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Automatic Essay Scoring of Swedish Essays using Neural Networks
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

We propose a neural network-based system for automatically grading essays written in Swedish. Previous system either relies on laboriously crafted features extracted by human experts or are limited to essays written in English. By using different variations of Long Short-Term Memory (LSTM) networks, our system automatically learns the relation between Swedish high-school essays and their assigned score. Using all of the intermediate states from the LSTM network proved to be crucial in order to understand the essays. Furthermore, we evaluate different ways of representing words as dense vectors which ultimately have a substantial effect on the overall performance. We compare our results to the ones achieved by the first and previously only automatic essay scoring system designed for the Swedish language. Although no state-of-the-art performance is reached, indication of the potential from a neural based grading system is found.

Place, publisher, year, edition, pages
2018. , p. 40
Keywords [en]
automatic essay scoring
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-352505OAI: oai:DiVA.org:uu-352505DiVA, id: diva2:1213688
Educational program
Master Programme in Statistics
Supervisors
Examiners
Available from: 2018-06-19 Created: 2018-06-05 Last updated: 2018-06-19Bibliographically approved

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Probability Theory and Statistics

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf