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With the development of Internet, the increasing volume of information posted on micro-blogging sites like Twitter necessitates the need for efficient information filtering. In conventional text classification problems, it is assumed that the feature vectors extracted from the available documents are sufficient to learn good classifiers. However, this conventional approach is not likely to work for...
In this paper, we analyze complex gaze tracking data in a collaborative task and apply machine learning models to automatically predict skill-level differences between participants. Specifically, we present findings that address the two primary challenges for this prediction task: (1) extracting meaningful features from the gaze information, and (2) casting the prediction task as a machine learning...
Rare category detection is the task of identifying examples from rare classes in an unlabeled data set. It is an open challenge in machine learning and plays key roles in real applications such as financial fraud detection, network intrusion detection, astronomy, spam image detection, etc. In this paper, we develop a new graph-based method for rare category detection named GRADE. It makes use of the...
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