Abstract. We investigate a generative latent variable model for modelbased word saliency estimation for text modelling and classification. The estimation algorithm derived is able ...
In this paper we propose an integration of a selforganizing map and semantic networks from WordNet for a text classification task using the new Reuters news corpus. This neural mo...
: Document clustering has been used for better document retrieval and text mining. In this paper, we investigate if a biomedical ontology improves biomedical literature clustering ...
This work addresses the problem of classifying the genre of text, which is useful for a variety of language processing problems. We propose statistics of POS histograms as classiï...
Sergey Feldman, Marius A. Marin, Mari Ostendorf, M...
This paper presents a statistical model for discovering topical clusters of words in unstructured text. The model uses a hierarchical Bayesian structure and it is also able to iden...