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Automatically classifying academic conference into semantic topic promises improved academic search and browsing for users. Social tagging is an increasingly popular way of describing the topic of academic conference. However, no attention has been devoted to academic conference classification by making use of social tags. Motivated by this observation, this paper proposes a method which utilizes...
Segmentation of infrared image is very important in infrared image analysis. Support vector machine (SVM) approach is considered a good candidate because of its good generalization performance, especially when the number of training samples is very small and the dimension of feature space is very high. In this paper, a segmentation algorithm based on SVM for infrared image is presented. The algorithm...
Semi-supervised learning mechanism requires new feature selection methods to work on unlabeled samples. Traditional researches deal it with the help of ldquofilter-typerdquo semi-feature selection mechanism, which may not work well for classification tasks. Genetic algorithm is one of widely used ldquowrapper-typerdquo supervised feature selection methods. Here, we propose a novel genetic algorithm...
Kernel partial least squares method can obtain nonlinear novel features for further classification and other tasks, the dimension of extracted kernel space is usually very high, there still may contain irrelevant and redundant features, so using feature selection to select the most discriminative and informative features for classification or data analysis is important, but there are few attentions...
We propose a novel method to detect frequent and distinctive feature configuration on a class instance. Each neighborhood of a local feature is described by a list of nonzero indices, and generates a transaction. An efficient mining of frequent item sets algorithm is used to automatically find spatial configurations of local features occurring frequently on a class instance. These mined spatial configurations...
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