We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Abstract. Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, th...
Roberto Basili, Marco Cammisa, Alessandro Moschitt...
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...