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ICDM
2007
IEEE
173views Data Mining» more  ICDM 2007»
13 years 11 months ago
Sparse Word Graphs: A Scalable Algorithm for Capturing Word Correlations in Topic Models
Statistical topic models such as the Latent Dirichlet Allocation (LDA) have emerged as an attractive framework to model, visualize and summarize large document collections in a co...
Ramesh Nallapati, Amr Ahmed, William W. Cohen, Eri...
IEEECIT
2009
IEEE
14 years 3 days ago
Describing Web Topics Meticulously through Word Graph Analysis
Topic description is as important as topic detection. In this paper, we propose a novel method to describe Web topics with topic words. Under the assumption that representative wo...
Bai Sun, Lei Shi, Liang Kong, Yan Zhang
NIPS
2004
13 years 6 months ago
Parametric Embedding for Class Visualization
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
13 years 11 months ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei