A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data

1 code implementation • 12 Jun 2021 • Jinghui Lu, Maeve Henchion, Ivan Bacher, Brian Mac Namee

While with the recent emergence of BERT, deep learning language models can achieve reasonably good performance in document classification with few labelled instances, there is a lack of evidence in the utility of applying BERT-like models on long document classification.

Classification Document Classification +1

Diverging Divergences: Examining Variants of Jensen Shannon Divergence for Corpus Comparison Tasks

no code implementations • LREC 2020 • Jinghui Lu, Maeve Henchion, Brian Mac Namee

Jensen-Shannon divergence (JSD) is a distribution similarity measurement widely used in natural language processing.

Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text Datasets

2 code implementations • 4 Oct 2019 • Jinghui Lu, Maeve Henchion, Brian Mac Namee

Active learning has been shown to be an effective way to alleviate some of the effort required in utilising large collections of unlabelled data for machine learning tasks without needing to fully label them.

Active Learning BIG-bench Machine Learning +1