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Latent Dirichlet allocation (LDA) has been widely used for analyzing large text corpora. In this paper we propose the topic-weak-correlated LDA (TWC-LDA) for topic modeling, which constrains different topics to be weak-correlated. This is technically achieved by placing a special prior over the topic-word distributions. Reducing the overlapping between the topic-word distributions makes the learned...
Text visualization becomes an increasingly more important research topic as the need to understand massive-scale textual information is proven to be imperative for many people and businesses. However, it is still very challenging to design effective visual metaphors to represent large corpora of text due to the unstructured and high-dimensional nature of text. In this paper, we propose a data model...
To illustrate the WORDij approach to automatic social network identification from large volumes of text, this research mined the social networks among President Clintonpsilas cabinet members (n=24) and also President G.W. Bushpsilas cabinet members (n=45) over each of their two terms based on the members co-occurrence in news stories. The software used a time-slice interval of 30 days for Clinton...
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