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ZENODO
Dataset . 2014
License: CC BY
Data sources: Datacite
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/
ZENODO
Dataset . 2014
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/
ZENODO
Dataset . 2014
License: CC BY
Data sources: ZENODO
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Classification Of Word Levels With Usage Frequency, Expert Opinions And Machine Learning

Authors: Guzey, Onur; Sohsah, Gihad ; Unal, Muhammed;

Classification Of Word Levels With Usage Frequency, Expert Opinions And Machine Learning

Abstract

This dataset includes classification of English words according to CEFR language levels. It can be used in various educational applications including determining levels of text that is appropriate for students learning English. For each word, part-of-speech, the word lemma and usage frequency is provided. For words that have no survey results, a machine learning based methodology is used to predict levels. These predictions are also included as a separate file. This data is released as part of the submission process to British Journal of Educational Technology Special Issue on Open Data. The included readme.pdf file contains a detailed description of data.

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Keywords

educational data mining, word levels, machine learning

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citations
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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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