Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/134671
Title: DOMAIN ADAPTATION FOR AUTOMATED ESSAY SCORING
Authors: PETER PHANDI
Keywords: essay scoring, domain adaptation, natural language processing
Issue Date: 27-Jul-2016
Source: PETER PHANDI (2016-07-27). DOMAIN ADAPTATION FOR AUTOMATED ESSAY SCORING. ScholarBank@NUS Repository.
Abstract: Automated Essay Scoring (AES) is an important task in Natural Language Processing. The research done by various commercial organizations has identi ed the features that correlate well with human scoring. They have built strong AES systems that achieve high agreement with human scoring based on these features. One of these commercial organizations, ETS, even uses their own AES system (erater) as a second rater for their high-stakes exams, GRE and TOEFL. However, most of these AES systems use prompt-speci c features. This means that each time a new prompt is introduced, a large number of essays need to be annotated as training data. This thesis gives an overview of the AES task and shows that domain adaptation can help an AES system to achieve high performance with a small number of annotated essays.
URI: http://scholarbank.nus.edu.sg/handle/10635/134671
Appears in Collections:Master's Theses (Open)

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