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All Outputs (3)

Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models (2017)
Book Chapter
Smith, E. M., Smith, J., Legg, P., & Francis, S. (2017). Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models. In F. Chao, S. Schockaert, & Q. Zhang (Eds.), Advances in Computational Intelligence Systems: UKCI 2017 (191-202). Springer Cham

The ability to predict future states is fundamental for a wide variety of applications, from weather forecasting to stock market analysis. Understanding the related data attributes that can influence changes in time series is a challenging task that... Read More about Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models.

RicherPicture: Semi-automated cyber defence using context-aware data analytics (2017)
Presentation / Conference
Erola, A., Agrafiotis, I., Happa, J., Goldsmith, M., Creese, S., & Legg, P. (2017, June). RicherPicture: Semi-automated cyber defence using context-aware data analytics. Paper presented at International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA 2017), London

In a continually evolving cyber-threat landscape, the detection and prevention of cyber attacks has become a complex task. Technological developments have led organisations to digitise the majority of their operations. This practice, however, has its... Read More about RicherPicture: Semi-automated cyber defence using context-aware data analytics.

Glyph visualization: A fail-safe design scheme based on quasi-hamming distances (2017)
Journal Article
Legg, P. A., Legg, P., Maguire, E., Walton, S., & Chen, M. (2017). Glyph visualization: A fail-safe design scheme based on quasi-hamming distances. IEEE Computer Graphics and Applications, 37(2), 31-41. https://doi.org/10.1109/MCG.2016.66

© 1981-2012 IEEE. In many spatial and temporal visualization applications, glyphs provide an effective means for encoding multivariate data. However, because glyphs are typically small, they are vulnerable to various perceptual errors. This article i... Read More about Glyph visualization: A fail-safe design scheme based on quasi-hamming distances.