We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
It has already been shown how Artificial Neural Networks (ANNs) can be incorporated into probabilistic models. In this paper we review some of the approaches which have been prop...
Our research focuses on analysing human activities according to a known behaviorist scenario, in case of noisy and high dimensional collected data. The data come from the monitori...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...