This paper proposes a framework for semi-supervised structured output learning (SOL), specifically for sequence labeling, based on a hybrid generative and discriminative approach...
In this paper, we proposed a novel probabilistic generative model to deal with explicit multiple-topic documents: Parametric Dirichlet Mixture Model(PDMM). PDMM is an expansion of...
String transformation, which maps a source string s into its desirable form t , is related to various applications including stemming, lemmatization, and spelling correction. The ...
We examine the problem of content selection in statistical novel sentence generation. Our approach models the processes performed by professional editors when incorporating materi...
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...