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regions and words. The third and fourth approaches are based on segmenting the images into homogeneous regions. Both of these approaches rely on a clustering algorithm to learn the association between visual features and keywords. The clustering task is not trivial as it involves clustering a very high-dimensional and sparse
title, keyword and link text information to represent the website. Heterogeneous classifiers are then built based on these different features. We propose a principled ensemble classification algorithm to combine the predicted results from different phishing detection classifiers. Hierarchical clustering technique has been
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.