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Open Access research which pushes advances in bionanotechnology

Strathprints makes available scholarly Open Access content by researchers in the Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS) , based within the Faculty of Science.

SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

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Classification of radical web text using a composite-based method

Owoeye, Kolade Olawande and Weir, George R. S. (2018) Classification of radical web text using a composite-based method. In: IEEE International Conference on Computational Science and Computational Intelligence, 2018-12-13 - 2018-12-15.

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    The spread of terrorism and extremism activities on the Internet has created the need for intelligence gathering via Web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult and time-consuming. In response to this challenge, an automated classification system called Composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a Web page. We implemented the framework on a set of extremist Web pages - a dataset that has been subjected to a manual classification process. Thereby, we developed a classification model on the data using the J48 decision algorithm, to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of the art, indicated a 96% success rate overall in classifying Web pages when matched against the manual classification.