Sentence Similarity Measures for Fine-Grained Estimation of Topical Relevance in Learner Essays
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Peer-reviewed
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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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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
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ACL
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Cambridge Assessment (unknown)