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Sentence Similarity Measures for Fine-Grained Estimation of Topical Relevance in Learner Essays

Published version
Peer-reviewed

Type

Conference Object

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Authors

Rei, Marek 
Cummins, Ronan 

Abstract

We investigate the task of assessing sentence-level prompt relevance in learner essays. Various systems using word overlap, neural embeddings and neural compositional models are evaluated on two datasets of learner writing. We propose a new method for sentence-level similarity calculation, which learns to adjust the weights of pre-trained word embeddings for a specific task, achieving substantially higher accuracy compared to other relevant baselines.

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Keywords

Journal Title

https://aclweb.org/anthology/volumes/proceedings-of-the-11th-workshop-on-innovative-use-of-nlp-for-building-educational-applications/

Conference Name

11th Workshop on Innovative Use of NLP for Building Educational Applications

Journal ISSN

Volume Title

Publisher

ACL
Sponsorship
Cambridge Assessment (unknown)