The positive effect of adding subword information to word embeddings has been demonstrated for predictive models.
Corpus2graph is an open-source NLP-application-oriented tool that generates a word co-occurrence network from a large corpus.
Contrary to the traditional Bag-of-Words approach, we consider the Graph-of-Words(GoW) model in which each document is represented by a graph that encodes relationships between the different terms.
We investigate how machine learning models, specifically ranking models, can be used to select useful distractors for multiple choice questions.
Our system uses a logistic regression model to predict the likelihood of a student making a mistake while answering an exercise on Duolingo in all three language tracks - English/Spanish (en/es), Spanish/English (es/en) and French/English (fr/en).
SOTA for Language Acquisition on SLAM 2018
Seq2Seq based neural architectures have become the go-to architecture to apply to sequence to sequence language tasks.
This article describes the system that participated in the shared task on metaphor detection on the Vrije University Amsterdam Metaphor Corpus (VUA).
This paper presents an investigation of using a co-attention based neural network for source-dependent essay scoring.