Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...

Text categorization is an important research area and has been receiving much attention due to the growth of the on-line information and of Internet. Automated text categorization is generally cast as a multi-class classification problem. Much of previous work focused on binary document classification problems. Support vector machines (SVMs) excel in binary classification, but the elegant theor...

Many existing researches employ one-vs-others approach to decompose a multi-label classification problem into a set of 2-class classification problems, one for each class. This approach is valid in traditional single-label classification. However, it incurs training inconsistency in multi-label classification, because a multi-label data point could belong to more than one class. In this work, w...

Recent progress in the development of techniques to optimize large-scale classification problems has extended the use of multi-class classification. Specifically the use of multi-class classification algorithms when the dataset is to large to fit into limited memory available of most computers. The most prominent algorithms used today solve the multi-class classification problem through an opti...

Many existing approaches employ one-vs-rest method to decompose a multi-label classification problem into a set of 2class classification problems, one for each class. This method is valid in traditional single-label classification, it, however, incurs training inconsistency in multi-label classification, because in the latter a data point could belong to more than one class. In order to deal wi...

A spectral feature selection scheme is proposed for multi-class automated rock recognition from real world drilling data using Gaussian Process classification. This work is part of a larger project aimed at surface mine automation. The motivation for this research is to investigate which combination of drilling data measurements is most relevant for rock recognition. We conduct feature selectio...