Ngo Van Linh

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Classification on networked data plays an important role in many problems such as web page categorization, classification of bibliographic information network, etc... Most classification algorithms on information networks work by iteratively propagating information through network graphs. One important issue concerning iterative classifiers is that false(More)
Automatic text summarization plays an important role in information retrieval and text mining. Furthermore, it provides an useful solution to the information overload problem. In this paper, we propose a simplicial NMF-based unsupervised generic document summarization method which can inherit some advantages of simplicial NMF such as easy interpretability,(More)
Document clustering has become an increasingly important technique for unsupervised document organization, automatic topic extraction, and fast information retrieval or filtering. This paper proposes a Dirichlet process mixture (DPM) model approach to clustering directional data based on the von Mises-Fisher (vMF) distribution, which arises naturally for(More)
Document classifications is essential to information retrieval and text mining. In real life, unlabeled data is readily available whereas labeled ones are often laborious, expensive and slow to obtain. This paper proposes a novel Document Classification approach based on semi-supervised vMF mixture model on document manifold, called Laplacian regularized(More)
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