All Outputs (3)

Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. (2019)
Journal Article
CHEN, Y.Y., WIRATUNGA, N. and LOTHIAN, R. 2020. Integrating selection-based aspect sentiment and preference knowledge for social recommender systems. Online information review [online], 44(2), pages 399-416. Available from: https://doi.org/10.1108/OIR-02-2017-0066

Purpose: Recommender system approaches such as collaborative and content-based filtering rely on user ratings and product descriptions to recommend products. More recently, recommender system research has focussed on exploiting knowledge from user-ge... Read More about Integrating selection-based aspect sentiment and preference knowledge for social recommender systems..

Contextual sentiment analysis for social media genres. (2016)
Journal Article
MUHAMMAD, A., WIRATUNGA, N. and LOTHIAN, R. 2016. Contextual sentiment analysis for social media genres. Knowledge-based systems [online], 108, pages 92-101. Available from: https://doi.org/10.1016/j.knosys.2016.05.032

The lexicon-based approaches to opinion mining involve the extraction of term polarities from sentiment lexicons and the aggregation of such scores to predict the overall sentiment of a piece of text. It is typically preferred where sentiment labelle... Read More about Contextual sentiment analysis for social media genres..

Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. (2011)
Journal Article
REGNIER-COUDERT, O., MCCALL, J., LOTHIAN, R., LAM, T., MCCLINTON, S. and N'DOW, J. 2012. Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers. Artificial intelligence in medicine [online], 55(1), pages 25-35. Available from: https://doi.org/10.1016/j.artmed.2011.11.003

Prediction of prostate cancer pathological stage is an essential step in a patient's pathway. It determines the treatment that will be applied further. In current practice, urologists use the pathological stage predictions provided in Partin tables t... Read More about Machine learning for improved pathological staging of prostate cancer: a performance comparison on a range of classifiers..