and AIC, developed in the PorSimples project [3], whose goal is to simplify Web texts for people with poor literacy levels. These tools, however, do not meet the needs of educators in the classroom: there are no classifiers able to discriminate the level of complexity of each year focus of this study -3rd to 7th years, using metrics of the many language levels.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation