Cross-lingual complex word identification with multitask learning

Bingel, Joachim; Bjerva, Johannes

doi:10.18653/v1/w18-0518

Cited by 11 publications

(15 citation statements)

References 15 publications

(8 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(Alfter & Volodina, 2018) Others NLP Others This paper present work-in-progress where we investigate the usefulness of previously created word lists to the task of single-word lexical complexity analysis and prediction of the complexity level for learners of Swedish as a second language. (Bingel & Bjerva, 2018) Others NLP…”

Section: (Vajjala and Lucic 2018)mentioning

confidence: 99%

Text mining in education

Mello

Andre

Pinheiro

et al. 2019

WIREs Data Min & Knowl

138

View full text Add to dashboard Cite

The explosive growth of online education environments is generating a massive volume of data, specially in text format from forums, chats, social networks, assessments, essays, among others. It produces exciting challenges on how to mine text data in order to find useful knowledge for educational stakeholders. Despite the increasing number of educational applications of text mining published recently, we have not found any paper surveying them. In this line, this work presents a systematic overview of the current status of the Educational Text Mining field. Our final goal is to answer three main research questions: Which are the text mining techniques most used in educational environments? Which are the most used educational resources? And which are the main applications or educational goals? Finally, we outline the conclusions and the more interesting future trends. This article is categorized under: Application Areas > Education and Learning Ensemble Methods > Text Mining

show abstract

Section: (Vajjala and Lucic 2018)mentioning

confidence: 99%

Text mining in education

Mello

Andre

Pinheiro

et al. 2019

WIREs Data Min & Knowl

138

View full text Add to dashboard Cite

show abstract

“…CoastalCPH describe systems developed for multilingual and cross-lingual domains for the binary and probabilistic classification tasks (Bingel and Bjerva, 2018). Unlike most systems, they have focused mainly on German, Spanish, and French datasets in order to investigate if multitask learning can be applied to the cross-lingual CWI task.…”

Section: Shared Task Systemsmentioning

confidence: 99%

A Report on the Complex Word Identification Shared Task 2018

Yimam¹,

Biemann²,

Malmasi³

et al. 2018

Proceedings of the Thirteenth Workshop on Innovative Use of NLP For Building Educational Applications

View full text Add to dashboard Cite

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 and 11 of them wrote system description papers that are referred to in this report and appear in the BEA workshop proceedings.

show abstract

“…Deep neural network learning is widely used for graphic image processing [24]. Deep learning of artificial neural networks, which was first used in 2006 has taken an important place in computational linguistics [25]. To date, neural network learning methods have been developed allowing to quickly and efficiently train networks consisting of one hundred or more layers [26].…”

Section: Literature Review and Abstractearch Problem Statementmentioning

confidence: 99%