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This paper introduces fuzzy support vector machines (FSVMs) for Japanese dependency analysis. Japanese dependency analysis based on support vector machines (SVMs) has been proposed and has achieved high accuracy. While regular SVMs try to find a decision hyperplane from two distinct classes of the input examples, FSVMs apply a fuzzy membership to each input example such that different examples can...
As increasing linked datasets are progressively published on the semantic Web, discovering the most similar entities in large linked datasets becomes crucial in many semantic applications. Conventional approaches usually draw upon either ontology taxonomy or relationships unilaterally. In this paper, we present a novel approach which utilizes node and link types together with the topology of semantic...
In many multimedia applications, some faults induce errors that are user-imperceptible and thus are acceptable. By not testing for these faults, the effective yield can be significantly increased based on the principle of error-tolerance. However, studies have shown that test patterns generated by a conventional ATPG procedure targeting only unacceptable faults also detect many acceptable faults,...
Previous trust mechanisms are mainly focused on reputational models based on explicit trust ratings. However, the large amount of system-provided and user-generated content published on Web is often ignored. These information is very important for providing more accurate, fine-grained and efficient trust management. In this paper, we propose a content-based trust mechanism and introduce trust reasoning...
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