We propose a novel type of document classification task that quantifies how much a given document (review) appreciates the target object using not binary polarity (good or bad) b...
We show that a classifier based on Gaussian mixture models (GMM) can be trained discriminatively to improve accuracy. We describe a training procedure based on the extended Baum-W...
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...
Extracting semantic relationships between entities from text documents is challenging in information extraction and important for deep information processing and management. This ...