Abstract:In real time applications related to social media, conventional anomaly detection techniques are not applicable as the accuracy is degraded due to higher dimensionality thereby hampering these applications leading to cyber threat. This paper focuses on an approach that can select feature subspaces of social media which have meaningful information and thereby conduct anomaly detection in the projected subspace correspondingly. Major goal is to maintain the accuracy of detection in the circumstance of high dimen… Show more
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