19 citations · 20 across the 4 of their papers we have counts for
4 papers
Multi-task Learning of Negation and Speculation for Targeted Sentiment Classification
Andrew Moore, Jeremy Barnes
The majority of work in targeted sentiment analysis has concentrated on finding better methods to improve the overall results. Within this paper we show that these models are not r…
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
Henry B. Moss, Andrew Moore, David S. Leslie +1
We present FIESTA, a model selection approach that significantly reduces the computational resources required to reliably identify state-of-the-art performance from large collectio…
Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis
Andrew Moore, Paul Rayson
Lack of repeatability and generalisability are two significant threats to continuing scientific development in Natural Language Processing. Language models and learning methods are…
Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter: predicting sentiment from financial news headlines
Andrew Moore, Paul Rayson
This paper describes our participation in Task 5 track 2 of SemEval 2017 to predict the sentiment of financial news headlines for a specific company on a continuous scale between -…