Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches

R. Jensen and Q. Shen. Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough Based Approaches. IEEE Transactions on Knowledge and Data Engineering, 16(12): 1457-1471. 2004.

Evolutionary approaches to fuzzy modelling for classification

M. Galea, Q. Shen and J. Levine. Evolutionary approaches to fuzzy modelling. Knowledge Engineering Review, 19(1):27-59, 2004.

Computational Intelligence and Feature Selection : Rough and Fuzzy Approaches

Computational Intelligence and Feature Selection provides a high level audience with both the background and fundamental ideas behind feature selection with an emphasis on those techniques based on rough and fuzzy sets, including their hybridizations. It introduces set theory, fuzzy set theory, rough set theory, and fuzzy-rough set theory, and illustrates the power and efficacy of the feature selections described through the use of real-world applications and worked examples. Program files implementing major algorithms covered, together with the necessary instructions and datasets, are available on the Web.

African Studies and the Postcolonial Challenge

Abrahamsen, Rita, 'African Studies and the Postcolonial Challenge', African Affairs (2003) 102(407) pp.189-210 RAE2008

Constructing Enemies: 'Islamic Terrorism' in Political and Academic Discourse

Jackson, Richard, (2007) 'Constructing Enemies: 'Islamic Terrorism' in Political and Academic Discourse', Government and Opposition, 42(3) pp.394-426 RAE2008

New Approaches to Social History. Myth, Memory and Place: Monmouth and Bath 1750-1900

Borsay, Peter, 'New Approaches to Social History. Myth, Memory and Place: Monmouth and Bath 1750-1900', Journal of Social History (2006) 39(3) pp.867-889 RAE2008