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In this paper we present a study on music mood classification by using only lyrics information. Specially considering the Chinese songs, the Chinese word-segmentation has caused intolerable errors and inadequate use of lyrics information. Our work proposes to use bag-of-character features instead of bag-of-word features to avoid the word segmentation error, which makes the classification more inaccurate...
Support vector machine is a novel machine learning method in recent years, the SVM with RBF is widely used in pattern recognition because of its good learning properties. If Support vector machine is applied into risk assessment, it will get better assessment results. But the performance of RBF-SVM is influenced greatly by the parameter of C and sigma. The principle of SVM and the essence of kernel...
In this paper, a kernel-based learning algorithm, kernel rank, is presented for improving the performance of semantic concept detection. By designing a classifier optimizing the receiver operating characteristic (ROC) curve using kernel rank, we provide a generic framework to optimize any differentiable ranking function using effective smoothing functions. kernel rank directly maximizes a 1-D quality...
With the proliferation of camera phones, new information retrieval applications will emerge. The image of a scene captured by a camera phone can be a query to a remote server to identify the scene and return relevant information. But unconstrained scene identification is an open problem. In this paper, we propose a discriminative measure to rank image patterns sampled from target scene classes. Support...
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