Temporal analysis of text data using latent variable models

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Temporal analysis of text data using latent variable models
Authors: Lasse L. Mølgaard, Jan Larsen (DTU Compute), Cyril Goutte
Citation: Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on  : 1-6. 2009
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Publisher: IEEE
Meeting: IEEE International Workshop on Machine Learning for Signal Processing, 2009
Database(s): Google Scholar cites
DOI: 10.1109/MLSP.2009.5306265.
Link(s): http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?action=rtdoc&an=15703730&lang=en
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Temporal analysis of text data using latent variable models describes temporal text mining with stepwise probabilistic latent semantic analysis and global multiway PLSA.

[edit] Data

Texts from Wikipedia was used to test the algorithm. Pages assigned to categories "Baroque composers" and "American composers" were used producing a corpus consisting of 7358 documents. 18536 terms were identified. Composers birthday were used as a third dimension.

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