To identify the societal risk category of the posts of Tianya Club, several studies are carried out toward the posts of Tianya Club. With 2-month manually risk labeled new posts published during December of 2011 to January of 2012, statistical analysis of posts is conducted at first. Later, similarity analysis of posts from one risk category, different risk categories and published on different...

Support Vector Machines represent a new approach to pattern classification developed from the theory of Structural Risk Minimization[1]. In this paper, we present an investigation into the application of Support Vector Machines’ to the confidence measurement problem in speech recognition. Specifically, based on the results from an initial decoding of an utterance during speech recognition, we d...

This paper introduces the Clifford Support Vector Machines as a generalization of the realand complexvalued Support Vector M* chines. The major advantage of this approach is that one requires only one CSVM which can admit multiple multivector inputs and it can carry multi-class classification. In contrast one would need many real valued SVMs for a multi-class problem which is time consuming.