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Document clustering is a popular topic in data mining and information retrieval. Most models and methods for this problem are based on computing the similarity between pair documents modeled in a space of all terms, or a new feature space obtained by applying a topic modeling technique for a given corpus. In this paper, we regard these two ideas as clustering on term feature and on semantic feature,...
Driver distraction has been identified as one major cause of unsafe driving. The existing studies on cognitive distraction detection mainly focused on high-speed driving situations, but less on low-speed traffic in urban driving. This paper presents a method for the detection of driver cognitive distraction at stop-controlled intersections and compares its feature subsets and classification accuracy...
This paper proposed a graph-based clustering approach for gene expression data. The new method is based on regulatory network graph obtained from gene expression data. Clustering is performed based on the topological features of the graph which characterizes the regulatory relationships between genes, which is different from the conventional methods that simply group genes with similar gene expression...
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