Search Results for author:
Found 12 papers, 3 papers with code
The Construction and Evaluation of the LEAFTOP Dataset of Automatically Extracted Nouns in 1480 Languages
The claims to novelty are: the use of a Koine Greek New Testament as the source language; using a fully-annotated manually-created grammatically parse of the source text; a custom scraper for texts in the target languages; a new metric for language similarity; a novel strategy for evaluation on low-resource languages.
Demonstrating the Reliability of Self-Annotated Emotion Data
Vent is a specialised iOS/Android social media platform with the stated goal to encourage people to post about their feelings and explicitly label them.
Query Focused Multi-document Summarisation of Biomedical Texts: Macquarie Universiy and the Australian National University at BioASQ8b
This paper presents the participation of Macquarie University and the Australian National University for Task B Phase B of the 2020 BioASQ Challenge (BioASQ8b).
Query Focused Multi-document Summarisation of Biomedical Texts
This paper presents the participation of Macquarie University and the Australian National University for Task B Phase B of the 2020 BioASQ Challenge (BioASQ8b).
Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b
Task B Phase B of the 2019 BioASQ challenge focuses on biomedical question answering.
Overview of the 2019 ALTA Shared Task: Sarcasm Target Identification
We present an overview of the 2019 ALTA shared task.
Towards the Use of Deep Reinforcement Learning with Global Policy For Query-based Extractive Summarisation
Supervised approaches for text summarisation suffer from the problem of mismatch between the target labels/scores of individual sentences and the evaluation score of the final summary.
Automated text summarisation and evidence-based medicine: A survey of two domains
We envision that this survey will serve as a first resource for the development of future operational text summarisation techniques for EBM.
