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

arXiv: https://arxiv.org/abs/1606.03144 · HTML: https://mlsanity.com/paper/1606.03144/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Jun 2016.

## Built on by (most cited first, 2 of 2)

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## Abstract (arXiv)

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.